Tissue marker detection systems and methods employing improved return signal processing and / or transmit ensembles

Abstract

Ultrasound systems and methods transmit wideband ultrasound via a probe to excite and detect markers in bodily tissue ( e.g. , breast, lung). For example, a transmitted pulse ensemble can advantageously include pulses with different frequencies from on another. Returning ultrasound energy detected by the probe is processed via a return signal processing chain to discern the response of a marker from other detected ultrasound. The processing is sufficiently fast to accommodate movement of a typically handheld probe, while providing accurate localization. Processing can include: RF filtering and mixing, demodulation, and "image" processing based on known geometry of the marker and its response signature. Target detection can include brightness mapping, sigma mapping with frame-to-frame comparisons, and segmentation mapping. Target analysis can include ranking targets based on a set of target characterizing criteria. Optionally, a nonlinearity is introduced into the transmissions, and used in discerning the marker responses.

Description

TISSUE MARKER DETECTION SYSTEMS AND METHODS EMPLOYING IMPROVED RETURN SIGNAL PROCESSING AND / OR TRANSMIT ENSEMBLESCross-Reference to Related Application

[0001] This patent application claims priority of U.S. Patent Application No. 63 / 625,167, filed on January 25, 2024, the entire disclosure of which is hereby incorporated by reference herein for all purposes.Field

[0002] This disclosure generally relates to ultrasound systems and methods employing ultrasound to detect markers, which may, for example, facilitate detection of margins of bodily tissue (e.g., abnormal bodily tissue) to be monitored, biopsied, excised or ablated, for instance during surgical procedures.BACKGROUNDDescription of the Related Art

[0003] Various types of markers are used to mark bodily tissue that is to be monitored over time, or biopsied, excised or ablated. Some markers may, for example, allow or enhance visual detection, for instance by a surgeon during a surgical procedure. Some markers allow detection via various type of energy emitted imaging modalities, for example ultrasound imaging, radiological imaging such as X-ray imaging, computerized tomography (CT) imaging, computerized axial tomography (CAT) imaging, or magnetic resonance imaging (MRI). These different imaging modalities are often employed in different scenarios, by different clinicians or technicians, and markers detectable under the various visual detecting or imaging modalities typically require different physical characteristics in order to be detectable.

[0004] Some markers may be permanent, while other markers may be absorbable by the body over a period of time. For example, it may be useful to mark a portion of bodily tissue for subsequent evaluation or detection over a fairly extended period (e.g., months, year).

[0005] Applicant has developed multi-modal markers which are detectable via ultrasound, as well as detectable via additional imaging modalities (e.g., X-Ray,MRI and / or other imaging technologies), and are optionally absorbable over time, and which can be long lasting (e.g., persisting for approximately 9 months).

[0006] Markers for use in bodily tissue take a variety of forms, and can include a plurality of ultrasound reflective elements and one or more gels (e.g., hydrogels) that binds the ultrasound reflective elements. The ultrasound reflective elements can, for example, take the form of porous or mesoporous particles or porous or mesoporous hollow shells. Cavities and / or pores of the ultrasound reflective elements (e.g., hollow shells, porous or mesoporous particles) can be filled with a fluid, for example a gas such air, a liquid, or a combination of gas and liquid (e.g., a vapor) and may advantageously can optionally be devoid of perfluorocarbon. The ultrasound reflective elements can be coated, for example with a hydrophobic coating, to at least temporally seal the pores to prevent or delay the ingress of liquid into the cavities to interior of the ultrasound reflective elements (e.g., hollow shells, porous or mesoporous particles).

[0007] The ultrasound reflective elements can comprise or consist of silica in one or more forms. The gels (e.g., hydrogel(s)) can be a natural gel, for instance gelatin, or an artificial gel, for instance polyethylene glycol (PEG), or the marker can be comprised of both natural and artificial gels (e.g., natural and artificial hydrogels). The gel(s) may be partially or fully cross-linked. The gels (e.g., hydrogel(s)) can be engineered to be absorbed by the body over a period of time, or alternatively may be non-absorbable.

[0008] The markers can optionally include contrast elements or “contrast agents” that permit the markers to be detected via one or more imaging modalities in addition to being detectable via ultrasound. For example, the markers can include one or more radiopaque material (e.g., metal, gold, platinum, tantalum, bismuth, barium and the like) to allow the markers to be detectable via X-ray imaging. For instance, the markers can include a metal element in the form of a clip (e.g., metal wire with a defined shape for instance a helical wound metal wire), strand or coil, or in the form of a plurality of metal particles. Also for example, the markers can include one or more MRI imaging contrast materials (e.g., as gadolinium including compounds such as gadolinium DTPA, ferrous gluconate, ferrous sulfate and the like) to allow the markers to be detectable via MRI imaging. Also for example, themarkers can include one or more dyes (e.g., florescent dyes, methylene blue) to allow the markers to be more readily visually detected.BRIEF SUMMARY

[0009] There is a need for improved imaging techniques that do not employ ionizing radiation, for instance improved ultrasound imaging techniques that may enhance detection of markers in bodily tissue and / or detection of the margins of certain bodily tissues (e.g., abnormal bodily tissues, for instance tumors, or bodily tissues suspected of being abnormal) that are marked with implanted markers. Such can advantageously allow marker localization in surgical scenarios where ionizing radiation sources may not be readily available or may be undesirable or otherwise inconvenient to use.

[0010] This disclosure generally relates to detection of markers in bodily tissue, and further relates to systems and methods which can, for example, employ ultrasound processing to facilitate more precise detection of tissue to be monitored, biopsied, excised or ablated than otherwise possible using conventional approaches. The systems and methods advantageously do not require ionizing radiation to perform marker localization in at least some settings or implementations. The systems and methods can be particularly suited for use in surgeries, for example by surgeons or others who are not specialized or dedicated medical imaging technicians or are not specialized or dedicated ultrasound technicians. Thus, it is particularly advantageous if operation of the systems and methods is simplified, for instance requiring no manual adjustment of settings or input parameters by the operator (e.g., surgeon). It is additionally particularly advantageous if operation of the systems and methods accommodates the movement of the hand of an operator holding a probe (e.g., ultrasound probe) who is typically not a skilled or dedicated ultrasound technician, by for instance accommodating imprecise and / or rapid or uneven movement (e.g., varying velocity) of the probe. It is further particularly advantageous if operation of the systems provide for precise localization in at least a two-dimensional area, and preferably in a three-dimensional volume, for example using visual and / or aural indications or alerts. It is even further particularly advantageous if the systems provide accurate results, resulting in few or even no false results (e.g., false detections or false alerts; missing a marker when a marker ispresent). User feedback can be provide visually (e.g., representation of marker or cross hairs relative to image of anatomy) and / or aurally (e.g., aural alerts as probe moves towards or away from marker in one, two, or even three dimensions.)

[0011] The ultrasound system (e.g., hardware, software, firmware) employs excitation and detection algorithms that discern responses from the marker, and provides an intuitive indication (distinctive visual indication that does not itself represent bodily tissue, distinct aural alert). Such is a very different approach as compared to commercial off-the-shelf ultrasound systems. While a trained clinician can use ultrasound images to locate a marker in tissue, the approach described herein allows much faster acquisition and a hands free, no setting, user experience. In contrast, conventional ultrasound requires a trained clinician to adjust the settings of the ultrasound machined. Conventional ultrasound is an interpretive visual activity, requiring a trained clinician to visual interpret displayed ultrasound images. In the approach described herein, the ultrasound system alerts the clinician in real time whether a marker has been found, and where that marker is in the tissue. So the clinician receives what can be characterized as a binary answer (e.g., visually distinctive and aural indications of presence are presented when a marker is located) and with automatic ranging (e.g., distance and direction relative to current location), versus the clinician having to try to interpret anatomical structures in ultrasound images. With the approach described herein, there is no need for knobs or for the clinician to adjusts setting, the clinician instead just get a fast, simple, detection with intuitive operation, without disrupting the normal workflow of the operating room. This is particularly important in surgical environments with a patient under anesthesia, in sterile field, and where the clinician is typically a surgeon who likely is not as experienced with using ultrasound as an ultrasound technician, and who is occupied with other aspects of the surgical procedure.

[0012] Unlike conventional approaches in which ultrasound energy is focused on a specific region-of-interest (ROI), in one or more implementations described herein, the transmit beam model spreads energy across all of the interrogation space. For example, the ultrasound system can drive an ultrasound probe to emit ensembles of ultrasound pulses, where each pulse in a given ensemble has a different frequency from the other pulses in the ensemble. The frequencies of the pulses in a given ensemble can extend partially or even fullyacross a range of frequencies that the ultrasound probe (e.g., crystals) is capable of emitting. Such can flatten and extend the response curve (e.g., K-curve) for ultrasound energy returned from ultrasound reflective particles, advantageously reducing volatility and prolonging the time during which a response from the ultrasound reflective particles is detectable. This transmit approach can be employed with the receive signal processing chain described herein or can be employed with other approaches to receive signal processing (e.g., the receive signal processing approaches described in U.S. patent application 63 / 441 ,558; and U.S. patent application 63 / 525,280, and patent applications that claim benefit or priority to those two patent applications) while still providing a technical advantage (e.g., moving away from fundamental frequency and improving sensitivity of the response signal processing chain, increasing persistence of response, and / or lowering transmit voltages and hence background noise).

[0013] In one or more implementations described herein, returning ultrasound energy detected by the probe is processed via a return signal processing chain to discern the response of a marker from other detected ultrasound. The processing is sufficiently fast to accommodate movement of a typically handheld probe, while providing accurate localization. Processing can include: RF filtering and mixing, and demodulation. Processing can include target detection via “image” processing and target analysis based on a known geometry of the marker and its response signature. Target detection can include brightness mapping, sigma mapping with frame-to-frame comparisons, and segmentation mapping. Target analysis can include ranking targets based on a set of target characterizing criteria. Optionally, a nonlinearity is introduced into the transmissions {e.g., pulses in a given ensemble of pulses have different frequencies from one another), and used in discerning the marker responses. The improved return signal processing chain can realize various technological advantages as compared to other approaches to receive signal processing {e.g., the receive signal processing approaches described in U.S. patent application 63 / 441 ,558; and U.S. patent application 63 / 525,280, and patent applications that claim benefit or priority to those two patent applications), for example improved sensitivity, and more stable, reliable and consistent results {e.g., less false positives detections, less false negative detections).

[0014] In at least some implementations, a GPU executed algorithm advantageously implements a parallel processing return signal processing chain to discriminate a response from a marker from all the other signals and noise that is detected.

[0015] A detection imaging system is designed to aid clinicians (e.g., surgeons) to find implanted tissue markers (e.g., OneMark™ markers from View Point Medical). The system is used to scan and localize physical implanted tissue markers in bodily tissue (e.g., breast tissue, lung tissue). The system transmits pulsed ultrasound energy to excite the tissue marker, and then compares changes in the motion between pulse sets from the received ultrasound energy (e.g., return signal or a series of return signals, which can constitute a scattered or backscatter return of ultrasound energy from the tissue marker or portions of the tissue marker). The pulses cause higher variation at locations where tissue markers have been placed as compared to the energy level in unmarked areas. The system highlights the tissue marker location, for example on a display screen (e.g., liquid crystal display (LCD)), for instance using a color map overlay on a low-resolution gray scale representation of anatomical background. The system additionally or alternatively indicates the location of the tissue marker to the clinician using additional audio and visual feedback, for instance as an X-Y crosshairs centered over the marker in a low- resolution gray scale representation of anatomical background.

[0016] In general, surgeons seek to site-center tissue markers so they resect around the tissue marker and get reasonable confirmation they have made the correct resection. The system supports the current standard of care for lesion localization and provides more visual information than currently used wire-free localization devices that do not visually display the tissue marker. The presently described systems and methods can produce localization information that advantageously represents a centroid of a tissue marker (e.g., visually represented with cross hairs), in contrast to sound or wire center of a tag, and can prove for realtime image centering of the tissue marker which is particularly uniquely advantageous in surgical settings.

[0017] The scan process applies a non-diagnostic, custom, ultrasoundbased method to excite the tissue marker and give clinicians (e.g., surgeons) a real time image of the location of the tissue marker location from the skin surface and inthe wound during resection. Unlike traditional diagnostic ultrasound imaging, the system does not need to provide quantitative information about anything scanned other than the tissue marker the system is designed to detect. Unlike ultrasound systems that are intended to show all the structural characteristics (e.g., anatomy) of tissue, the OneMark™ system optionally, and preferably, does not offer diagnostic ultrasound modes, is not intended as a tool for qualitative analysis of tissue itself and does not provide adjustment controls like would be common in a diagnostic tool. The system can be used to image a tissue marker location for the purposes of providing information to aid in clinical localization. The system advantageously requires almost no setup and is designed to be used by surgeons that are not dedicated ultrasound technicians and by those who generally do not operate ultrasound equipment in their daily practice. It is designed for maximum ease of use by automating the marker detection process, eliminating buttons and / or keys or keyboards to better accommodate sterile field application. The system also advantageously supports rapid marker detection to efficiently support clinicians treating patients under anesthesia.

[0018] In contrast to most ultrasound systems used for diagnostics which try to focus the transmitted ultrasound energy to a point of interest, the presently described ultrasound systems and methods in at least one mode spreads the transmitted wideband ultrasound energy across an entire area of interest (e.g., entire breast, entire lung). Thus, rather than attempting to improve resolution as is done in diagnostic ultrasound, the presently described ultrasound systems and methods try to achieve a high, or even best, power coupling with the tissue marker. The ultrasound can be transmitted as ensembles of pulses along various axes, angles or beams, each associated with a respective piezo-electric element, crystal or transducer of an ultrasound probe. In contrast to most ultrasound systems which employ a relatively low frame rate with a relatively high number of pulses per ensemble, the presently described ultrasound systems and methods typically employ a relative high frame rate with a relative low number of pulses (e.g., 3, 4, 5) per ensemble, and also typically employ a relative low number of focus depths (e.g., 2), all to achieve sufficient speed to accommodate expected hand movements of the ultrasound probe. The presently described ultrasound systems and methods can, for example, employ ensembles of 5 pulses down each beam and at 2 different focaldepths when operating in detector (D) mode. The presently described ultrasound systems and methods can, for example, employ ensembles of 4 pulses down each beam when operating in B-mode. In at least some implementations, the presently described ultrasound systems and methods can, for example, advantageously vary a characteristic (e.g., frequency, period) of each pulse in an ensemble of pulses (pulse ensemble), flattening a response curve (e.g., K-curve) of received responses and increasing the persistence of a detectable returned response.

[0019] Notably, the more pulses in an ensemble the more time it takes to transmit, receive and process the ultrasound. This, along with the relying on identification of a tissue marker’s response in multiple consecutive frames to accurately determine marker location, and the fact that the ultrasound probe will typically be hand-held and subject to movement, places constraints on the technical operational aspects including the transmit model, frame rate and the receive signal processing chain. Additionally, while a relatively large amplitude (e.g., voltage) of the transmitted ultrasound pulses can facilitate detection of responses by the tissue markers, some practical considerations can place constraints on such. For instance, thermal limits of the piezo-electric elements, crystals or transducers or of a head of the ultrasound probe and constrain the amplitude of the transmitted ultrasound pulses that can be employed.

[0020] The presently described ultrasound systems and methods can employ a receive signal processing chain to process a return signal or a series of return signals, which can constitute a scattered or backscatter return of ultrasound energy from the tissue marker or portions of the tissue marker. The tissue marker or tissue markers also referred to herein simply as a marker or markers. The receive signal processing chain can include one, more or all of: RF filtering and mixing, demodulation and envelope detection, and target detection via “image” processing and target analysis. The receive signal processing chain can employ defined target characterizing criteria based on a known geometry of the marker and its response signature. Target detection can include brightness mapping, sigma mapping with frame-to-frame comparisons, and segmentation mapping. Target analysis can optionally include ranking targets based on a set of target characterizing criteria. Target analysis can optionally include a determination of whether a marker has been detected or not based at least in part on the ranking. The processing is sufficientlyfast to accommodate movement of a typically handheld probe, while providing accurate localization.

[0021] In some implementations, a system (e.g., ultrasound system) advantageously injects a nonlinearity (e.g., variation in frequency or period between pulses in a pulse ensemble) in a drive signal, that produces a nonlinearity in an ultrasound transmit or interrogation signal, but which preferably does not generally change a direction of emission of the ultrasound pluses. The nonlinearity can produce a nonlinear response or return from a tissue marker e.g., from echogenic portions of the tissue marker), thus facilitating the detection (e.g., match filtering) of the tissue marker by the ultrasound system. The nonlinearity may be periodic, may form or follow a defined pattern, or may be pseudo-random or random.

[0022] In some implementations, a system (e.g., ultrasound system) and method advantageously processes received ultrasound energy to identify responses from the tissue marker and provides visual and / or aural indications of a presence and / or location of the tissue marker, and in particular detailing an implementation of target detection in a target detection phase (detector mode or D mode) implemented by a receive signal processing chain the ultrasound system.

[0023] As an overview, target detection can include execution of a target ranking algorithm or process, which is designed to assign values to each blob that reflect how well the blob matches a specified set of target characterizing criteria. The target ranking algorithm or process operates on flattened sigma sector data (e.g., arrayed in a 48 x 2640 matrix) to generate equally sized connection and distance matrices. A segmentation map can represent a set of potential blob centroids and their left, right, up, and down extents. These centroids are then assessed, for example to determine how well the centroid matches the specified set of target characterizing criteria. The specified set of target characterizing criteria can, for example, include one, more or all of: frame metrics, region of interest metrics, region of interest relational metrics, and / or shape, of an ultrasound response of a tissue marker. Each target characterizing criterion can be assigned a respective weight, based on its significance in characterizing a target. This centroid of a target can be passed along to a centroid tracking algorithm or process. The use of centroids is particular advantageous in applications were a tissue marker is being used to mark tissue for inspection, monitoring, resection and / or ablation. Forexample, the presence or the absence of the response signal from the tissue marker can be detected based at least in part on the ranking of each of the plurality of targets with respect to one another.BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0024] In the drawings, identical reference numbers identify similar elements or acts. The sizes and relative positions of elements in the drawings are not necessarily drawn to scale. For example, the shapes of various elements and angles are not drawn to scale, and some of these elements are arbitrarily enlarged and positioned to improve drawing legibility. Further, the particular shapes of the elements as drawn, are not intended to convey any information regarding the actual shape of the particular elements, and have been solely selected for ease of recognition in the drawings.

[0025] Figure 1 A is an isometric view of a marker to mark bodily tissue and a distal portion of an instrument selectively operable to implant the marker at a desired location in bodily tissue according to one illustrated implementation, the marker comprising: a persistent (e.g., long term) portion and two otherfast dissolving portions.

[0026] Figure 1 B is an isometric view of a marker according to one illustrated implementation, the marker can for example take the form of a persistent (long term) portion (Figure 1A) comprising a gel (e.g., hydrogel) carrier, a plurality of ultrasound reflective elements, a clip, strand or coil detectable via X-ray imaging, and optionally a contrast agent to enhance detection in imaging modalities other than ultrasound, with an enlarged detailed view showing one of a plurality of agglomeration or clusters of the ultrasound reflective elements (e.g., ultrasound reflective particles or ultrasound reflective shells) in detail.

[0027] Figure 2 is a schematic view of an ultrasound system according to at least one illustrated implementation, with an ultrasound transducer positioned with respect to a marker that is ultrasound reflective and typically implanted in bodily tissue, the ultrasound imaging system operable to cause transmission of wideband ultrasound signals into the bodily tissue and process received ultrasound energy to discern or identify responses from the marker, and to provide suitable visual and / or aural indications of the presence and / or location of the marker.

[0028] Figure 3 is a block diagram showing an exemplary structure of an ultrasound system, according to at least one illustrated embodiment.

[0029] Figure 4 is a block diagram showing an exemplary receive signal processing chain of an ultrasound system according to at least one illustrated embodiment, and in particular detailing a receive signal processing chain thereof.

[0030] Figure 5 is a high level block diagram of a receive signal processing chain operable to process received ultrasound energy to detect at least a presence or an absence of responses from a marker (e.g., tissue marker) and to provide visual and / or aural indications of a presence and / or location of the marker according to at least one illustrated embodiment.

[0031] Figure 6 is a graph showing generation of transmit pulse ensembles, according to at least one illustrated implementation.

[0032] Figure 7 is a flow diagram showing a method of operation of a receive signal processing chain to perform initial processing on raw RF data received from an ultrasound probe or transducer array, according to at least one illustrated implementation.

[0033] Figures 8A and 8B are a flow diagram showing a method of operation of a receive signal processing chain, according to at least one illustrated implementation.

[0034] Figure 9 is a flow diagram showing a method of operation of a receive signal processing chain to perform GPU RF demodulation processing on raw RF data received from an ultrasound probe or transducer array, according to at least one illustrated implementation.

[0035] Figure 10 is a flow diagram showing a method of operation of a receive signal processing chain to implement GPU RF target sigma map stages, according to at least one illustrated implementation.

[0036] Figure 11 is a flow diagram showing a method of operation of a receive signal processing chain to find or detect regions of interest (ROIs), according to at least one illustrated implementation.

[0037] Figure 12 is a flow diagram showing a method of operation of a receive signal processing chain to implement a GPU amplitude segmentation processing chain to generate amplitude segmentation output, according to at least one illustrated implementation.

[0038] Figure 13 shows a GPU idle detection method implemented between a single board computer (SBC) and a GPU (SBC / GPU Domain), used to execute at least part of a receive signal processing chain, according to at least one illustrated implementation.

[0039] Figure 14 is a flow diagram showing a method of performing a single region of interest (ROI) finder sequence as part of a receive signal processing chain, according to at least one illustrated implementation.

[0040] Figure 15 is a flow diagram showing a method of target analysis as part of operation of a receive signal processing chain to find, analyze and track targets, according to at least one illustrated implementation.

[0041] Figure 16 is a flow diagram showing a method of operation of a receive signal processing chain to find, analyze, track and display targets, according to at least one illustrated implementation.

[0042] Figures 17A and 17B are schematic diagrams that show transmit (TX) and receive (RX) signal path components of an ultrasound system that implements transmit and receive signal processing chains, according to at least one illustrated implementation.DETAILED DESCRIPTION

[0043] In the following description, certain specific details are set forth in order to provide a thorough understanding of various disclosed embodiments. However, one skilled in the relevant art will recognize that embodiments may be practiced without one or more of these specific details, or with other methods, components, materials, etc. In other instances, well-known structures associated with processors (e.g., microcontrollers), piezo-electric elements, crystals or transducers, power supplies such as DC / DC power converters, computing systems, and communications networks (e.g., cellular, packet switched), as well as other communications channels, have not been shown or described in detail to avoid unnecessarily obscuring descriptions of the embodiments.

[0044] Unless the context requires otherwise, throughout the specification and claims which follow, the word “comprise” and variations thereof, such as, “comprises” and “comprising” are to be construed in an open, inclusive sense, that is, as “including, but not limited to.”

[0045] Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0046] As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the content clearly dictates otherwise. It should also be noted that the term “or” is generally employed in its sense including “and / or” unless the content clearly dictates otherwise.

[0047] As used in this specification and the appended claims, the terms left, right, up, and down are used to indicate four directions along two perpendicular axes with respect to a location, position or cell in a two-dimensional array of layout of data. For example, the terms left and right can refer to nearest neighbors in a row, on respective sides of a specified location, position or cell in the array. Likewise, the terms up and down direction can refer to nearest neighbors in a column, spaced relatively above and spaced relatively below a specified location, position or cell in the array. It is noted that the terms left, right, up, and down are used for convenience and in a relative sense, not an absolute sense. Hence, an orientation of the array or arrangement of data can be changed, for example rotated 90 degrees, 180 degrees or mirrored.

[0048] Unless otherwise specified, the use of the ordinal adjectives "first," "second,” and “third,” etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking or in any other manner.

[0049] As used in this specification and the appended claims, the terms module or modules when used with respect to executable-instructions includes, by way of example, components, such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, andvariables. The functionality provided for in the components and modules may be combined into fewer components and modules or further separated into additional components and modules.

[0050] As used in this specification and the appended claims, the terms tissue maker and marker are used interchangeably as are the terms tissue markers and markers.

[0051] The headings and Abstract of the Disclosure provided herein are for convenience only and do not interpret the scope or meaning of the embodiments.

[0052] In particular, described herein systems and methods that can determine the presence or absence and / or a location of tissue markers in bodily tissue using ultrasound. Such can, for example, be used to more precisely define the margins of abnormal or suspect tissue (e.g., a tumor) in bodily tissue.

[0053] Figure 1A shows a marker 100 to mark bodily tissue and a distal portion of an instrument 101 selectively operable to implant the marker 100, or a portion thereof, at a desired location in bodily tissue according to one illustrated implementation.

[0054] The distal portion of an instrument 101 is shown in cross-section to better illustrate the marker 100. The instrument 101 can take the form of an applicator and the distal portion of the instrument 101 can take the form of needle or similar structure with a lumen 101 a, in which the marker 100 is loaded and / or through which the marker 100 passes in use. The marker 100 is shown offset (e.g., radially inwardly) of an inner wall 101 b that delimits the lumen 101 a to better illustrate an outer perimeter of the marker 100, although typically the marker 100 will be closely received by, and even in contact with, the inner wall that delimits the lumen 101 a. The distal portion of an instrument 101 has an opening 101 c at a distal end thereof. The distal portion is shown as having a pointed or sharp end, for instance to puncture or cut bodily tissue.

[0055] In implementation illustrated in Figure 1A, the marker 100 comprises: a persistent (e.g., long term) portion 100a and two other fast dissolving portions 100b, 100c. In some implementations, one or both of the two other fast dissolving portions 100b, 100c can be optional and hence omitted in certain implementations.

[0056] The persistent portion 100a includes a gel body 104a, a plurality of ultrasound reflective elements 102a, 102b (only two called out) that are detectable using ultrasound (e.g., detectable in detector (D) mode), and one or more detectable objects 106 that are detectable using another imaging modality other than ultrasound. The ultrasound reflective elements 102a, 102b can, for example take the form of porous or mesoporous hollow shells (as illustrated in Figure 1A) and / or as porous or mesoporous particles(as illustrated in Figure 1 B), which are described in more detail herein. The porous or mesoporous hollow shells may, in at least some implementations, be distinguishable from porous or mesoporous particles in that the porous or mesoporous particles do not include a single, primary interior cavity to which two, more or typically all pores connect (provide a fluidly communicative path between the exterior of the shell and the single, primary internal cavity or interior thereof but for the sealing coating (hydrophobic coating), unlike shells which include at least a single primary cavity to which two, more or all pores are fluidly communicatively coupled. The detectable object(s) 106 can, for example, take the form of a clip or strand or coil (e.g., metal) that is detectable using X-ray imaging, as described in more detail herein.

[0057] The gel body 104a can, for example, take the form of a hydrogel which is partially or fully cross-linked to enhance longevity when implanted in the bodily tissue that allows detection via ultrasound and other imaging modalities throughout the diagnostic and therapeutic treatments. The gel body 104a that has been partially or fully cross-linked can also advantageously facilitate bio-adhesion between the marker 100 and the bodily tissue in which the marker 100 is implanted, the bio-adhesion achieved via the wound healing process. For example, the gel body 104a provides a fibrosis scaffolding, fostering bio-adhesion without a glue or adhesive. For instance, the polymer combination of gel body 104a is engineered to facilitate slight ingress of natural fibrosis healing.

[0058] A first fast dissolving portion 100b of the two other fast dissolving portions 100b, 100c (the relatively inner portion that is proximate the persistent portion 100a) can likewise include a gel body 104b and a plurality of ultrasound reflective elements 102c (only one called out). The gel body 104b of the first fast dissolving portion 100b can be polyethylene glycol (PEG) and is generally not crosslinked or not highly cross-linked, allowing rapid hydration and hence rapid activationof the ultrasound reflective elements 102c thereof. This rapidly provides a response to ultrasound, aiding detection by a clinician using the system during the initial implantation of the marker 100. The first fast dissolving portion 100b is allowed to dissolve after serving its purpose of providing an ultrasound response (e.g., backscatter) during implantation of the marker 100.

[0059] A second fast dissolving portion 100c of the two other fast dissolving portions 100b, 100c (the outermost portion) includes a gel body 104c and typically omits ultrasound reflective elements. A portion of the gel body 104c of the second fast dissolving portion 100c extends slightly out of the opening 101 c at the distal end of the lumen 101 a of the instrument 101. The portion of the gel body 104c of the second fast dissolving portion 100c that extends slightly out of the opening 101 c has a bulbous end 104d to retain the rest of the marker 100 in the lumen 101 a prior to embedding in the bodily tissue. The gel body 104c of the second fast dissolving portion 100c can consist of, or be comprised of, PEG, and is generally not crosslinked or not highly cross-linked, allowing rapid hydration and rapid dissolving after serving its function of retaining the marker 100 in the lumen 101a of the instrument 101.

[0060] As best illustrated in the enlarged portion, each of the ultrasound reflective elements 102a, 102b, 102c has one or more pores 108 (e.g., mesoporous) and contains a fluid 110 (e.g., air or other gas). Each of the ultrasound reflective elements 102a, 102b, 102c also includes a coating, for example a hydrophobic coating 112 that seals the pores 108 or interior of the ultrasound reflective elements 102a, 102b to prevent the ingress of liquid (e.g., water) while implanted in bodily tissue. The hydrophobic coating 112 can, for example, consist of or comprise silicone or consist of or comprise of a mono-, di-, tri-, or tetra-alkoxysilane.

[0061] The ultrasound reflective elements 102a, 102b, 102c can comprise or consist of silica or another inert material (e.g.,, titanium dioxide). When implemented as porous shells, the ultrasound reflective elements 102a, 102b, 102c can, for example, be formed by depositing on a template with later removal of the template (e.g., via calcination). One exemplary process to form ultrasound reflective elements 102a, 102b, 102c as porous hollow shells starts with styrene templates in solution. The TMOS and DETA are added to plate the templates with silica. The styrene template is then removed by calcination, The resulting porous hollow shellsare then washed, and coated with a hydrophobic coating (e.g., silane) to seal the pores and / or internal cavities. The resulting porous hollow shells are then dried. Some or all of the resulting porous hollow shells are then tested to ensure they produce response to ultrasound. The resulting porous hollow shells are then ready to add to a hydrogel to build a marker 100. The ultrasound reflective elements 102a, 102b, 102c can, for example, have an overall size or dimensions or around 2mp and a wall thickness of around 30nm.

[0062] The ultrasound reflective elements 102a, 102b, 102c could alternatively comprise titanium dioxide (TiC ) with the same or similar overall structure (e.g., , pores, cavities, surface roughness, dimensions including overall size or dimensions (e.g., 2mp), shape, wall thickness (e.g., 30nm)), although would tend to have a higher toxicity and would likely require FDA approval. Other materials with the same overall structure might be viable candidates for ultrasound reflective elements 102a, 102b, 102c, particularly inert materials that remain in the body for relatively long periods of time (e.g., 9 months, 18 months) without adverse effects, and are otherwise compatible with long term in vivo use, and would not require separate FDA approval.

[0063] Typically, the ultrasound reflective elements 102a, 102b, 102c will tend to agglomerate or cluster in the gel body 104a, 104b, for example as illustrated and discussed with reference to Figure 1 B, below.

[0064] The cross-linked gel body 104a of the persistent portion 100a allows implantation and retainment in the targeted tissue at a precise location. The plurality of ultrasound reflective elements 102a, 102b provide a distinctive response to ultrasound. The clip or strand or coil (e.g., metal) 106 is detectable via X-ray imaging or potentially some other imaging modality. The shape of clip or strand or coil (e.g., metal) 106 can vary from persistent portion 100a to persistent portion 100a of markers 100, allow two or more different persistent portions 100a to be readily discerned. As mentioned above, the hydrophobic coating 112 seals the fluid 110 (e.g., air) in the pores 108 of the ultrasound reflective elements 102a, 102b, 102c. The hydrophobic coating of the ultrasound reflective elements 102a, 102b of the persistent portion 100a of the marker 100 is selected to seal the pores 108 over the long term (e.g., 9 months, 18 months) while implanted in bodily tissue and hence hydrated by bodily fluid. The relatively inner first fast dissolving portion (with porousshells) 100b facilitates implantation, since the cross-linked gel body 104a of the persistent portion 100a does not hydrate quickly enough to be visible via ultrasound during implantation. The relatively outermost fast dissolving portion (without porous shells) 100b serves as a plug.

[0065] The ultrasound reflective elements 102a, 102b of the persistent portion 100a of the marker 100 are the primary source of the ultrasound response. The ultrasound reflective elements 102a, 102b provide a fundamental scattering surface, with reflection enhanced by its porous nature with fluid 110 sealed in the 108 pores via the hydrophobic coating 112. The surface roughness and the wall thickness of the ultrasound reflective elements 102a, 102b, 102c can affect the response (e.g., backscattering) to ultrasound. The shell structure and its porous or mesoporous nature is controlled by the chemistry and chemical process, for instance via the depositing of silica fleck on a template and subsequent calcination to remove the template and create a cavity in the ultrasound reflective elements 102a, 102b, 102c. The porous or mesoporous nature allows sound energy to enter the cavity or cavities of the ultrasound reflective elements 102a, 102b, 102c, for instance into air bubbles entrapped in the cavity or cavities, eliciting or enhancing the type of scatter that facilitates detection in detector (D) mode operation. Overall size of the ultrasound reflective elements 102a, 102b, 102c and / or overall size of agglomerations of the ultrasound reflective elements 102a, 102b, 102c can shift the spectra of performance. The hydrophobic coating 112 seals the pores 108, preventing ingress of fluid into the ultrasound reflective elements 102a, 102b, 102c so that the ultrasound reflective elements 102a, 102b, 102c do not “wet out”, which would otherwise reduce the signal to noise (SNR) ratio of the ultrasound response. The ultrasound reflective elements 102a, 102b, 102c produce a B-mode response in ultrasound imaging, which is a composite effect as color mode is an overlay to B mode. The B mode signal out sends groups of B mode imaging data (also referred to as B image data or B image(s)), which in some implementations are then interpreted as color Doppler images using color Doppler techniques. This structure, particularly as suspended in a gel matrix that allows movement in response to ultrasound energy, advantageously provides for broad harmonics, detectable via detector (D) mode operation described herein. The amount of ultrasound reflective elements 102a, 102b, 102c to enable detection is very low.

[0066] In some implementations, the ultrasound reflective elements 102a, 102b, 102c may leak or otherwise leach from the cross-linked gel body 104a, but would still tend to remain proximate the site of the marker 100 and remain detectable using the ultrasound techniques and technology described herein.

[0067] An example process to form a marker 100 includes cooking the gel (e.g., hydrogel components). Ultrasound reflective elements can be coated with a hydrophobic polymer. The coated ultrasound reflective elements are added to a hot mix of the gel, for example via a syringe mixer, for instance to achieve a colloidal dispersion or suspension of coated ultrasound reflective elements in the gel. Tubes of the gel with the ultrasound reflective elements are made, for instance using a custom injector, which are used for the persistent portion 100a of the marker 100 and for the first fast dissolving portion 100b of the marker 100. T ubes without the ultrasound reflective elements are made, for instance using a custom injector, which are used for the second fast dissolving portion 100c. The tubes can then be cut to desired sizes, for instance based on the respective portions 100a, 100b, 100c of the marker 100. A detectable object 106 (e.g., clip or strand or coils or metal) is added to tubes that will be used for the persistent portion 100a of the marker 100, for example via a mandrel. The tubes are removed from the mandrel and dried.

[0068] Figure 1 B shows an exemplary marker 120 to mark bodily tissue, the marker 120 detectable via the systems and methods described herein. The various implementations and embodiments are not limited to use with the exemplary marker 120, but rather can be advantageously employed with other markers that include ultrasound detectable elements. The marker 120 can, for example, be or take the form of the persistent portion 100a of the marker 100 (Figure 1A).

[0069] The marker 120 includes a gel body 124, a plurality of ultrasound reflective elements 102a (only two called out in detailed view) that are detectable using ultrasound (e.g., detectable using detector (D) mode operation), and one or more detectable objects 106a that are detectable using another imaging modality other than ultrasound. The ultrasound reflective elements 102a can, for example take the form of porous or mesoporous hollow shells (as illustrated in Figure 1A) and / or as porous or mesoporous particles(as illustrated in Figure 1 B), which are described in more detail herein. The detectable object(s) 106a can, for example,take the form of a clip or strand or coil (e.g., metal) that is detectable using X-ray imaging, as described in more detail herein.

[0070] The ultrasound reflective elements 102 may tend to agglomerate or form agglomerations or clusters 122 as illustrated. The gel body 124 binds the agglomerations or clusters 122 of the plurality of ultrasound reflective elements 102 together. The agglomerations or clusters 122 can be dispersed throughout the gel body 124, for example in a colloidal dispersion. When the gel body 124 is hydrated, the agglomerations or clusters 122 of the plurality of ultrasound reflective elements 102 are suspended or in suspension, and movable with respect to each other and / or with respect to an external reference frame over at least a distance and in one or more directions, which can advantageously induce or increase scattering of ultrasound backscatter. In some implementations, the agglomerations or clusters 122 of the plurality of ultrasound reflective elements 102 may leak or otherwise leach from the cross-linked gel body 124, but would still tend to remain proximate the site of the marker 120 and remain detectable using the ultrasound techniques and technology described herein.

[0071] The gel body 124 may take variety of forms. The gel body 124 may, for example, comprise one or more hydrogels. The gel body 124 may comprise a natural hydrogel, for example a gelatin. The gel body 124 may comprise an artificial hydrogel, for example a polyvinyl alcohol (PVA) hydrogel or a polyethylene glycol (PEG) hydrogel. The gel body 124 may comprise a combination of a natural hydrogel (e.g., gelatin) and an artificial hydrogel (e.g., PVA hydrogel, PEG hydrogel). In at least some of the implementations, the gel body 124 is an at least partially cross-linked hydrogel. In at least some of the implementations, the gel body 124 is a gelatin, for example a cross-linked gelatin. In at least some of the implementations, the gel body 124 is a PVA hydrogel, for example a cross-linked PVA hydrogel. In at least some of the implementations, the gel body 124 is a PEG hydrogel, for example a cross-linked PEG hydrogel. In at least some of the implementations, the gel body 124 comprises a combination of a natural hydrogel and an artificial hydrogel, for instance as respective gel bodies coupled to one another.

[0072] The gel body 124 may be non-absorbable by the body (e.g., persistent over 60 years or longer), or may be absorbable by the body within of a period of time. Where absorbable, gel body 124 may be engineered (e.g., via extentand / or strength of cross-linking) to persist in the body for a period of time, for example being persistent over a period of hours, days, a week or weeks, a month or months, or even for a year or years. In at least some implementations, outer or exposed portions of an absorbable gel body 124 when implanted may absorb sooner than more interior portions of the gel body 124, the absorption occurring as various portions of the gel body 124 are exposed to bodily tissue, including bodily fluids. In at least some implementations, the gel body 124 can be engineered (e.g., controlled cross-linking profiles) to cause some portions to absorb faster than other portions and / or to ensure that some portions persist longer than other portions. Thus, various absorption profiles may be formed across or through a gel body 124.

[0073] Each ultrasound reflective element is highly reflective of ultrasound. Each ultrasound reflective element preferably has in irregular surface, for example having a rough outer surface to cause scattering or dispersion of ultrasound energy. The ultrasound reflective elements 102 may be in the nanometer size range (e.g., 1 .8 microns to about 2.2 microns).

[0074] The ultrasound reflective elements 102 are typically echogenic and can take any of a large variety of forms.

[0075] The ultrasound reflective elements 102 can be porous or mesoporous with pores and / or cavities to retain a gas. As discussed with reference to Figures 1A and 1 B, the ultrasound reflective elements 102 can include a hydrophobic coating to prevent liquid ingress, protecting the gas (e.g., air) from “wetting out” which would significantly diminish function.

[0076] In at least one implementation, each ultrasound reflective element comprises a porous hollow shell, for instance a silica porous hollow shell, which may or may not be spherical in shape. In at least one implementation, each ultrasound reflective element comprises a particle that is not a hollow shell, but which is porous, and which can be or cannot be a porous non-spherical particle. Each ultrasound reflective element may, for example, comprise a respective particle that comprises, or consists of, silica with pores but without a singular defined hollow interior cavity. Each particle may comprise one or more layers (not shown in Figures 1A and 1 B). The one or more layers may including contrast agents, to enhance detection via modalities other than ultrasound imaging, as discussed below. Alternatively, one ormore ultrasound reflective elements may comprise, or consist of, one or more contrast agents.

[0077] The gel body 124 {e.g., hydrogel carrier) and / or some or all of the ultrasound reflective elements 102 can optionally carry one or more contrast agents 126. Contrast agents 126 may, for example include one or more contrast agents that enhance unaided visual detection, or detection using X-ray or MRI imaging modalities. Contrast agents 126 can, for example, include a dye to enhance detection by direct visual observation either unaided or aided {e.g., via UV or “black light” illumination). The dye may advantageously be a florescent dye. The dye may, for example, comprise or consist of methylene blue. Contrast agents 126 can, for example, include or consist of a radiopaque material e.g., gold, platinum, tantalum, bismuth, barium and the like). Contrast agents 126 can, for example, include or consist of an MRI imaging material {e.g., as gadolinium including compounds such as gadolinium DTPA, ferrous gluconate, ferrous sulfate and the like).

[0078] Alternatively, one or more contrast agents 126, for example the contrast agents 126 identified above, may be incorporated into or about the gel body 124. A detectable object 106a {e.g., clip, thread, sting coil or helical wound metal wire or other radiopaque element) incorporated into or about the gel body 124.

[0079] In at least one implementation, each ultrasound reflective element 102 comprises a hollow shell. Each hollow shell has at least one outer wall that forms a cavity. In at least some implementations, the hollow shell is a multi-layer hollow shell, for example a shell with an inner layer and an outer layer. Each hollow shell is highly reflective of ultrasound. Each hollow shell preferably has in irregular surface, for example having a rough outer surface to cause scattering or dispersion of ultrasound energy. The hollow shells may be in the nanometer size range.

[0080] In at least some implementations, each hollow shell may comprise, or alternatively consist of, a silica or titanium dioxide. Some techniques to form hollow shells in the nanometer size range are described, for example in: U.S. patent application 60 / 955678; U.S. patent application 61 / 034468; U.S. patent application 12 / 673224 (now U.S. Patent 8440229); International patent application PCT / US2008 / 072972; U.S. patent application 13 / 866940 (now U.S. Patent 9220685); U.S. patent application 15 / 722436; U.S. patent application 61 / 707794; International patent application PCT / US2013 / 062436; U.S. patent application15 / 706446; U.S. patent application 62 / 135653; U.S. patent application 15 / 559764; International patent application PCT / US2016 / 23492; U.S. patent application 62 / 483,274; U.S. patent application 62 / 645,677; U.S. patent application 15 / 946,479; and International patent application PCT / US2018 / 26291.

[0081] In some implementations, the hollow shells or the porous particles, or one or more layers of the hollow shell or the porous particles, may comprise one or more contrast agents, for example the contrast agents identified above to enhance visual, radiological or MRI detection.

[0082] In at least some implementations, the cavity and / or pores of the ultrasound reflective elements 102 contain a fluid, that is a gas, a liquid, or a combination or mixture of one or more gases and one or more liquids, although typically a gas that remains in gaseous state even during interrogation with ultrasound energy during use may be preferred. The gas may take the form of one material while the liquid takes the form of another material, different from the material that forms the gas. Alternatively, the gas and liquid may be the same material, just in different phase states. The combination or mixture of gas and liquid may, for instance, take the form of a vapor, either in a quiescent state or when subjected to ultrasound at some threshold level of energy which causes heating. The cavity of the at least one hollow shell may, for example, contain air. Alternatively, the cavity and / or pores of the ultrasound reflective elements 102 may contain an inert gas (e.g., nitrogen, argon) or even less desirably a purflurocarbon. The cavity and / or pores is / are preferably devoid of any perfluorocarbon, for instance whether in either gaseous and / or liquid forms.

[0083] Each ultrasound reflective element 102 may be porous or mesoporous. Where the ultrasound reflective elements 102 contains a fluid ( / .e., gas, liquid, or combination or mix of gas and liquid), the ultrasound reflective elements 102 may optionally and preferably include comprise a coating to seal the cavity and / or pores, preferably a hydrophobic coating, that at least temporarily seals the cavity and / or pores thereof, preventing ingress of fluid from the bodily tissue into the pores or cavities of the ultrasound reflective elements 102.

[0084] In some implementations, the gel body 124 may be expandable, for example when implanted into bodily tissue. In some implementations the marker 120 may, in an unexpanded state, have a length of about 2 mm to about 40 mm anda transverse dimension of about 0.5 mm to about 2 mm. The marker may have a ratio of size expansion from a dried unexpanded state to a water saturated expanded state of about 1 : 1 .5 to about 1 :10. The marker 100 may have a ratio of size expansion from a dried unexpanded state to a water saturated expanded state of about 1 :2 to about 1 :3.

[0085] This disclosure also generally relates to markers 100, 120 (e.g., tissue markers) which have physically characteristics that render the markers 100, 120 more readily discernable via detector (D) mode operation when the markers 100, 120 are implanted in bodily tissue. Such markers 100, 120 can include a gel body 104a, 104b, 124 with a plurality of ultrasound reflective elements 102a, 102b, 102c (e.g., porous shells, porous particles), for instance held in suspension in the gel body 104a, 104b, 124. The ultrasound reflective elements 102a, 102b, 102c may, for example, be dispersed through the gel body 104a, 104b, 124, for instance in a colloidal dispersion or colloidal suspension throughout the gel body 104, 124.

[0086] The gel body 104a, 104b, 124 can take the form of a hydrogel. The gel body 104a, 104b, 124 can be fully or partially cross-linked, so long as when the gel body 104a, 104b, 124 is hydrated, the ultrasound reflective elements 102a, 102b, 102c are free to move (e.g., vibrate or oscillate) in at least one dimension (e.g., along at least one axis, and preferably along two or more axes) a sufficient degree or distance to enhance any scattered return from the ultrasound reflective elements 102a, 102b, 102c in response to ultrasound interrogation of the marker 100, 120.

[0087] The ultrasound reflective elements 102a, 102b, 102c typically will have an irregular surface which leads to scattering (e.g., backscattering) in response to ultrasound interrogation of the marker 100, 120. The ultrasound reflective elements 102a, 102b, 102c typically hold a fluid ( / .e., gas, liquid, or gas and liquid in combination), which enhances the backscatter in response to ultrasound interrogation of the marker 100, 120. The ultrasound reflective elements 102a, 102b, 102c typically include a hydrophobic coating (e.g., silicone) that retains the fluid (e.g., air) in the shells for an extended period (e.g., 3 months, 9 months, 18 months) while preventing the ingress of liquid even when the marker 100, 120 is subjected to bodily fluid during the extended period. Such advantageously prevents the ultrasound reflective elements 102a, 102b, 102c from “wetting out” which would diminish or even eliminate detectable scattering. The gel body 104a, 104b, 124 may be dried ordehydrated or freeze-dried until implanted in bodily tissue, and will then hydrate over a period of time as fluid (e.g., water) is absorbed from the bodily tissue. The gel body 104a, 124 also provides a framework for bio-adhesion via the natural healing process of fibrous of the bodily tissue into which the marker 100, 120 is implanted. Such can secure the marker 100, 120 in place in the bodily tissue without the use of glues or adhesives.

[0088] Various of these described physical structures or physical characteristics of the marker 100, 120 provide for, or enhance, the scattering (e.g., backscattering) of ultrasound from the marker 100, 120, and in particular contribute to a variation in position and / or velocity of the ultrasound reflective elements 102a, 102b, 102c, either individually or in agglomerations or clusters 122, which resulting broad velocity spectrum contribute to detectability using detector (D) mode ultrasound techniques described herein. The physical characteristics of the ultrasound reflective elements 102a, 102b, 102c or agglomerations or clusters 122 of the ultrasound reflective elements 102a, 102b, 102c can vary from persistent portion 100a to persistent portion 100a and / or from fast dissolving portion 100b to fast dissolving portion 100b of different ones of the markers 100, allow two or more different persistent portions 100a to be readily discerned from one another based on distinctive response signals and / or to allow two or more fast dissolving portions 100b to be readily discerned from one another based on distinctive response signals.

[0089] Without being bound by theory, it is believed that the response of the marker 100, 120 is dependent on vibration of the ultrasound reflective elements 102a, 102b, 102c in the hydrogel matrix or as leached into the bodily tissue. The vibration and / or leaching is affected by a number of factors. For example, vibration in the hydrogel matrix is effected by crosslinking lengths of PEG which limits (between 4 arm junctions is between 50-1 OOnm). This limits the range of motion of the ultrasound reflective elements 102a, 102b, 102c in matrix of the at least partially cross-linked gel body. Also for example, motion of the ultrasound reflective elements 102a, 102b, 102c from the incident transmit wave is limited by the range of sizes of the ultrasound reflective elements 102a, 102b, 102c (e.g., ~2um), and range of sizes of agglomerations or clusters 122 of ultrasound reflective elements 102a, 102b, 102c (in the range of ~2 to ~6 porous shells per cluster for an overall size of agglomeration or cluster of approximately 12um). Also for example, vibration in thehydrogel matrix is effected by spans of interstitial hydrogel ( / .e., where no ultrasound reflective elements 102a, 102b, 102c are present) between hydrophobic agglomerations or clusters 122 of ultrasound reflective elements 102a, 102b, 102c, which ranges from about 3 urn to about 15 urn, inclusive, with a typical distance of approximately 6 urn to approximately 9 urn, inclusive. As a further example, vibration in the hydrogel matrix is affected by polymer mixture crosslinking density, which can be characterized by, for instance, a measure of water swell at 15 times dry mass of polymer matrix.

[0090] Additionally, the excitation frequency affects motion behavior of the ultrasound reflective elements 102a, 102b, 102c, with maximums at specific frequencies (e.g., MHz). For example, a PEG-PEG amine hydrogel design with 8mg / ml concentration of ultrasound reflective elements 102a, 102b, 102c per pad of gel has a peak variance at 2.76 MHz, 3.33 MHz, and 4.44 MHz.

[0091] In one example, agglomerations or clusters 122 of ultrasound reflective elements 102a, 102b, 102c have a dimension of from approximately 10 urn to approximately-30 urn, and are coated or sealed to prevent the ingress of liquid and / or egress of gas. Backscatter perturbed by the ultrasound reflective elements 102a, 102b, 102c produce extra harmonics in the return signal. Such can be enhanced by choice of frequency. Changing a wavelength of the ultrasound interrogation or transmit signal to fit the scatter structure (e.g., 500 ultrasound reflective elements 102a, 102b, 102c across) advantageously results in a broad spectrum response. Cross-linking affects the range of motion of the ultrasound reflective elements 102a, 102b, 102c, as does agglomeration. Cross-linking is typically characterized on the order of Angstroms while size of ultrasound reflective elements 102a, 102b, 102c is typically characterized on the order of microns.

[0092] Figure 2 shows a marker 200 implanted in bodily tissue 202, and an ultrasound system 204 with an ultrasound probe or transducer array 206 positioned to detect the marker 200, according to at least one illustrated implementation.

[0093] The ultrasound system 204 includes a transmit section 208 and a receive section 210. The transmit section 208 generates drive signals and drives the ultrasound probe or transducer array 206 to emit ultrasound energy pulses (e.g., ensembles of pulses along each beam or angle from the respective ultrasound piezo-electric elements, crystals or transducers of the ultrasound probe or transducerarray 206). The receive section 210 receives signals (e.g., return signal or a series of return signals, which can constitute a scattered or backscatter return of ultrasound energy from the marker or portions of the marker) representative of the ultrasound energy detected by the ultrasound probe or transducer array 206, and processes the received signals to discern and / or localize a marker based on a known transmit model (e.g., pulse ensembles, pulse repetition frequency) using a receive signal processing chain, examples of which are described here. The ultrasound system 204 can operate in any one or more operational modes (e.g., A-mode, B-mode, M- mode, color Doppler mode, power Doppler mode). In some implementations, the ultrasound system 204 will alternate between modes (e.g., alternating between capturing B-mode frames for instance to image anatomy, and capturing detector (D) mode frames to detect responses from markers with echogenic features for instance without generating images of the anatomy).

[0094] In some implementations, the transmit section 208 has an associated base or fundamental frequency, that is a base or fundamental frequency of the ultrasound signals that will be emitted by the ultrasound probe or transducer array 206. Such can, for example, be in the range of 2 MHz to 20 MHz, inclusive. In some implementations, the transmit section 208 can cause the ultrasound probe or transducer array 206 to emit pulses at a variety of different frequencies, for example emitting ensembles of pulses (e.g., four pulses per ensemble) where each pulse in the ensemble of pulses is emitted at a respective frequency that is different from the frequencies of the other pulses in the ensemble. Such is illustrated in Figure 6 and discussed in more detail with respect to Figure 6, below. It is noted that this approach can advantageously reduce volatility in the response curve and prolong the time (persistence) that a response from a marker is detectable in the returned ultrasound as compared to relying on a single base or fundamental frequency for all of the pulses in an ensemble of pulses.

[0095] The ultrasound system 204 includes a master clock or oscillator 212 which outputs a timing signal. The timing signal output by the master clock or oscillator 212 can, for example, set or be used to set a nominal pulse repetition frequency (PRF), that is the frequency (e.g., default frequency or automatically set frequency or even user set frequency) at which ultrasound pulses repeat. In at least some implementations, the nominal pulse repetition frequency can advantageouslybe a default value or automatically set for example based on the type of marker being used and / or based on a type of ultrasound probe or transducer array 206 being used. Less preferably the nominal pulse repetition frequency value can be set by an operator, at least within some defined range. In other implementations, the nominal pulse repetition frequency may be a fixed characteristic of the particular ultrasound system 204 and / or marker 200 and / or ultrasound probe or transducer array 206.

[0096] As described herein, in some implementations the transmit section 208 of the ultrasound system 204 optionally introduces a variation (e.g., a nonlinearity) in the ultrasound energy emitted by the ultrasound probe or transducer array 206, and receive section 210 can employ the variation (e.g., nonlinearity) in the received ultrasound energy (e.g., a return signal or a series of return signals, which can constitute a scattered or backscatter return of ultrasound energy from the marker or portions of the marker) to facilitate marker detection (e.g., via matched filtering). For example, in at least some implementations, the transmit section 208 preferably includes a variation circuit (VAR) 214 that introduces one or more variations, preferably nonlinear variations, into the ultrasound transmissions. Such can advantageously result in or otherwise produce an artifact in the returned ultrasound which can render a response from a marker more detectable or discernable. The nonlinear variation(s) in the ultrasound transmissions can take any one or more of a variety of forms, and enhances the ability of the systems and methods described herein to reliably detect markers in the bodily tissue advantageously without requiring the reading or interpretation of ultrasound images. It is noted that various implementations of the receive section 210 and the associated receive signal processing chain can operate successfully without variations or non-linear variations being introduced into the outgoing ultrasound transmissions. It is also noted that that the various implementations of the receive section 210 and the associated receive signal processing chain can in at least some instances be simplified with respect to the illustrated implementations where variations, for instance non-linear variations, are introduced into the transmit model, for instance allowing the omission or simplification of some filtering, signal or image processing and / or culling otherwise included in the illustrated receive signal processing chain.

[0097] The nonlinear variation(s) in the ultrasound transmissions can, for example, include variations in magnitude or voltage, and hence variations in an output power of the ultrasound transmissions. Additionally or alternatively, the nonlinear variation(s) can, for example, include variation(s) in pulse repetition frequency (PRF), which indicates the number of ultrasound pulses emitted by the ultrasound probe or transducer array 206 over a designated period of time (e.g., typically between 1 kHz and 10 kHz). Alternatively or additionally, the nonlinear variation(s) can, for example, include variation(s) in a base frequency or phase of the ultrasound transmissions emitted by the ultrasound probe or transducer array 206. Thus, the optional variation may be a variation in any one or more of: magnitude or voltage, time, frequency and / or phase. The optional variation can, for example, be implemented via one or more resistors, resistor networks or rheostats to adjust a magnitude or via one or more delay circuits or capacitors, which for instance delay the clock signal. The variation may be periodic, may follow a pattern, or may be pseudo-random, for instance produced via a pseudo-random number generator, also known as a random number generator (RNG). As an example, as indicated by the broken line arrows, the optional variations can be provided to the amplifier 218 to vary magnitude or voltage, or to the gate generator 216 to vary to the PRF or phase, or to otherwise vary the base or fundamental frequency of the ultrasound transmissions. The variations can also be supplied to the receive section 210 for use in discerning which received ultrasound signals correspond to responses returned by the marker.

[0098] The receive section 210 receives signals (e.g., raw RF) representative of the ultrasound energy (e.g., return signal or a series of return signals, which can constitute a scattered or backscatter return of ultrasound energy from the marker or portions of the marker) detected by the ultrasound probe or transducer array 206. The signals typically represent ultrasound energy reflected or otherwise returned from objects in the field of view of the ultrasound probe or transducer array 206. Those objects can include the marker itself, as well as bodily tissue. The signals representative of the ultrasound energy detected by the ultrasound probe or transducer array 206 can also possibly represent outgoing ultrasound transmissions (i.e., outgoing ultrasound pulses from the ultrasound probe or transducer array 206 toward the bodily tissue) as well as other noise. The receivesection 210 includes a sophisticated receive signal processing chain 220 that includes various receive signal processing stages to remove noise, increase signal- to-noise ratio, and discern, identify and / or locate or localize those signals that represented ultrasound energy returned from the markers. The signals representative of the ultrasound energy detected by the ultrasound probe or transducer array 206 are at times denominated as received signals herein for convenience of discussion. The transmitted ultrasound is preferably wide band. As described herein, frame-by-frame analysis can be performed to isolate the transmit frequencies from the other frequencies in the responses and to identify relative large responses of the echogenic material preferably via the artifacts that represent the responses to the transmit pulse ensembles.

[0099] The receive section 210 can include one or more amplifiers 222 to amplify the received signals (e.g., return signal or a series of return signals, which can constitute a scattered or backscatter return of ultrasound energy from the marker or portions of the marker) detected by the ultrasound probe or transducer array 206. Any one or more of a various amplifiers suitable for amplifying signals from an ultrasound probe or transducer array 206 can be employed.

[0100] The receive signal processing chain 220 can optionally include a DC canceler 224 (e.g. high pass filter) that removes or cancels DC components from the received signals detected by the ultrasound probe or transducer array 206.

[0101] The receive signal processing chain 220 can optionally include one or more matched filters (e.g., pulse-matched filter) that filters the amplified signals, for example passing detected reflected or returned ultrasound pulses that match a pattern of the outgoing ultrasound pulses, and rejecting noise and other signals.

[0102] The receive signal processing chain 220 includes a set of RF stages 228. The RF stages 228 process beam-formed RF data, for example applying RF filters and mixing. The RF stages 228 are described in more detail with respect to Figure 4 (see RF stages 416) below.

[0103] The receive signal processing chain 220 includes a set of detector stages 230. The detector stages 230 demodulate the raw RF data. The detector stages 230 are described in more detail with respect to Figure 4 (see detector stages 418) below.

[0104] The receive signal processing chain 220 can include a set of target stages 232. The target stages 232 perform “image” processing on the data that represents the ultrasound signals detected by the ultrasound probe or transducer array 206 (Figure 2). The target stages 232 are described in more detail with respect to Figure 4 (see target detection stages 424) below and operation of the receive signal processing chain is described in more detail with respect to Figures 5, and 7-16, below. The target stages 232 typically look for a distinctive return signal (e.g., artifact) returned from the maker without the need to evaluate anatomical structure.

[0105] The receive section 210 can include can Include one or more presentation stages 234. The presentation stages 234 process data, for example data representing a location or centroid of a marker, and optionally data that represents anatomy, to allow presentation to a user, for example via a display screen or other visual and optionally aural indications. For example, a representation of a location of a marker or centroid of a marker (e.g., captured during detector mode or “D” mode operation) can be visually represented on a display screen overlaid or superimposed on a low resolution representation of anatomy (e.g., captured during B-mode operation) to facilitate visualization of the location of the marker with respect to various anatomical features of the body. In at least some instances, the centroid of a marker can correspond to the location of a sparkle or twinkle effect or artifact in ultrasound imaging. The presentation stages 234 are described in more detail with respect to Figure 4 (see scan converters 430 and associated beam geometry 431 and associated B map data 432, image filter stages 434, scan converters 436, image filter stages 440, image mergers 442 and image pane 444) below.

[0106] Figure 3 shows an exemplary structure of an ultrasound system 300, according to at least one illustrated implementation. The ultrasound system 300 can, for example, be an implementation of the ultrasound system 204 (Figure 2).

[0107] The ultrasound system 300 can include a housing or console that houses electronics, for example employing three custom sub-assembly circuit cards, a single board computer and a custom power sub assembly. The ultrasound system 300 is preferably fully contained with all executable instructions (e.g., software, firmware) executing internally on appropriate hardware (e.g., processors), and user output provided to an LCD screen and speakers that are part of the ultrasoundsystem 300 and preferably housed by the housing or console. In normal use, only two other electrical connections are made to the ultrasound system 300, one to the ultrasound probe or transducer array 206 and the other to AC line power (e.g., an electrical power outlet).

[0108] The ultrasound probe or transducer array 206 is preferably a self- contained transducer assembly (e.g., comprising a linear or a two-dimensional array of piezo-electric elements, crystals or transducers). The ultrasound probe or transducer array 206 connects to a back of the housing of the ultrasound system 300. The ultrasound probe or transducer array 206 can be detached and replaced, for example if defective. The ultrasound probe or transducer array 206 is managed by the ultrasound system 300 and is specifically matched to it. In at least some implementations, the ultrasound probe or transducer array 206 can, for example, take the form of a passive ultrasound probe. In at least some implementations, the ultrasound probe or transducer array 206 can, for example, provide identification capability (e.g., identification of the specific ultrasound probe or transducer array 206 or at least a make and model thereof). User interaction with the ultrasound system 300 is preferably minimized, for example to turning the ultrasound system 300 ON, placing and / or moving the ultrasound probe or transducer array 206 on or with respect to a portion of the body until a response is presented, without requiring the user to set any values or operational parameters.

[0109] The ultrasound system 300 can, for example, include a computer, preferably a single board computer (SBC) 302 (e.g., processor(s), memory or storage), and can also include an ultrasound main board 304 communicatively coupled to the SBC 302 via a hardware interface 306 and any associated drivers (e.g., software or firmware communications drivers).

[0110] The ultrasound system 300 can, for example, additionally include one or more cards or boards (not shown in Figure 3), for example to manage and distribute electrical power and / or communications (e.g., denominated herein as carrier card). The carrier card can, for example, connect and power all of the components in the ultrasound system 300, for instance: a system power supply, SBC 302, ultrasound main board 304, display monitor, USB connectors, audio speakers, fans, thermistors, and power ON switch. The carrier card can also have circuitcomponents, for example: tracking transmit regulators, magnetic high voltage supply (magnetics), audio amplifier, and / or fan motor controller.

[0111] The SBC 302 can have one or more processors and one or more memories or other non-transitory storage media communicatively coupled to the one or more processors. The processor(s) may, for example, include one or more of: microprocessors, microcontrollers, central processing units (CPUs), digital signal processors (DSPs), graphics processing units (GPUs), applications specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), and / or programmed logic controllers (PLCs), etc. The memory may, for example, include one or more of: read only memory (ROM), random access memory (RAM), EEPROMs, Flash memory, and / or registers, etc. The other non-transitory storage media may, for example, include one or more of: magnetic disks and associated magnetic disk drives, optical disks and associated optical disk drives, and / or solid state drives (SSDs), etc. In the illustrated implementation, the single board computer 302 is shown as including a CPU 308 (e.g., a CPU of a microprocessor) and a GPU 310 communicatively coupled with the CPU 308, although those of ordinary skill in the art will appreciate that other sets of components and arrangement of those components are possible and the illustrated implementation is not intended to be limiting.

[0112] The SBC 302 controls overall operation of the ultrasound system 300 and communicates through many different types of interfaces, for example: a front panel interface, a front audio interface, USB 2.0 and 3.0 interfaces, PCIe interfaces, and a power input interface. The carrier card routes these signals to their appropriate destination connector. Employing a separate card or board (e.g., carrier card) facilitates changes to the ultrasound system 300, for example allowing future changes to the SBC 302 to use different hardware and / or operating systems.

[0113] The SBC 302 can be powered from a system +12V supply that is distributed via the carrier card. The SBC 302 also shares a common ground with the ultrasound system 300. The connector can, for example, take the form of a 2 pin Samtec I PL type connector that supports both a defined maximum in rush current and a steady state current from the SBC 302.

[0114] The front panel connector interfaces the system power ON switch to the SBC 302 through a PSWIN connection and GND. The PWSIN signal is an activelow signal that signals to the SBC 302 to power ON or power OFF. This signal is preferably momentary shorted to ground to activate the power ON or power OFF sequence, hence the power switch can be implemented as a momentary ON, single pole switch. There can also be two LED signals that indicate the system power status (SUS) and hard drive activity (HD). These two signals can be active low signals and connected to a P3v3 SBC supply pin for operation. Two LEDs and two resistors are employed, one for each signal to properly indicate visually the status of these two signals. There can also be a GND pin for power and signal return currents that is to be connected to a common system ground and +3.3V power supply that is used to power the LEDs as described above. The front audio connector is used to interface with an audio amplifier on the carrier card. The audio connections can be pseudo differential and thus routed with the appropriate audio ground to the input of the audio amplifier.

[0115] A power distribution network can be comprised of switching and linear regulators, where the switches can be synchronized with a system image clock. For example, P5v2 SMPS and P5V0 regulators can be used to power circuits on the carrier card. The SMPS output voltage can be set by the P5v0 linear regulators dropout voltage. The SMPS monitors the P12v0 signals amplitude and uses two threshold voltages to determine when to change the state of the Power good signal (PG_P5v2). This signal is used to enable or disable the HV clamp circuit and disable or enable the HVP and HVM power supplies. Also for example, M5v6 SMPS and M5V0 regulators can be used to power circuits on the carrier card. The SMPS output voltage can, for example, be set by the M5v0 linear regulators dropout voltage.

[0116] The transmit clamp and enable circuits can be used to put the transmit power supply in a safe state during system power OFF or ON sequencing. This circuit employs a proper time sequencing between the two signals to ensure sufficient dead time. The FPGA preferably implements a break before make switching topology. To implement proper power ON and OFF sequencing of the HVP and HVM supplies, an active clamp circuit with an active power supply enable circuit can be employed. These two signals can be controlled by hardware to implement the timing sequence used to implement the break before make switch topology. There are two operational states for the HV clamp and HV enable circuit.The two states are active clamp and power supply disabled and the other is disabled clamp and power supply active. These two states are triggered by the P5v2 SMPS power good signal which is an output from the P5v2 SMPS regulator that is actively monitoring the voltage on the P12v0 power supply using the SMPS UVLO circuitry. An active high or +12V on the PG signal indicates the P12v0 voltage is above the UVLOrising thresholds which means the P12v0 power supply is fully turned ON and the HVP and HVM power supplies can now safely be turned ON as well. An active low or OV on the PG signal indicates the P12v0 power supply is below the UVLOfaiiing thresholds which means there is either a failure in the system or the system is powering OFF. In either case, the HVP and HVM power supplies are disabled and then clamped to ground.

[0117] The SBC USB2.0 connector can take the form of a ribbon cable type connector that is used to interface between the SBC 302 and the carrier card. There are two sets of HS USB2.0 signaling that are used to communicate between the SBC 302 and either a touch panel or a maintenance port. These are standard USB2.0 interfaces that include vBus, Gnd, and a pair of differential signals.

[0118] The USB3.0 connector can take the form of a standard USB3.0 compliant connector. The connection between the SBC 302 and carrier card is made by connecting a standard USB3.0 interface cable between the two connectors. This is the main communication path from the SBC 302 to transfer data to and from the ultrasound main board 304.

[0119] The single board computer 302 implements an operating system312 that controls overall operation of the ultrasound system 300, including system startup and system checks, and optionally controls specific operations with respect to the detection of markers and / or presentation of output (e.g., visual and / or aural) indicative of a location of detected markers.

[0120] The single board computer 302 executes a detector (D) application313 that controls specific detector related operations of the ultrasound system 300, for example processing of ultrasound energy detected by the ultrasound probe or transducer array 206 (Figure 2) via a receive signal processing chain, as described below.

[0121] In at least some implementations, the CPU 308 executes a workflow state machine and performs configuration management 314. For example, theworkflow or operation of the ultrasound system 300 from startup through processing of received signals and presentation of data can be specified as various states of a state machine, which the CPU 308 executes. Also for example, the CPU 308 can configure the ultrasound system 300, for example based on a default set of parameters.

[0122] The CPU 308 can also execute logic to handle user feedback management and control 316. For example, the CPU 308 can generate visual representations of a location of a detected marker relative to a visual representation of the anatomy and / or a visual representation of a location of the ultrasound probe or transducer (e.g., the anatomy captured during a different operational mode, for instance a B-mode, from an operational mode during which the marker is detected, for instance a D mode, with the visual representation of the location of the marker overlaid over the representation of the anatomy or vice versa). Also for example, the CPU 308 can generate aural representations of a location of a detected marker relative to a location of the ultrasound probe or transducer and / or representative of a direction of movement (e.g., beeps or other sounds corresponding to movement away from and / or towards the marker, for instance based in loudness or frequency) of the ultrasound probe or transducer with respect to the detected marker in one, two, or even three dimensions.

[0123] The CPU 308 can also execute logic to handle system settings management and control 318. For example, the CPU 308 can manage a set of settings of the ultrasound system 300, for instance using a default set of system settings, or using system settings that are based on: i) a type (e.g., make and model) of ultrasound probe or transducer that is communicatively coupled to the ultrasound system 300, ii) the type of marker being used and / or iii) the type of bodily tissue (e.g., breast, lungs) in which the marker is implanted.

[0124] The GPU 310 can implement an ultrasound processing pipeline 320 to process retuned ultrasound received by an ultrasound probe or transducer array 206 (Figure 2), which is discussed in more detail herein (e.g., see Figure 4, receive signal processing chain 402). The GPU 310 can execute logic to implement detection metrics 322 to detect markers from the detected ultrasound, which is discussed in more detail herein (e.g., see Figure 4, receive signal processing chain 402). The GPU 310 can execute logic to implement image composting 324 toproduce image data that is presentable (e.g., displayable) to a user, which is discussed in more detail herein (e.g., see Figure 4: scan converters 430 and associated beam geometry 431 and associated B map data 432, image filter stages 434, scan converters 436, image filter stages 440, image mergers 442 and image pane 444) below).

[0125] The ultrasound main board 304 can perform local and ultrasound probe control and is used for the various image sequencing events. The ultrasound main board 304 can, for example, embody firmware 323. While the ultrasound main board 304 is illustrated as employing a processor 325 in the form of an FPGA, the ultrasound main board 304 can more preferably employ one of more GPUs to enhance speed of operation.

[0126] The ultrasound main board 304 can include a software and firmware stack (e.g. Cypress USB) 326 to implement communications between the ultrasound main board 304 and with external devices, which can allow for communications with an attached ultrasound probe or transducer array 206 (Figure 2) and allow for programming of the processor 328 (e.g., FPGA, or GPU) of the ultrasound main board 304. For example, the ultrasound main board 304 can include one or more communications ports (e.g., 2 communications ports, not shown in Figure 3) that provide communications interfaces with external devices. One port can, for example, take the form of a probe port used to interface with an ultrasound probe and carry ultrasound transmit (TX) and ultrasound receive (RX) electrical signals respectively to and from the ultrasound probe or transducer array 206. The probe port can have suitable contacts or pins to communicatively (e.g., electrically) interface with complementary structure on the ultrasound probe or transducer array 206 (Figure 2), and / or include physical coupling features or structures. An optional communications port, denominated as a magnetic resonance port, can be included to provide synchronous magnetic pulses as described elsewhere herein.

[0127] The ultrasound main board 304 can include a processor 325 (e.g., FPGA or GPU) that is the center of imaging and diagnostics control via the ultrasound probe port, and optionally via a magnetics port. While the processor 325 is illustrated as an FPGA, in some implementations one or more GPUs can advantageously be employed.

[0128] The processor 325 of the ultrasound main board 304 can, for example, implement a scan state machine 330 to control the scanning by the ultrasound probe or transducer array 206 (Figure 2). The processor 325 of the ultrasound main board 304 can, for example, execute logic to provide for front end chip register access 332. The processor 325 of the ultrasound main board 304 can, for example, perform beam forming 334 on the received or returned ultrasound signals, activating the transducer array elements in a controlled manner during reception of the ultrasound energy to form a high-quality set of ultrasound image data of the field of interest. Any of a variety of beam forming approaches can be employed.

[0129] Figure 4 shows an exemplary receive signal processing chain 400 for an ultrasound system, according to at least one illustrated implementation. The ultrasound system can, for example, be an implementation of the ultrasound system 204 (Figure 2) or 300 (Figure 3).

[0130] An ultrasound probe or transducer, typically with a plurality of individual piezo-electric elements, crystals or transducers, transmits ultrasound pulses outward, for example grouped as an ensemble of pulses along each of a plurality of beam directions (e.g., an ensemble of pulses from each piezo-electric element, crystal or transducer along a principal axis of emission of the respective piezo-electric element, crystal or transducer). The ultrasound probe detects ultrasound energy, and the receive section of the ultrasound system performs processing to discern or localize the detected ultrasound energy that corresponds to a response by a marker from all other detected ultrasound energy. The processing should balance accuracy and speed of computation. In particular, the processing should be sufficiently fast to be useful in a surgical environment and sufficiently robust to accommodate the motion of the ultrasound probe which is typically handheld thus can move with varying velocities (e.g., speed and direction), and may even shake. For example, it is desirable to locate the response from a marker multiple times to enhance accuracy. Yet such can increase the time it takes to transmit pulses, receive responses and process the received responses. In at least some implementations, a marker is considered detected if its response signature if found in a defined multiple (e.g., three (3)) consecutive frames of captured ultrasound data.

[0131] The ultrasound energy emitted by the ultrasound probe or transducer array 206 can advantageously be spread across a range of frequencies producible by the ultrasound probe or transducer array 206. For example, each ensemble of pulses can include pulses at 4 distinct frequencies across the range of frequencies producible by the ultrasound probe or transducer array 206. Such can, for example, advantageously improve or increase persistence of a detectable return signal. An example is described below with respect to Figure 6.

[0132] The ultrasound energy detected by the ultrasound probe or transducer array 206 (Figure 2) can be represented by signals (received signals) and processed via a receive signal processing chain 402 of the signal processing chain 400. The receive signal processing chain 402 can be implemented via circuitry and / or processor-executable instructions stored in a non-transitory form on one or more tangible media (e.g., nonvolatile memory, spinning storage media for instance magnetic hard disk drives, optical disk drives, or solid state storage media for instance solid state drives (SSDs) or FLASH memory, the processor-executable instructions executable by one or more processors (e.g., microcontrollers, microprocessors, central processing units (CPUs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), and / or graphics processing units (GPUs). The receive signal processing chain 402 can, for example, be executed via a FPGA, or more preferably by one or more GPUs.

[0133] In particular, the ultrasound probe or transducer array 206 (Figure 2) can pass signals via a cable 404 and a communications driver 406 e.g., USB driver, PCIe driver) and a hardware interface 408 (e.g., USB compliant port or connector, PCIe compliant port or connector).

[0134] The signals can be accumulated via a frame stream buffer 410 implemented by a frame data manager. The frame data manager stores, maps or otherwise arranges (i.e., beam mapping) the RF beam data in an arrangement or format expected by the receive signal processing chain 402, for example via storing the signals to the frame stream buffer 410 in the specified format. The format or arrangement can, for example, be specified in a storage medium (e.g., non-volatile or read only memory or EEPROM, denominated as beam SIM 412). It is noted that the receive signal chain can include the cable 404, communications driver 406,hardware interface 408, frame stream buffer 410 and / or beam SIM 412, in addition to the components of the receive signal processing chain 402.

[0135] Thus, the receive signal processing chain 402 can, for example, start with a full frame of beam-formed RF data dispatched by from the frame stream buffer 410 by the frame data manager.

[0136] The receive signal processing chain 402 can optionally implement a DC canceller 414 to cancel DC components in the beam-formed RF data received from the frame stream buffer 410. The DC canceller 414 (alternatively referred to as an ensemble canceler) can, for example apply means cancelation and depth based gains, to remove averages to make differences apparent (e.g., via an ensemble canceler).

[0137] The receive signal processing chain 402 can include one or more RF stages 416 to process the beam-formed RF data to, for example, improve a signal-to-noise ratio. The RF stage(s) 416 can, for example, implement RF filtering and / or mixing. The RF stage(s) 416 can, for example, split the raw RF data. For instance, the RF stage(s) 416 can separate or split raw RF data that represents responses from a marker (pulse ensemble data) from raw RF data that represents other types of returns or reflections (e.g., non-pulse ensemble data or B data) that may represent reflections from anatomy. For instance, the RF stages 416 can employ one or more RF filters (e.g., finite impulse response (FIR) bandpass filters) to perform such real-time digital signal processing. The RF stage(s) 416 can, for example, process multiple streams of RF data, for example two streams of pulse ensemble RF data and a stream of B RF data. For example, the RF stage(s) 416 can include a number of mixers that produce RF in-phase- or direct-quadrature (IQ) signals for the various streams of pulse ensemble RF data and non-pulse ensemble RF data. For instance, mixers can mix two or more streams (e.g., two streams) of pulse ensemble data with respective multiples of a mixing frequency. RF mixing can result in two or more different multiples of mixing, which can advantageously address a possible “blinding effect” by eliminating ultrasound signals detected by the ultrasound probe that are actually outgoing transmit ultrasound signals rather than return signals. The RF stages 416 can also employ one or more low pass filters, for example to remove negative frequencies from the IQ signals. The RF stages 416can also employ one or more notch filters, for example to filter out the fundamental frequency of the ultrasound.

[0138] The receive signal processing chain 402 can include one or more detector stages 418. The detector stages 418 can demodulate the split raw RF data. The demodulation, which is also referred to as detection, removes the carrier signal and reconstructs the signal envelope (e.g., envelope detection) for each of the streams of RF data. Thus, the detector stages 418 can, for example, remove the transducer pulse frequency from the data, preventing or reducing ripple. The envelope detection can, for instance, demodulate or convert the RF signals back to an amplitude representation.

[0139] A variety of approaches can be employed to perform demodulation or envelope detection, for example: i) implementing quadrature (IQ) detection, or ii) applying a Hilbert transform. The quadrature (IQ) detection mixes (essentially multiplies) an in-phase and quadrature-phase sinusoid with the input signal, causing signal content of that frequency to be accentuated and all other content to be reduced. Such can be implemented in hardware or software. The raw signal after IQ detection can still contain ripple (e.g., at twice the carrier frequency), which can be advantageously addressed via low-pass filtering. Application of the Hilbert transform shifts the peaks of the ripples in the RF data halfway in time towards the troughs. The resulting modified signal can be combined with the original signal, so that one fills in the ripples of the other, thereby estimating the envelope magnitude. The result is a good approximation of the pulse energy, reducing the ripple while maximizing detail.

[0140] The receive signal processing chain 402 can optionally perform logarithmically compression ( / .e., log compress) 420 on the output from the RF stages 416.

[0141] The receive signal processing chain 402 can optionally perform logarithmically compression ( / .e., log compress) 422 on the output from the detector stages 418.

[0142] The receive signal processing chain 402 can include one or more target stages 424 to perform target or “image” processing on the data that represents the ultrasound signals detected by the ultrasound probe or transducer array 206 (Figure 2). The target stages 424 can, for example, perform frame-to-framecomparisons, denominated herein as sigma mapping to, for instance, identify changes or differences in the received ultrasound data from frame-to-frame. The sigma mapping can maximize signal to noise by, for example, drawing out a response of a target (e.g., return signal from marker) in the received signal data. The target stages 424 can also include target analysis via a target analyzer , for example employing a various metrics (e.g., frame metrics including line density and noise floor; region of interest metrics including average, maximum, variance, width to height or aspect ratio and / or area; region of interest relational metrics including relative positioning of ROIs) to rank various targets and / or select a target based on the metrics and / or ranking of the target. The target analyzer ranks the blobs based on specified target characterizing criteria (e.g., frame metrics, region of interest metrics, region of interest relational metrics, and / or shape, of an ultrasound response of a marker). Each target characterizing criterion can be assigned a respective weight, based on its significance in characterizing a target. The ranking of each of the plurality of targets with respect to one another can be used to detect the presence or the absence of the response signal from the tissue marker.

[0143] The receive signal processing chain 402 can include one or more focus mixers 426 (also referred to a focal merger) operable to implement a focus merge. The focus mixers 426 takes data from multiple focal depths from the previous stage and flattens the data. For example, the focus mixers 426 can take data (e.g., 48 x 2640 x 2 data) from e.g., 2 focal depths, and produce a smaller set of data (e.g., 48 x 2640 data). The focus merge combines focus sets. The focus merge can, for example, take a set of data (e.g., 48 x 2640 x 2 data) from the previous stage and flatten the data to create a smaller, flattened data set (e.g., 48 x 2640 data). This facilitates the alternating split focus in at least one implementation, by duplicating the data for depth sets. Other implementations may be able to omit such and / or employ other approaches. The focus mixers 426 can combine B focus beams and allow the detector to cross into the B stream.

[0144] The receive signal processing chain 402 can perform one or more decimations 428 to reduce a size of data sets. For example, the receive signal processing chain 402 can perform detector decimation on the sample in the beam (e.g., Detector decimation and B sample decimation).

[0145] The receive signal processing chain 402 can include one or more scan converters 430, 436 and associated beam geometry 431 and associated B map data 432 and associated color map data 438. The scan converters 430, 436 output a scan conversion on the B mode image data and detection or “D” mode image data (e.g., D Scan Conversion, B Scan Conversion.

[0146] The receive signal processing chain 402 can include one or more image filter stages 434, 440 to filter various components of images or image data (e.g., B mode image data; D mode image data).

[0147] The receive signal processing chain 402 can include one or more image mergers 442 operable to merge image data (e.g., B mode image data with D mode image data).

[0148] The receive signal processing chain 402 can include one or more image panes 444 operable to present the merged image data.

[0149] The receive signal chain 400 for an ultrasound system can include a systems interface (Vdevice model) 446, for example to read registers and tables.

[0150] The receive signal chain 400 for an ultrasound system can include a graphics interface (Pipleline DeviceVM View model) 448, which for example interfaces between a graphics engine (C++ CLR Interface) 450 and a presentation frame work (e.g., WPF for Windows applications) 452 to present images via a display screen and / or display driver (View) 454, for instance via a markup language layer (XAML III DEF) 456. The Pipeline DeviceVM View model 448 reads and writes to external files (e.g., configuration or present files 458) and external libraries (e.g., scripting 460).

[0151] Figure 5 shows a high level block diagram of a receive signal processing chain 500 operable to process received ultrasound energy to detect at least a presence or an absence of responses from a marker (e.g., tissue marker) and to provide visual and / or aural indications of a presence and / or location of the marker according to at least one illustrated embodiment. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204.

[0152] The receive signal processing chain 500 can be implemented in hardware, software and / or firmware, according to at least one illustrated implementation. The hardware may, for example, include: an analog-to-digitalconverter (ADC), a processor-based computer system that employs one or more processors and memory or other non-transitory storage media, and / or one or more of: a field programmable gate array (FPGA), a graphics processing unit (GPU), and / or an application specific integrated circuit (ASIC) which can, for example, be implemented on one or more cards or boards. The processor(s) may, for example, include one or more of: microprocessors, microcontrollers, central processing units (CPUs), digital signal processors (DSPs), graphics processing units (GPUs), applications specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), and / or programmed logic controllers (PLCs), etc. The memory may, for example, include one or more of: read only memory (ROM), random access memory (RAM), EEPROMs, Flash memory, and / or registers, etc. The other non-transitory storage media may, for example, include one or more of: magnetic disks and associated magnetic disk drives, optical disks and associated optical disk drives, and / or solid state drives (SSDs), etc.

[0153] While not illustrated, an analog transducer signal is received from ultrasound probe or transducer array 206 (Figure 2). The received analog transducer signal has a center frequency, for example a center frequency of 2.76 MHz. Optionally, the received analog transducer signal is digitized, for example via an analog-to-digital converter (not shown).

[0154] The receive signal processing chain 500 described herein can advantageously process multiple samples, for instance in parallel (e.g., four blobs), and rank the samples that have characteristics that indicate that the respective samples may represent responses from a marker, as described below, for later analysis. Each target characterizing criterion can be assigned a respective weight, based on its significance in characterizing a target. So, instead of identifying a single sample as a response during detection, the currently described approach can identify a larger number of samples as possibly representing responses from a marker, and intelligently rank those samples based on defined target characterizing criteria for later analysis, thereby improving stability, reliability and consistency.

[0155] At 502, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system 204) receives and process RF data.

[0156] At 504, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system 204) generates envelop data. Forexample, envelope detection can be performed to demodulate the RF data. Envelope detection can, for example, be performed on two different multiples of the respective transmit frequency for each pulse in a pulse ensemble or on two different multiples of a defined frequency (e.g., average of transmit frequencies of the pulses in a pulse ensemble, or some default frequency).

[0157] At 506, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system 204) performs a focus blending. For example, the ultrasound system can employ or apply ensemble focus blends to, for instance, blend transmit (tx) focus patterns for the data resulting from the envelope detection. For instance, once the envelopes have been detected, the receive signal processing chain 500 of the ultrasound system 204 blends alternating focal depths (e.g., a first focal depth and a second focal depth) at a transition depth. Adding two or more depths together can get rid of some of the transmit noise. In a current implementation two focal depths are employed since including additional focal depths would greatly increase the time involved in transmitting, detecting and processing the ultrasound, and hence placing undesirable limits on hand and ultrasound probe movement. The processing beyond this stage can be performed laterally, against the same depth position.

[0158] At 508, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system 204) generates one or more brightness maps that are indicative of intensity, strength or loudness levels (e.g., amplitudes, dBs) of the series of return signals in a set of image data. The receive signal processing chain 500 can, for example, employ ensemble averaging or ensemble averages to generate the brightness map(s).

[0159] At 510, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system 204) generates one or more sigma maps. Sigma maps represent frame-to-frame differences in the image data. Sigma maps can represent ensemble differences. Such can also represent lateral standard deviations (e.g., 3 : N angles wide). Such can also employ a squaring, for example to accentuate the dynamic range of variant responses.

[0160] At 512, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system 204) generates one or more segmentation input maps. The receive signal processing chain 500 can, forexample, employ ensemble differences and / or convolution (e.g., .25, .5, .25) to segment the image data. The segmentation input map(s) can, for example, represent radii and / or blobs (contiguous pixels or voxels with values that indicate a return was detected). The segmentation input map can represent ensemble differences. Such can employ convolution (e.g., .25 .5 .25)

[0161] Optionally at 514, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system) log compresses the brightness map, sigma map and segmentation input map.

[0162] At 516, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system 204) performs amplitude segmentation. The receive signal processing chain 500 can, for example, segment the “image” data into radii and / or blobs (contiguous pixels or voxels with amplitude values that indicate a return was detected). The amplitude segmentation can advantageously reduce data, for example using a histogram (e.g., 4096 bins) to reduce the data.

[0163] For example, to perform the amplitude segmentation, the receive signal processing chain 500 can advantageously perform K-means clustering (e.g., by amplitude). For instance, the receive signal processing chain 500 can advantageously employ a number of centroids (e.g., three centroids: centroid 0: nonzero average; centroid 1 : non-zero average + (.25 * value range) and centroid 2: non-zero average + (.50 * value range)). Also for instance, the receive signal processing chain 500 can advantageously employ various epochs (e.g., 5 epochs to 20 epochs, for instance 11 epochs, with the ideal being to convergence). Also for instance, the receive signal processing chain 500 can advantageously attempt to minimize amplitude differences from the centroid.

[0164] For example, to perform the amplitude segmentation, the receive signal processing chain 500 can advantageously perform assignment mapping or generate an assignment map. For instance, each of the samples can be assigned to one of the centroids (e.g., centroid 0, centroid 1 or centroid 2).

[0165] For example, to perform the amplitude segmentation, the receive signal processing chain 500 can advantageously perform assignment map smoothing. For instance, the receive signal processing chain 500 can perform assignment map smoothing in two perpendicular directions in the set of data,referred to as vertical and horizontal for convenience of reference. The receive signal processing chain 500 can perform vertical assignment map smoothing, for example via convolution (e.g., height 12, center weight .25, all other weights ,75 / (height-1 )). The receive signal processing chain 500 can perform horizontal assignment map smoothing, for example via convolution (e.g., width set to 3.0, center weight set to 0.25, all other weights set to 0.75 / (width- 1 )).

[0166] For example, to perform the amplitude segmentation, the receive signal processing chain 500 can advantageously generate and / or employ a segmentation mask. For instance, the receive signal processing chain 500 can generate and / or employ a segmentation masks where all samples having a value less than 1 is assigned the Boolean value 0 or False in the segmentation mask and all samples having a value equal to or greater than 1 is assigned the Boolean value 1 or True in the segmentation mask. Such can advantageously reduce data and increase computational efficiency.

[0167] At 518, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system 204) finds blobs or regions of interest. The receive signal processing chain 500 can, for example, find up to a number N (e.g., N=4) contiguous blobs in the segmentation mask sorted by size.

[0168] At 520, the receive signal processing chain 500 (e.g., receive section 210 (Figure 2) of the ultrasound system 204) performs target analysis. The receive signal processing chain 500 can, for example, determine (e.g., calculate) including one or more or even all of: frame metrics (e.g., a line density; a noise floor); region of interest metrics (e.g., average, maximum, variance, width-to-height or aspect ratio, area); and / or region of interest relational metrics (e.g. relative positioning of ROIs). The receive signal processing chain 500 can, for example, use the determined frame metrics, region of interest metrics, and / or region of interest relational metrics to rank various targets (e.g., blobs or ROIs) and / or select a target having the best or highest ranking.

[0169] Figure 6 is a graph showing wave forms 600 to generate transmit pulse ensembles for transmitting ultrasound beams to produce responses from markers, according to at least one illustrated implementation.

[0170] It is noted that the ultrasound system can employ two or more operational modes. In one operational mode, denominated as detector (D) mode,the ultrasound system causes the ultrasound probe or transducer array to emit ultrasound energy designed to elicit responses from markers. The ultrasound energy designed to elicit responses from markers is denominated herein as a target beam. In another, optional operational mode, the ultrasound system causes the ultrasound probe or transducer array to emit ultrasound energy using conventional ultrasound B mode, in order to image anatomical structure. The B mode operation is independent from the D mode operation. In at least some implementations, the B mode operation is fixed, for example at approximately 6 MHz.

[0171] In the detector mode (D mode) operation, the ultrasound energy transmitted or output by the probe is spread over a valid frequency range of probe (a frequency range at which the probe can transmit and detect). For example, the transducer probe or transducer array can be driven to emit ensembles of pulses (e.g., two or more pulses per ensemble, for instance four to six pulses to an ensemble of pulses), where a characteristic (e.g., frequency, period) of each pulse in a given ensemble of pulses is different from one another. Such can advantageously move away from a fundamental frequency as the fundamental frequency can constitute a source of noise ( / .e., noise source). For instance, while this described transmit model spreads energy across a relative wide range (2MHZ to 6MHz), the receive signal processing chain can sample a relatively quiet portion e.g., 2.75MHz) of the detected or returned ultrasound for assessing whether such contains a response from a marker. Thus, such can improve sensitivity, in addition to temporally prolonging a detectable a response. This wideband transmit approach allows the voltage of the transmit beam to be significantly lowered (e.g., lowered to around 65V) which itself can advantageously lower undesired background noise, as well as advantageously reducing thermal load on the ultrasound probe or array of ultrasound transducers.

[0172] As illustrated in Figure 6, a sine wave is used to modulate a frequency across 4 pulses that comprise a pulse ensemble, for example with the timing centered around 4 Mhz. In at least some implementations, every pulse is different in the form of frequency or period from a proceeding pulse. In at least some implementations, pulses in an ensemble start from a relatively lower frequency and progress to a relatively higher frequency (e.g., from 2MHz to 6MHz). Such can, for example, be implemented using a table (e.g., wave table) to specify the differencesin a given characteristic of the respective pulses of the pulse ensembles or otherwise alter the pulses in a given ensemble of pulses. Alternatively or additionally, such can be implemented using a pseudo-random number generator to vary the characteristics of the pulses within a defined range. The transmit (TX) waveform is the composite illustrated at the bottom of the Figure 6.

[0173] Figure 7 is a flow diagram showing a method 700 of operation of a receive signal processing chain 500 to perform initial processing on raw RF data received from an ultrasound probe or transducer array, according to at least one illustrated implementation. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204.

[0174] At 702, the receive signal processing chain 500 receives incoming frames of received raw RF data (e.g., incoming frame raw sample data, for instance 64x ADC Data Channels, 64 channels of 14 bit signed data, at a rate of 40 megasamples per second (Msps), 32msps in raw). The receive section 210 can, for example, receive incoming frame raw sample data received via the ultrasound probe or transducer.

[0175] At 704, the receive signal processing chain 500 low pass filters the received raw RF data (e.g., 16 bit signed integer samples) using one or more low pass filters. For example, the receive signal processing chain 500 low pass filters (e.g., 10 MHz low pass filter) the received RF data (e.g., 40Msps, 32msps in raw).

[0176] At 706, the receive signal processing chain 500 buffers the filtered received raw RF data (e.g., 16 bit signed integer samples) in one or more buffers, for eventual transfer.

[0177] At 708, the receive signal processing chain 500 performs raw channel interpolation (e.g., un-sample 2x, rate 80Msps) on the received raw RF data (e.g., 14 bit signed integer samples).

[0178] At 710, the receive signal processing chain 500 then performs low pass filtering (e.g., 10MHz FIR low pass filter) on the output of the raw channel interpolation (e.g., 8Msps, 14 bit signed integer samples).

[0179] At 712, the receive signal processing chain 500 performs aperture growth on the output of the low pass filtered raw channel interpolation and on the received raw RF data (received at 702) to select which beams are used forbeamforming. The output of the aperture growth can, for example be 80 / 40 Msps 20 bits, 1 beam.

[0180] At 714, the receive signal processing chain 500 performs apodization on the output of the aperture growth to weight the effect of each receive (RX) stream according to steering angle and focus. The output of the apodization can, for example be 80 / 40 Msps 20 bits, 1 beam.

[0181] At 716, the receive signal processing chain 500 performs receive (RX) beamforming on the output of the apodization. Such can advantageously delay and combine analog-to-digital (ADC) streams to produce a respective single output beam. The output of the beamforming can, for example be 80 / 40 Msps 20 bits, 1 beam.

[0182] At 718, the receive signal processing chain 500 performs digital time gain compensation (TGC) on the output of the beamforming to perform depth dependent gain. The output of the digital TGC can, for example include 80 Msps 16 bits, 1 beam and 40 Msps 16 bits, 1 beam. One output (e.g., 40 Msps 16 bits, 1 beam) of the digital TGC can be buffered at 706.

[0183] At 720, the receive signal processing chain 500 decimates the other output (e.g. 80 Msps 16 bits, 1 beam) of the digital TGC, For instance, the receive signal processing chain 500 can perform a 2x decimation, advantageously further reducing data (e.g., 40 Msps 16 bits, 1 beam) and improving computational efficiency.

[0184] At 722, the receive signal processing chain 500 low pass filters (e.g., 15 MHz lowpass) the output of the decimation via one or more low pass filters. The output of the low pass filtering can be 40 Msps 16 bits signed data, 1 beam.

[0185] The receive signal processing chain 500 buffers the output of the low pass filtering at 706.

[0186] At 724, the receive signal processing chain 500 provides the buffered data (e.g., 40 Msps 16 bits, 1 beam) for further processing by the receive signal processing chain 500. The receive signal processing chain 500 can, for example, provide the buffered data via a Universal Serial Bus (USB) connection or link.

[0187] Figures 8A and 8B are a flow diagram showing a method 800 of operation of a receive signal processing chain 500, according to at least one illustrated implementation.

[0188] The method 800 can be implemented as part of a processor-based algorithm executed, for example by one or more GPUs, and thus denominated herein as GPU Compute Processing 801. The GPU Compute Processing 801 can implement RF demodulation and target detection, denominated herein as GPU RF demodulation and target detection 801a, and can also implement pixel image processing, denominated herein as GPU pixel image processing 801b.

[0189] At 802, the receive signal processing chain 500 performs RF demodulation (e.g., GPU RF demodulation) on incoming frames of received raw RF data (e.g., incoming frame raw sample data, for instance 64x ADC Data channels). The RF demodulation can employ multiple stages. The receive section 210 can, for example, receive incoming frame raw sample data received via the ultrasound probe or transducer. The method 800 then proceeds along two parallel paths one processing received B ultrasound signals and one processing received D ultrasound signals, before merging again (at image stream mixing 810).

[0190] Along one of the two parallel paths, R-Theta blocks 804 of a GPU perform processing on the received B ultrasound signals as part of the receive signal processing chain 500. The received B ultrasound signals are provided as output of the GPU RF demodulation 802. Such can include performing R-Theta filtering 804a on the received B ultrasound signals. The R-Theta filtering 804a can, in some implementations, include bilateral filtering of the B data (B Bilateral filtering), for example to smooth an R-Theta filter with an NxN kernel.

[0191] At 806, the receive signal processing chain 500 employs the GPU to perform scan conversion (B Scan Conversion) on the R-Theta filtered B image frame data.

[0192] At 808, the receive signal processing chain 500 employs the GPU to perform image persistence (B Persistence) on the scan converted B image frame data, which is then passed to an image stream mixer 810.

[0193] Along the other one of the two parallel paths, D sigma map blocks 812 of the processor (e.g., GPU) perform sigma mapping on the D ultrasound signals as part of the receive signal processing chain 500. Such can employ multiplestages. The D ultrasound signals are provided as output of the GPU RF demodulation 802. Such can include generating a sigma map, denominated herein as GPU RF Sigma Map 812a. The sigma map represents frame-to-frame changes in the D ultrasound image data. While the term “image” is used herein, the D ultrasound image data may reflect responses from a marker (e.g., tissue marker) and may not reflect responses from or images of anatomical structure.

[0194] D detection blocks 814 of the processor (e.g., GPU) perform RF detection using the sigma map (e.g., RF Sigma Map 812a) as part of the receive signal processing chain 500 Sigma maps represent or otherwise indicate frame-to- frame differences in image data (e.g., detector image data). Again, such can employ multiple stages. Such can include performing RF detection using a GPU, thus is denominated herein as GPU RF Detection 814a.

[0195] D targeting blocks 816 of the processor (e.g., GPU) perform targeting as part of the receive signal processing chain 500 using the output of the D detection blocks 814. Again, such can employ multiple stages. Targeting can include processing pixels or voxels in image data to identify contiguous areas or regions (e.g., blobs, regions of interest) and / or to evaluate or analyze such contiguous areas or regions as possible targets. Such can include performing targeting using a GPU, thus is denominated herein as GPU Targeting 816a.

[0196] D display blocks 818 of the processor (e.g., GPU) perform target display or rendering as part of the receive signal processing chain 500. Again, such can employ multiple stages. Such can include performing target display using a GPU, thus is denominated herein as GPU Target Display 818a.

[0197] At 820, the receive signal processing chain 500 employs the GPU to perform D scan conversion (D Scan Conversion) as part of the receive signal processing chain 500, for example to perform scan conversion of R-theta frame data.

[0198] At 822, the receive signal processing chain 500 employs the GPU to optionally perform D final smoothing (D Final Smoothing) as part of the receive signal processing chain 500. D final smoothing can, for example, include performing a 3x3 boxcar filter on the D image.

[0199] At 824, the receive signal processing chain 500 employs the GPU to perform image persistence (D persistence) on the scan converted and smoothed D image frame data, as part of the receive signal processing chain 500.

[0200] Optionally, at 830, the receive signal processing chain 500 employs the GPU to perform image overlay as part of the receive signal processing chain 500, providing the image overlay information to a image stream mixer 810. The image overlay can overlay labels, tick marks, etc. on the images.

[0201] At 810, the image stream mixer mixes the processed B image data, the processed D image data and optional image overlay image data 830 as part of the receive signal processing chain 500. The processed B image data and processed D image data can be received from the two processing paths, one for processing the B data and the other for processing the D data. Thus, a resulting composite image or overlay image can be generated, the B data representing anatomical structure while the D data represents a response (e.g., artifact) of a marker to the ultrasound emitted by an ultrasound probe.

[0202] At 826, the receive signal processing chain 500 employs the GPU to send the resulting composite image or overlaid image to a display as part of the receive signal processing chain 500.

[0203] At 828, the receive signal processing chain 500 employs the GPU to perform can optional save or store the composite or overlay image 830 to a nontransitory storage medium (e.g., FLASH memory, hard drive, RAM) as part of the receive signal processing chain 500.

[0204] Figure 9 is a flow diagram showing a method 900 of operation of a receive signal processing chain 500 to perform GPU RF demodulation processing on raw RF data received from an ultrasound probe or transducer array, according to at least one illustrated implementation. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204.

[0205] At 902, the receive signal processing chain 500 of the ultrasound system 204 beam forms incoming frames of received RF data (e.g., incoming frame raw sample data). The receive section 210 can, for example, process incoming frame raw sample data received via the ultrasound probe or transducer.

[0206] At 904, the receive signal processing chain 500 of the ultrasound system 204 beam maps, time gain compensates (TGC) and splits the incoming beams to a specified or otherwise defined format. The receive signal processing chain 500 can, for example, map incoming beams to a specified format, apply TGCand then split the received ultrasound signals into B beams, D path 1 beams and D path 2 beams for subsequent processing, where the letter “D” denominates detector.

[0207] The receive signal processing chain 500 of the ultrasound system 204 can, for example, perform RF splitting by separating non-ensemble beams (e.g., beams without the specified pulse pattern) from ensemble beams (e.g., beams with the specified pulse pattern), and resulting in multiple sets of RF data, for example multiple sets of ensemble beam RF data and a set of non-ensemble beam RF data. The output can, for example, include two sets of ensemble beam RF data (denominated as D beams path 1 and D beams path 2) and a set of non-ensemble beam RF data (denominated as B beams). The sets of ensemble beam RF data will predominately represent responses e.g., resonant or beat frequency responses or artifacts) from markers, while the set of non-ensemble beam RF data may predominately represent structure (e.g., reflections from anatomy). While the RF splitter is illustrated as having three legs that provide two sets of ensemble beam RF data and one set of non-ensemble beam RF data, in other implementation the RF splitter can be implemented with a different number of legs. This can advantageously separate B data from a least defined number (e.g., four) of ensemble beams. In some instances, such can be implemented or denominated as RF detector filtering, for example when an RF detector filter is enabled. The receive signal processing chain 500 of the ultrasound system 204 can, for example, apply a FIR bandpass filter in order to separate ensemble beams (e.g., beams with the specified pulse pattern) and non-ensemble beams (beams lacking the specified pulse pattern).

[0208] The output data of the RF splitting is processed by three portions of the signal chain. The three portions of the signal chain comprise generally parallel sets of operations to one another, which are performed on two sets of data that comprise the pulse ensemble responsive data (e.g., resonant or beat frequency responses or artifacts) from markers and the B data (i.e., resulting from B mode ultrasound imaging). The operations of the generally parallel sets of operation are indicated by shared three digit reference numbers followed by the lower case letters “a”, “b” and “c”, respectively, below. Thus, the receive signal processing chain 500 can employ three paths for processing: i) the B beams, ii) the D path 1 beams and iii) the D path 2 beams, in parallel. The B beams can be processed along one path,while the D path 1 beams and D path 2 beams can be processed along a pair of parallel paths, which D paths merge at target detection processing 917 (discussed below).

[0209] At 910a, 910b, 901c, the receive signal processing chain 500 of the ultrasound system 204 performs RF mixing via RF mixers (RF Mixer D, path 1 , RF Mixer D, path 2, and RF Mixer B) to produce RF direct-quadrature (IQ) signals using various different mixing frequencies and coefficients. The RF mixing (RF Mixer D, path 1 , RF Mixer D, path 2) can result in two or more different multiples of a mixing frequency. Such can advantageously address a possible “blinding effect” of the outgoing ultrasound energy, and / or improve the ability to discern which signals correspond to the response by the marker.

[0210] At 912a, 912b, 912c the receive signal processing chain 500 of the ultrasound system 204 optionally performs low pass filtering via low pass filters (D Lowpass Filter 1 , D Lowpass Filter 2, B Lowpass Filter 1 , respectively). Such can, for example, remove negative frequencies from the IQ signals.

[0211] At 914a, 914b, 914c the receive signal processing chain 500 of the ultrasound system 204 demodulates the low pass filtered the RF IQ signals, for example by performing envelope detection (D Envelope Detection 1 , D Envelope Detection 2, B Envelope Detection, respectively). Such can advantageously, remove the carrier signal and reconstruct the signal envelope, for instance converting the IQ signals back to an amplitude representation.

[0212] As also represented in in Figure 9, the signal processing chain 500 of the ultrasound system 204 can further include performing sample decimation on the data of the two D path branches (denominated as DT sample decimation 1 915a, DT Sample Decimation 2 915b, respectively), and on the data of the B path (denominated as B sample decimation, 915c). Such can, for example, lower a sample rate or sample count (e.g., N=4), and potentially guard against aliasing.

[0213] Along the B path, the signal processing chain 500 of the ultrasound system 204 can further include performing B log compression at 916 on the B data, for example to compress the data range to a desired range (e.g., 0 to 255). The results can be provided to a focus mixer at 930.

[0214] As noted above, the D path 1 and D path 2 processing chains can merge at the target detection processing 917. In particular, the output of thedecimation (DT sample decimation 1 915a, DT Sample Decimation 2 915b) is supplied to the target detection processing 917 of the signal processing chain 500.

[0215] The target detection processing 917 can include sigma map processing chains 918 to perform sigma mapping on the decimated results of the D Envelope Detection 1 and D Envelope Detection 1. The sigma mapping maps differences between frames of image data. The sigma map processing chains 918 can include multiple stages. The target detection processing 917 can further include performing region of interest (ROI) detection at 920 using a sigma map generated by the sigma mapping chains 918. The ROI detection 920 can include multiple stages. The ROI detection 920 detects ROIs (e.g., contiguous areas or regions (e.g., blobs, regions of interest)) in the image data. The target detection processing 917 can further include performing target finding and display at 921. The target finding and display 921 evaluates the detected ROIs to identify or select which ones constitute targets. The sigma mapping chains 918, the target or ROI detection 920 and the target finding and display at 921 are explained in more detail with reference to other Figures below, for example Figure 11.

[0216] The output of the target find and display 921 is provided for D scan conversion at 924.

[0217] The output of the target find and display 921 is also provided to focus mixer 930 which performs focus mixing on the output from the target find and display 921 and the output of the B log compression 916, to combine B focus beams and allow the detector (D) beams to cross into stream of B data.

[0218] At 932, a B scan converter of the receive signal processing chain 500 performs B scan conversion on the output from the focus mixer 930, for example to output a scan conversion suitable for visual presentation.

[0219] Figure 10 is a flow diagram showing a method 1000 of operation of a receive signal processing chain 500 to implement GPU RF target sigma map stages, according to at least one illustrated implementation. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204.

[0220] Along one path, the receive signal processing chain 500 of the ultrasound system 204 performs DT sample decimation 1 at 1002, for example to reduce the sample rate or sample count (e.g., N=4).

[0221] At 1004, the receive signal processing chain 500 of the ultrasound system 204 performs ensemble focus blending (ensemble focus blend 1) on the output of the DT sample decimation 1 , to blend the transmit (TX) focus patterns.

[0222] At 1006, the receive signal processing chain 500 of the ultrasound system 204 determines or calculates a sum of differences for the output of the ensemble focus blending. Such can, for example, reduce two beams in the ensemble to one beam by taking the absolute difference of each position in the beam. This operation helps to draw out temporal differences in the RF data.

[0223] At 1008, the receive signal processing chain 500 of the ultrasound system 204 determines lateral standard deviations based on the sum of the differences (also referred to as an across beam standard deviation), for example calculating an across-beam standard deviation. For example, the receive section 210 calculates the standard deviation of the number of beams (e.g., 3 beams) surrounding a target or “current” beam. A window size (e.g., 3) is set by the environment variable VPM_LATERAL_WINDOW. This operation helps to draw out spatial differences in the lateral plane.

[0224] At 1010, the receive signal processing chain 500 of the ultrasound system 204 multiplies, cancels and compresses (e.g., log compresses) the data. In some implementations, a lateral canceler can, for example, subtract a mean of the other beams from each ensemble sample. For instance, the lateral canceler subtracts the mean of surrounding beams (e.g., the 4 surrounding beams) from an active or “current” beam ( / .e., the beam currently being processed). The lateral canceler has a window size (e.g., window size of 5) set by an environment variable. The ultrasound system optionally employs or applies a frame cancel, for example performing frame to frame cancellation and smoothing. Alternatively, the frame cancellation can be disabled so that the data passes through this operation unaltered.

[0225] At 1012, the receive signal processing chain 500 of the ultrasound system 204 creates a force target (Force Target 1) in the output, resulting in a target sigma source non-mased). The resulting target sigma source is supplied to a sigma detector output 1014 which serves as a source for target sigma data, discussed below. The resulting target sigma source is also supplied to generate a brightnessmask 1016, which can be used as described below. The generation of the brightness mask 1016 can reduce incoming sigma at high brightness levels.

[0226] Along another path, the receive signal processing chain 500 of the ultrasound system 204 performs DT sample decimation 2 at 1018, for example to reduce the sample rate or sample count (e.g., N=4).

[0227] At 1020, the receive signal processing chain 500 of the ultrasound system 204 performs ensemble focus blending (ensemble focus blend 2) on the output of the DT sample decimation 2, for example to blend transmit (TX) focus patterns. The output of the ensemble focus blend 2 is processed by two processing chains, namely a brightness processing chain 1022 and an amplitude segmentation chain 1024. The brightness processing chain 1022 will be discussed first, then the amplitude segmentation chain 1024 will be discussed.

[0228] As part of the brightness processing chain 1022, the receive signal processing chain 500 of the ultrasound system 204 determines an ensemble average at 1026, for example outputting the average of the DT ensembles. The receive signal processing chain 500 then performs a logarithmic compression (DT LOGCOMPRESS) on the data at 1026. The logarithmic compression can advantageously map the data to a specified range (e.g., the range 0 - 235 where 235 is equal to 160 dB). In this example, a step size is .681 dB per step. The log compression (DT LOGCOMPRESS) is used for the aforesaid generation of the brightness mask 1016.

[0229] The brightness processing chain 1022 continues with the receive signal processing chain 500 determining beam histograms (DT Beam Histograms) at 1028, for example generating a per beam histogram. The beam histogram (e.g., average, peak, maximum) can be employed to inform a dynamic threshold / flooded sector assessment where implemented. The receive signal processing chain 500 then determines frame histograms (DT Frame Histograms) at 1030. The frame histogram (e.g., average, peak, maximum) can be employed to inform a dynamic threshold I flooded sector assessment where implemented. The receive signal processing chain 500 then estimates densities (DT Density Estimator) at 1032, for example generating frame statistics and density estimated output. Finally as part of the brightness processing chain 1022, the receive signal processing chain 500 provides the histogram output 1038, for example as a source for histogram displays.

[0230] As part of the amplitude segmentation chain 1024, the receive signal processing chain 500 of the ultrasound system 204, the receive signal processing chain 500 of the ultrasound system 204 determines a sums of difference at 1040. The receive signal processing chain 500 then performs de-interlacing at 1042, for example outputting a blending of adjacent DT beams. The receive signal processing chain 500 then performs a log compression (AS LOGCOMPRESS) at 1044, resulting in a segmentation mask source. Finally as part of the amplitude segmentation processing chain 1024, the receive signal processing chain 500 provides amplitude segmentation output 1046 (see Figure 12 for generation of provides amplitude segmentation output 1046), which is a source for amplitude segmentation (discussed below).

[0231] Figure 11 is a flow diagram showing a method 1100 of operation of a receive signal processing chain 500 to perform find or detect regions of interest (ROIs), according to at least one illustrated implementation. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204.

[0232] The receive signal processing chain 500 of the ultrasound system 204 receives an amplitude segmentation (AS) sigma source (AS Sigma Source) 1102, which is the amplitude segmentation processing chain sigma data.

[0233] The receive signal processing chain 500 of the ultrasound system 204 executes an amplitude segmentation processing chain 1104. Such can include executing an amplitude segmentation sequence 1106, which may itself employ multiple stages.

[0234] In some implementations, the receive signal processing chain 500 optionally performs a sigma threshold cull to filter out any out-of-bounds regions. The receive signal processing chain 500 can, for example, remove regions based on a sigma threshold. For instance, the receive signal processing chain 500 checks positions in the distances data where the left, right, up, and down distances are zero, and sets a culling code accordingly. The receive signal processing chain 500 then checks positions in the sigma data for values less than the target minimum sigma threshold, and sets a culling code accordingly. The culling code may be a Boolean flag or value that indicates a binary state of either cull or do not cull.

[0235] In some implementations, the receive signal processing chain 500 optionally performs a regions cull. The regions cull can remove regions based on sigma content and B content, being feed from a B processing chain and from a B log compress. For example, the receive signal processing chain 500 checks positions in the distances data for connected widths that are too wide, and sets a culling code accordingly. Also for example, the receive signal processing chain 500 checks positions in the B data for values over the B threshold, and sets a culling code accordingly.

[0236] In some implementations, the receive signal processing chain 500 optionally performs an orphans cull. The orphans cull can remove blob orphans created in the previous stage. For example, the receive signal processing chain 500 searches a region of interest (ROI) associated with the currently active position, for positions that were previously culled for being too wide, and sets a culling code accordingly if any are found. The ROI is defined by the left, right, up, and down distances for the active position. The receive signal processing chain 500 searches a smaller ROI and tracks the number of positions culled for being under the sigma threshold. The smaller ROI is defined by a sub-range of left, right, up, and down distances of the currently active position. A culling code is set if a ratio of culled to valid positions exceeds the threshold.

[0237] In some implementations, the receive signal processing chain 500 optionally refines distances calculations, for example recalculating the distances without the culled values. For example, the receive section 210 can step out from the active position in the left, right, up, and down directions, and count the number of steps in each direction until a culled value is reached. These counts are saved as the new left, right, up, and down distances for the active position. The receive signal processing chain 500 then assesses culled regions, for example filtering out out-of- bounds regions. The receive signal processing chain 500 can, for example, check a width (left and right distance sum) and a height (up and down distance sum) of the active position against minimum size requirements. The minimum size requirement can, for instance, be defined by a set of registers, denominated herein as DT Target Min Width and DT Target Min Height. If the minimum size requirement is not met then the receive signal processing chain 500 sets a culling code accordingly. The receive signal processing chain 500 can then optionally refine distances again, forexample again recalculating distances without the culled values. The receive signal processing chain 500 can, for example, steps out from the active position in the left, right, up, and down directions, and counts the number of steps in each direction until a culled value is reached. These counts are saved as the new left, right, up, and down distances for the active position.

[0238] In some implementations, the receive signal processing chain 500 optionally performs a first pass of centroid reduction. The receive signal processing chain 500 can, for example, reduce distances set to a highest match within a specified range. For example, the receive signal processing chain 500 can calculate a width ratio, a height ratio and an area I distance product for each valid centroid. The receive signal processing chain 500 can recursively compare the values in pairs until reduced to a single best fit. The receive signal processing chain 500 of the ultrasound system 204 then optionally performs a second pass of centroid reduction. The receive signal processing chain 500 can, for example, reduce the set again to a highest match within a specified range.

[0239] The receive signal processing chain 500 of the ultrasound system 204 generates or accesses a connection map 1108. The connection map 1108 can represent or indicate pixels or voxels which can form contiguous areas or regions (e.g., blobs, regions of interest), for example determining a left, right, up, and down (LRUD) connection status of each sample. For example, the receive signal processing chain 500 calculates horizontal and vertical connection information of each cell. The connection map establishes the left, right, up, and down connections ( / .e., nearest neighbors in row and in column) for the active sample.

[0240] At 1110, the receive signal processing chain 500 of the ultrasound system 204 can determine (e.g., calculate) distances between contiguous areas or regions (e.g., blobs, regions of interest) from the connection map 1108. For example, the receive signal processing chain 500 of the ultrasound system 204 determines or calculates distances, for instance LRUD distances to the blob edge of each cell. For example, the receive section 210 calculates the left, right, up, and down distances ( / .e., distances in row and distances in column) from the active sample to the non-connected edge.

[0241] The receive signal processing chain 500 of the ultrasound system 204 can execute a number (e.g., three) of region of interest (ROI) finder sequences,denominated herein as ROI Finder Sequence 1 1112a, ROI Finder Sequence 2 1112b and ROI Finder Sequence 3 1112c. In particular, the ROI finder sequences can rely on the output of the amplitude segmentation sequence 1106, the connection map 1108 and the determined distances (DT Distances) 1110, Subsequent ones of the region of interest finder sequences can rely on the output of previous ones of the region of interest finder sequences. For instance, a second one of the region of interest finder sequences (ROI Finder Sequence 2 1112b) can rely on the output of a first one of the region of interest finder sequences (ROI Finder Sequence 1 1112a), and a third one of the region of interest finder sequences (ROI Finder Sequence 3 1112c) can rely on the output of a second one of the region of interest finder sequences (ROI Finder Sequence 2 1112b), as illustrated. In some implementations, the ROI finder (aka blob finder) can find up to four blobs (continuous pixels of voxels indicated as being occupied) in the segmentation mask, sorted by size of the blob.

[0242] Each of the region of interest finder sequences (ROI Finder Sequence 1 1112a, ROI Finder Sequence 2 1112b, ROI Finder Sequence 3 1112c) can including finding a respective target (Find T arget 1 1114a, Find T arget 2 1114b, Find Target 3 1114c), each of which can employ multiple stages to find the respect targets.

[0243] Figure 12 is a flow diagram showing a method 1200 of operation of a receive signal processing chain 500 to implement a GPU amplitude segmentation processing chain to generate amplitude segmentation output (1046 Figure 10), according to at least one illustrated implementation. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204.

[0244] At 1202, the receive signal processing chain 500 of the ultrasound system 204 starts with amplitude segmentation sigma data, which is the sigma source for the amplitude segmentation.

[0245] At 1204, the receive signal processing chain 500 of the ultrasound system 204 generates amplitude segmentation (AS) beam histograms (AS BE AM HISTOGRAMS). Such can generate a per beam histogram of the AS sigma data (e.g., size 256).

[0246] At 1206, the receive signal processing chain 500 of the ultrasound system 204 generates amplitude segmentation (AS) frame histograms (AS FRAMEHISTOGRAMS). Such can generate a total frame histogram of AS sigma data (e.g., size 356).

[0247] At 1208, the receive signal processing chain 500 of the ultrasound system 204 determines or otherwise generates frame histogram statistics (FAME HISTO STATS), for example calculating summary statistics on the total frame histogram.

[0248] At 1210, the receive signal processing chain 500 of the ultrasound system 204 determines or otherwise generates K-Means beam histograms (KMEANS BEAMHISTOGRAMS), for example determining a per beam histogram of AS sigma data scaled to a minimum / maximum (e.g., 4096 bins).

[0249] At 1212, the receive signal processing chain 500 of the ultrasound system 204 determines or otherwise generates K-Means frame histograms (KMEANS FRAMEHISTOGRAMS), for example determining total frame histograms of AS sigma data scaled to a minimum / maximum (e.g., 4096 bins).

[0250] At 1214, the receive signal processing chain 500 of the ultrasound system 204 performs K-Means preparation (K-Means Prep), preparing the data for segmentation passes and determining seed segments.

[0251] At 1216, the receive signal processing chain 500 of the ultrasound system 204 performs amplitude segmentation, for example running a K-Means segmentation on the data.

[0252] At 1218, the receive signal processing chain 500 of the ultrasound system 204 determines or otherwise generates a segmentation mask 1218, for example based on the amplitude segmentation sigma 1202 and amplitude segmentation 1216. Such can, for example, create a marked mask of the upper two (2) segments.

[0253] At 1220, the receive signal processing chain 500 of the ultrasound system 204 performs smoothing on the segmentation mask. Such can, fore example, include generating a smoothing mask, filling holes and reducing tendrils.

[0254] At 1222, the receive signal processing chain 500 of the ultrasound system 204 forces a target in the mask, for example when enabled.

[0255] The receive signal processing chain 500 of the ultrasound system 204 then determines, generates or otherwise provides amplitude segmentation output (the segmented amplitude segmentation) 1224.

[0256] Figure 13 shows a GPU idle detection method implemented between a single board computer (SBC) 1300 and a GPU (SBC / GPU Domain) 1302, used to execute at least part of a receive signal processing chain 500, according to at least one illustrated implementation. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204, for instance via one or ore GPUs and one or more CPUs.

[0257] The SBC 1300 includes a GPU (SBC / GPU Domain) 1302, that executes a set of processor-executable instructions or logic. The SBC / GPU Domain) 1302 can, for example, perform idle detection at 1304, for instance calculating the frame differential sum of the background ensemble and using consecutive number of low differential frames to determine the states (e.g., idle, not idle). The SBC / GPU Domain 1302 can also, for example, apply an adaptive threshold to the data at 1306. For instance, such can zero out the sigma data if the idle status is set or otherwise set all values less than the sigma threshold to be equal to zero (0). The sigma threshold can have been set by a harmonic sigma threshold register. As an example, a sigma threshold can be 75, which equates to 51 .08 dB. The sigma threshold sets the basis for establishing spatial connections. The value can intentionally be set to be lower than an expected target minimum to ensure that a broader size of objects are measured including objects that may have a sub-region that meets the target minimum.

[0258] The SBC 1300 includes a CPU (SBC / CPU Domain) 1308, that executes a set of processor-executable instructions or logic. The SBC / CPU Domain) 1302 can, for example, monitor a scan state at 1310, for example responding to the idle status from the GPU and setting a total frame clocks register to control the scan rate.

[0259] Figure 14 is a flow diagram showing a method 1400 of performing a single region of interest (ROI) finder sequence as part of a receive signal processing chain 500, according to at least one illustrated implementation. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204.

[0260] The receive signal processing chain 500 of the ultrasound system 204 generates or accesses a connection map 1402. The connection map 1108 can represent or indicate pixels or voxels which can form contiguous areas or regions (e.g., blobs, regions of interest) and can determine a left, right, up and down (LRUD) connection status of each sample.

[0261] At 1404, the receive signal processing chain 500 of the ultrasound system 204 determines (e.g., calculates) distances (DT DISTANCES) from each sample from the connection map 1108, for example determining left, right, up and down (LRUD) distances between contiguous areas or regions (e.g., blobs, regions of interest).

[0262] At 1406, the receive signal processing chain 500 of the ultrasound system 204 determines centroids (DT_CENTROIDS) for each sample (e.g., for each contiguous areas or regions (e.g., blobs, regions of interest)) of the connection map 1108. Such can include finding the max centroid within specified limits.

[0263] The receive signal processing chain 500 of the ultrasound system 204 then marks a number (e.g., three) of targets in the connection map 1108, for example marking a target A (Mark Target A) at 1408a, marking a target B (Mark Target B) at 1408b, and marking a target C (Mark Target C) at 1408c. The receive signal processing chain 500 can employ the connection map 1402, the determined distances (DT Distances) 1404 and the determined centroids (DT_Centroid) 1406 in marking the targets. Such can advantageously expand a centroid of a target around comers.

[0264] The receive signal processing chain 500 of the ultrasound system 204 generates or receives an incoming target map 1410. The incoming target map 1410 is a map that identifies other targets where there is more than one target.

[0265] The receive signal processing chain 500 of the ultrasound system 204 generates or receives amplitude segmentation output 1412 that constitutes the segmented amplitude segmentation data previously described (see amplitude segmentation output 1046 (Figure 10) and the method of generating such (Figure 12)).

[0266] At 1414, the receive signal processing chain 500 of the ultrasound system 204 applies a mask relying on the incoming target map 1410, amplitudesegmentation output 1412, and the mark target(s). Applying the mask can isolate a target and supply a distance map with the target removed.

[0267] The receive signal processing chain 500 of the ultrasound system 204 receives or generates incoming target bounds (INCOMING TARGET BOUNDS) 1416, which specifies the bounds of other targets than the identified target where there is more than on target in the image data.

[0268] The receive signal processing chain 500 of the ultrasound system 204 determines or otherwise generates target bounds (TARGET BOUNDS) 1418 based on output of applying the mask 1414 and based on the incoming target bounds 1416, for example finding a bound box for a target.

[0269] The receive signal processing chain 500 of the ultrasound system 204 generates or provides a target sigma map (TARGET SIGMAMAP) 1420 based on output of applying the mask 1414. The target sigma map 1420 is a sigma map of just the identified target.

[0270] The receive signal processing chain 500 of the ultrasound system 204 generates or provides non-target distances (NON TARGET DISTANCES) 1422 based on output of applying the mask 1414. The non-target distances 1422 can take the form of a distance map of non-identified targets.

[0271] The receive signal processing chain 500 of the ultrasound system 204 generates or provides a merged target identification map (MEREGED TARGET ID MAP) 1424 based on output of applying the mask 1414. The merged target identification map (MEREGED TARGET ID MAP) 1424 can take the form of a marked target identification map merged with prior target identification maps.

[0272] Figure 15 is a flow diagram showing a method 1500 of target analysis as part of operation of a receive signal processing chain 500 to find, analyze and track targets, according to at least one illustrated implementation. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204.

[0273] The receive signal processing chain 500 of the ultrasound system 204 finds a number (e.g., three) targets in a connection map. The receive signal processing chain 500 can for example, find a first target (FIND TARGET 1) 1502a, find a second target (FIND TARGET 2) 1502b, and find a third target (FIND TARGET 3) 1502c. Resulting information, for example TARGET A ISOLATED SIGMA data,TARGET B ISOLATED SIGMA data and TARGET C ISOLATED SIGMA data, can be output and provided to a preparation target analyzer (PREP TARGET ANALYZER) 1504.

[0274] The preparation target analyzer (PREP TARGET ANALYZER) 1504 combines the target data in preparation for analysis, for example combining the identified targets (e.g., first target, second target, third target).

[0275] Output from the preparation target analyzer (PREP TARGET ANALYZER) 1504 is supplied to a target analyzer 1506, along with output (e.g., CENTROID 1 , CENTROID 2, CENTROID 3, COMBINED BOUNDS) from the first, second and third target finds (FIND TARGET 1 1502a, FIND TARGET 2 1502b, FIND TARGET 3 1502c). The target analyzer 1506 also receives a brightness mask output 1508 (brightness mask see 1016 of Figure 10). The target analyzer (TARGET ANALYZER) 1506 does the substantive processing (heavy lifting) of deciding if a blob or ROI is a marker target that should be tracked. The target analyzer (TARGET ANALYZER) 1506 analyzes the targets, and ranks targets based on defined target characterizing criteria. Such, for example, includes: metrics, for instance: frame metrics including line density and noise floor; region of interest (ROI) metrics including average, maximum, variance, area, and / or width to height or aspect ratio; brightness map (average), and region of interest relational metrics including relative positioning of ROIs. The noise floor metric is used to disable detection output on frames that are saturated with high sigma. The line density metric is used to selectively exclude blobs / ROIs that are part of a larger reflective object, like the tissue back wall. The ranking is essentially an assessment of how much each response “looks like” a response from a marker, which is at least in part based on a marker’s physical geometry and expected response pattern (e.g., artifacts) of ultrasound reflective elements of the marker.

[0276] The target analyzer 1506 also applies weights. For example, to apply weights the target analyzer 1506 applies a form of high pass, low pass, or band pass to the ROI Metrics and applies linear scaling to the data in the transition band in the range of 0 to 1 . It then applies a weight value to each scaled metric.Sigma Map• Average High PassLow Cutoff: 26.56High Pass: 58.35Scaled Weight: 0.4• MaxHigh passLow Cutoff: 41.24High Pass: 90.08Scaled weight: 0.05• VarianceHigh PassLow Cutoff: 50.61High Pas 355.85Scaled Weight: 0.25• Width / Height RatioBand PassLow Cutoff: 0Full Pass: 0.38High Cutoff: 1.1Scaled Weight: 0.3• AreaBand PassLow Cutoff: 0Full Pass: 700High Cutoff: 1400Scaled Weight: 0.2Brightness Map• AverageLow Pass: 50.0High Cutoff: 60.0Scaled Weight: 0.2

[0277] At 1510, the receive signal processing chain 500 of the ultrasound system 204 tracks multiple targets (e.g., blobs, regions of interest) from frame-to-frame, for example receiving current tracking information from the target analyzer 1506 and providing prior target tracking information to the target analyzer 1506.

[0278] For example, the receive signal processing chain 500 can optionally perform centroid tracking, for example generating a centroid tracking table or other data structure. The receive signal processing chain 500 can take sigma and distance matrices along with the best fit centroid and track the blob over time (e.g., frame-to-frame). The receive signal processing chain 500 can maintain a state machine that updates the target tracking attributes across various states, for instance two primary states: seeking and tracking. Within each primary state there can be sub-states that, for example control responsiveness, persistence, and confidence.

[0279] The receive signal processing chain 500 can, for example, characterize an ROI or blob. This stage tests the scaled and weighted metrics against a series of gates that qualify a blob as a valid marker target and produces a fitness metric for blobs / ROIs that pass.

[0280] Qualification can include two gates, denominated as Gate 1 and Gate 2. In Gate 1 , if not tracking, it is determined whether the Average, Max, Variance, Width / Height Ratio, and Brightness Average weighted metrics are nonzero. In Gate 1 , if tracking, it is determined whether the Average, Max, Variance, and Width / Height Ratio weighted metrics are non-zero. In Gate 2, it is determined whether the sum of the weighted Average, Max, Variance, Width / Height Ratio, and prior fitness >= 0.6.

[0281] For fitness, for all ROIs or blobs that passed qualification, the weighted Average, Max, Variance, Width / Height Ratio, Area, Brightness Average, and prior fitness are summed to get a final fitness metric for each ROI or blob.

[0282] The receive signal processing chain 500 can then rank the ROI or blob. For example, the receive signal processing chain 500 ranks the ROIs or blobs by fitness in descending order. The receive signal processing chain 500 checks whether the top 2 ranked blobs are horizontally aligned (one above the other) and similar in strength. If so, the ranks are swapped so the top positioned ROI or blob is the higher ranked. The higher ranked ROI or blob of the ranked ROIs or blobs is the primary target.

[0283] Figure 16 is a flow diagram showing a method 1600 of operation of a receive signal processing chain 500 to find, analyze, track and display targets, according to at least one illustrated implementation. One of skill in the art will note some overlap between the method 1600 and the method 1500, although the method 1600 notably provides additional details on tracking multiple targets. The receive signal processing chain 500 can, for example, be implemented by the receive section 210 (Figure 2) of the ultrasound system 204.

[0284] As previously discussed above, the receive signal processing chain 500 of the ultrasound system 204 finds a number (e.g., three) of targets in a connection map, for example, finding a first target (FIND TARGET 1) 1602a, finding a second target (FIND TARGET 2) 1602b, and finding a third target (FIND TARGET 3) 1602c. Resulting information, for example TARGET A ISOLATED SIGMA data, TARGET B ISOLATED SIGMA data and TARGET C ISOLATED SIGMA data, can be output and provided to a preparation target analyzer (PREP TARGET ANALYZER) 1604. Output from the preparation target analyzer (PREP TARGET ANALYZER) 1604 is supplied to a target analyzer 1606, optionally along with other output (e.g., CENTROID 1 , CENTROID 2, CENTROID 3, COMBINED BOUNDS) from the first, second and third target finds (FIND TARGET 1 1502a, FIND TARGET 2 1502b, FIND TARGET 3 1502c). The target analyzer 1506 also receives a brightness mask output 1508 (brightness mask see 1016 of Figure 10). The target analyzer (TARGET ANALYZER) 1606 analyzes the targets, and can even rank targets.

[0285] As also previously discussed above, the receive signal processing chain 500 includes a multiple target tracker 1610 tracks multiple targets (e.g., blobs, regions of interest) from frame-to-frame in conjunction with the target analyzer 1506.

[0286] The target analyzer 1506 provides output to a number (e.g., two) of target selectors (TARGET SELECTOR 1 1608a, TARGET SELECTOR 2 1608b), which selects targets based on the analysis (e.g., based on rank, which itself can be based on various target characterizing criteria or metrics, for instance: frame metrics including line density and noise floor; region of interest metrics including average, maximum, variance, width to height or aspect ratio and / or area; region of interest relational metrics including relative positioning of ROIs). The target selectors (TARGET SELECTOR 1 1608a, TARGET SELECTOR 2 1608b can select arespective target and can provide sigma (Target 1 output sigma, Target 2 output sigma) and other information about the selected target.

[0287] As previously explained, the multiple target tracker 1610 exchanges information with the target analyzer 1606, for example information specifying a current state or current tracking information and information that specifies a prior tracking state. The multiple target tracker 1610, for example receives current tracking information from the target analyzer 1506 and provides prior target tracking information to the target analyzer 1506.

[0288] The multiple target tracker 1610 also receives histograms from a sigma estimator (DT ESTIMATOR) 1612. The sigma estimator (DT ESTIMATOR) 1612 can estimate density (density estimator) and statistics from a main sigma processing chain.

[0289] The multiple target tracker 1610 also receives left, right up, and down (LRUD) distances 1614, which can represent raw distances in the segmentation map.

[0290] Output from the multiple target tracker 1610 is provided to a multitarget merge 1622. The multi-target merge 1622 also receives output from the target selector TARGET SELECTOR 2, and from the target selector TARGET SELECTOR 1 via a bilateral filter 1616. The multi-target merge 1622 further receives output from a sigma chain process (SIMA CHAIN A) 1618, as well as a raw brightness mask 1620. The multi-target merge 1622 determines the output to display and causes the display of the determined output. The output (DETECTOR CHAIN OUTPUT) from the multi-target merge 1622 is provided as detector processing chain output 1624. For example, the receive signal processing chain 500 can optionally implement or apply a centroid merge. The centroid merge can be used to format and / or routes the desired data for display. In the standard operating mode the centroid merge can route the isolated best fit blob with targeting accents (e.g., Crosshairs, shadows), but can also route the distances data, culling codes, test patterns, etc. The receive section 210 can update the centroid tracking table accordingly.

[0291] As discussed above, there may be two primary states: seeking and tracking.

[0292] While in the seeking state, the receive signal processing chain 500 attempts to detect the same target multiple times, for example attempting to detectthe same target in three (3) frames in a row. Such can provide an enhanced level of confidence over a single detection. While three (3) frames in a row is provided as an example, a greater or lesser number of frames can be employed, although it is believed that three (3) frames provides a good balance between speed and accuracy. It will qualify as a consecutive detection if the centroid of each subsequent detect is within the target reach of the target in the previous frame. A consecutive detect counter is incremented on each successful detection. In response to the specified number (e.g., three (3)) of detections of the same target occurring, the initial tracking attributes are set and the state machine is transitioned to the tracking state. The consecutive detect counter is reset immediately upon a frame with no detection of the target.

[0293] While in the tracking state, the receive signal processing chain 500 determines whether a target is within a target tracking region of interest (ROI).

[0294] If the target is within the target tracking ROI, the receive signal processing chain 500 updates the tracking attributes, and the state of the state machine is maintained as tracking.

[0295] If, on the other hand, the target is not within the target tracking ROI, the receive signal processing chain 500 optionally executes the following algorithm.

[0296] The receive signal processing chain 500 increments a set of persistence counters (denominated as ROI persistence counter; and Precise persistence counter).

[0297] The receive signal processing chain 500 determines whether the target is a confident (e.g., level 2) detection. If so, the receive signal processing chain 500 updates the tracking attributes for the new target, and the state of the state machine is maintained as tracking.

[0298] The receive signal processing chain 500 then enters an outer loop while the ROI persistence counter is less than or equal to 0.

[0299] The receive signal processing chain 500 then enters an inner loop while the precise persistence counter is less than or equal to 0.

[0300] The receive signal processing chain 500 then clears the tracking attributes for the current target (Clear TARGET_CURRENT Tracking Attributes), and the state of the state machine is transitioned to a tracking lost state.

[0301] Once the ROI persistence counter is greater than zero (0), the receive signal processing chain 500 exits the outer loop. The receive signal processing chain 500 then clears the tracking attributes, and the state of the state machined is changed to seeking.

[0302] The tracking attributes can, for example, include: target confidence and target tracking ROI. The target confidence is determined within the Centroid Tracking by accumulating counters for all of the positions with high sigma, for example greater than 125.957 dB, and non-zero sigma within the target reach of the target. If the ratio of high sigma to non-zero sigma is greater than a threshold value (e.g., 25%) then the confidence is increased, for instance from 1 to 2. The Target ROI is the full beam width of the sector and a top and bottom that is the target’s precise top and bottom plus a margin.

[0303] Figures 17A and 17B show transmit (TX) and receive (RX) signal path components of an ultrasound system 1700 that implements transmit and receive signal processing chains, according to at least one illustrated implementation. Such can be implemented with a variety of different types of processors (e.g., microprocessors with one or more central processing units (CPUs), graphics processing units (GPUs) and / or digital signal processors (DSPs); dedicated CPUs, GPUs and / or DSPs; field programmable gate arrays (FPGAs)); and / or microcontrollers. Such can also be implemented with analog circuitry.

[0304] The ultrasound system 1700 includes a field programmable gate array (FPGA) domain 1702. The ultrasound system 1700 includes single board computer (SBC) which itself includes a CPU (SBC / CPU Domain) 1704 and a GPU (SBC / GPU Domain) 1706. The ultrasound system 1700 also includes a display 1708, a transducer interface 1710, and an analog domain 1712 ( / .e., ultrasound analog circuitry).

[0305] The field programmable gate array (FPGA) domain 1702 executes programmed logic that was programmed into the FPGA. The CPU (SBC / CPU Domain) 1704 executes a respective set of processor-executable instructions which can be stored on nontransitory computer- or processor-readable media (e.g., ROM, RAM, FLASH memory, magnetic disk drives, optical disk drives). The GPU (SBC / GPU Domain) 1706 executes a respective set of processor-executableinstructions which can be stored on nontransitory computer- or processor-readable media (e.g., ROM, RAM, FLASH memory, magnetic disk drives, optical disk drives).

[0306] The FPGA domain 1702 includes or implements a receive beamformer (RX BEAM FORMER) 1714, which beam forms ultrasound energy received by an ultrasound transducer or probe, for example focusing raw beam data to a single receive beam. The receive beamformer (RX BEAM FORMER) 1714 can buffer beams and transmit or dispatch the buffered beams to the CPU (SBC / CPU Domain) 1704, for example via a Universal Serial Bus (UBS) communications interface (USB DISPATCH) 1716. The FPGA domain 1702 can also include or implement a scan controller 1718. The scan controller 1718 is communicatively coupled to the transducer interface 1710 and operable to control ultrasound scanning, for example configuring per beam transmission and receipt of ultrasound. The scan controller 1718 is also communicatively coupled to the analog domain 1712 ( / .e., ultrasound analog circuitry).

[0307] The CPU (SBC / CPU Domain) 1704 includes a USB receive interface (USB RECEIVE ) 1720 to receive the beams from the communications interface (USB DISPATCH) 1716.

[0308] The CPU (SBC / CPU Domain) 1704 includes a frame assembly 1722, operable to receive beams, beam by beam, and assemble or otherwise combine the received beams into frames. The CPU (SBC / CPU Domain) 1704 includes a communications interface (FRAME DISPATCH) 1724 operable to transfer (e.g., load) frames to the GPU (SBC / GPU Domain) 1706.

[0309] The GPU (SBC / GPU Domain) 1706 receives the frames from the CPU (SBC / CPU Domain) 1704. The GPU (SBC / GPU Domain) 1706 includes a GPU compute process 1726 and a GPU image process 1728. The GPU compute process 1726 performs RF processing (e.g., demodulation; filtering in an R Theta space). The GPU image process 1728 renders and / or performs image processing of the image data readying such for display.

[0310] The display 1708 can, for example, take the form a display driver 1730 that sends or otherwise renders images to a display, screen or monitor.

[0311] The transducer interface 1710 includes an ultrasound transducer or probe 1732 (e.g., ultrasound transducer crystal array) which is operable to emit ultrasound energy or signals and to detect returned ultrasound energy or signals.The transducer interface 1710 includes a multiplexer (Tl MUX) 1734 communicatively coupled to the scan controller 1718 and communicatively coupled with the ultrasound transducer or probe 1732 (e.g., 64 Channels, analog transmit / receive) to exchange signals therewith. The multiplexer (Tl MUX) 1734 can, for example, multiplex 128 channels to 64 channels.

[0312] The analog domain 1712 typically comprises analog circuitry of the ultrasound system. For example, the analog domain 1712 can include pulsurs 1736 operable to drive the ultrasound transducers (e.g., crystals) to emit ultrasound energy. The pulsurs 1736 can, for example, perform 64 channel transmit delay and waveform generation, and switch the ultrasound transducer or probe 1732 between transmit and receive. Also for example, the analog domain 1712 can include an analog front end (AFE-ANALOG FRONT END) 1738, communicatively coupled with the scan controller 1718 to exchange information therewith, and communicatively coupled to the pulsurs 1736 to receive information therefrom. Such can, for example, perform TGC and / or ADC conversion.

[0313] The foregoing detailed description has set forth various implementations of the devices and / or processes via the use of block diagrams, schematics, and examples. Insofar as such block diagrams, schematics, and examples contain one or more functions and / or operations, it will be understood by those skilled in the art that each function and / or operation within such block diagrams, flowcharts, or examples can be implemented, individually and / or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. In one implementation, the present subject matter may be implemented via Application Specific Integrated Circuits (ASICs). However, those skilled in the art will recognize that the implementations disclosed herein, in whole or in part, can be equivalently implemented in standard integrated circuits, as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs running on one or more controllers (e.g., microcontrollers) as one or more programs running on one or more processors (e.g., microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and / or writing the code for the software and or firmware would be well within the skill of one of ordinary skill in the art in light of this disclosure.

[0314] Those of skill in the art will recognize that many of the methods or algorithms set out herein may employ additional acts, may omit some acts, and / or may execute acts in a different order than specified.

[0315] In addition, those skilled in the art will appreciate that the mechanisms taught herein are capable of being distributed as a program product in a variety of forms, and that an illustrative implementation applies equally regardless of the particular type of signal bearing media used to actually carry out the distribution. Examples of signal bearing media include, but are not limited to, the following: recordable type media such as floppy disks, hard disk drives, CD ROMs, digital tape, and computer memory.

[0316] The various implementations described above can be combined to provide further implementations. U.S. patent application 60 / 955678; U.S. patent application 61 / 034468; U.S. patent application 12 / 673224 (now U.S. Patent 8440229); International patent application PCT / US2008 / 072972; U.S. patent application 13 / 866940 (now U.S. Patent 9220685); U.S. patent application 15 / 722436; U.S. patent application 61 / 707794; International patent application PCT / US2013 / 062436; U.S. patent application 15 / 706446; U.S. patent application 62 / 135653; U.S. patent application 15 / 559764; International patent application PCT / US2016 / 23492; U.S. patent application 62 / 483,274; U.S. patent application 62 / 645,677; U.S. patent application 15 / 946,479; International patent application PCT / US2018 / 26291 ; U.S. patent application 62 / 892,952; U.S. patent application 63 / 441 ,558; U.S. patent application 63 / 441 ,558; and U.S. patent application 63 / 525,280; U.S. patent application 63 / 625,167, are each incorporated herein by reference in their entirety. Aspects of the implementations can be modified, if necessary, to employ systems, circuits and concepts of the various patents, applications and publications to provide yet further implementations.

[0317] These and other changes can be made to the implementations in light of the above-detailed description. In general, in the following claims, the terms used should not be construed to limit the claims to the specific implementations disclosed in the specification and the claims, but should be construed to include all possible implementations along with the full scope of equivalents to which such claims are entitled. Accordingly, the claims are not limited by the disclosure.

Claims

CLAIMS1 . A method of operation in an ultrasound system having a transmit section and a receive section to detect at least a presence or an absence of a response from a tissue marker, the method comprising: generating a set of drive signals via the transmit section of the ultrasound system; supplying the set of drive signals to an ultrasound probe having at least one ultrasound transducer to cause the at least one ultrasound transducer to emit ultrasound energy as ensembles of pulses, a respective ensemble of pulses emitted along a respective one of each of a plurality of beams and at a number of focal depths; and processing a series of return signals via a return signal processing chain of a receive section of the ultrasound system, the series of return signals representative of ultrasound energy detected by the ultrasound probe, wherein processing the series of return signals via the return signal processing chain includes: generating a brightness map based at least in part on the series of return signals, the brightness map indicative of intensity or loudness (dB) levels of the series of return signals in a set of image data; generating a sigma map based at least in part on the series of return signals, the sigma map indicative of changes between frames of the set of image data; generating a segmentation input map based at least in part on the series of return signals, the segmentation input map representing one or more regions of interest in the set of image data; and performing target analysis based at least in part on the sigma map to detect the presence or the absence of the response signal from the tissue marker.

2. The method of claim 1 wherein performing target analysis includes ranking each of a plurality of targets with respect to one another.

3. The method of claim 1 wherein performing target analysis includes ranking each of a plurality of targets with respect to one another based on a set of target characterizing criteria.

4. The method of claim 3 wherein ranking each of a plurality of targets with respect to one another based on a set of target characterizing criteria includes ranking each of the plurality of targets based on one, more or all of: frame metrics, region of interest metrics, region of interest relational metrics, and / or shape, of an ultrasound response of a marker.

5. The method of claim 4 wherein performing target analysis further includes detecting the presence or the absence of the response signal from the tissue marker based at least in part on the ranking of each of the plurality of targets with respect to one another.

6. The method of any of claims 1 thorough 5 wherein processing a series of return signals via the return signal processing chain includes mixing the return signals with a first multiple of a mixing frequency and mixing the return signals with a second multiple of a mixing frequency, the second multiple different from the first multiple.

7. The method of claim 6 wherein processing a series of return signals via the return signal processing chain further includes filtering the returns signals resulting from the mixing of the return signals with the first multiple and the second multiple to at least partially filter out ultrasound emitted by the at least one ultrasound transducer.

8. The method of claim 6 wherein processing a series of return signals via the return signal processing chain includes performing envelope detection on each signal that results from the mixing with the first multiple of the mixing frequency and the mixing with the second multiple of the mixing frequency.

9. The method of claim 6 wherein generating a sigma map includes performing a sigma mapping.

10. The method of claim 9 wherein performing a sigma mapping includes performing frame-to-frame comparisons to identify changes in received ultrasound data from frame-to-frame.

11. The method of claim 10 wherein performing a sigma mapping includes one or more of: ensemble focus blending, lateral canceling, summing of differences, and determining lateral standard deviations.

12. The method of claim 11 wherein performing a sigma mapping further includes any one or more of: multiplying two streams of ultrasound data, and performing frame cancellation.

13. The method of claim 6 wherein performing target detection further includes generating beam histograms and generating frame histograms.

14. The method of claim 6 wherein performing target detection further includes applying an adaptive threshold.

15. The method of claim 6 wherein performing target detection further includes performing a focus merge to combine sets of ultrasound data from two or more focus levels.

16. The method of claim 6 wherein performing target detection further includes generating connection map data representing connection information between cells along at least two axes, the at least two axes perpendicular to one another.

17. The method of claim 6 wherein performing target detection further includes calculating distance to a blob edge for each cell of a plurality of cells.

18. The method of claim 6 wherein performing target detection further includes any one or more of: determining a centroid for a blob; performing centroid tracking; and performing centroid merging.

19. The method of claim 6 wherein processing a series of return signals via the return signal processing chain further includes any one or more of: focus mixing and performing scan conversion.

20. The method of claim 19 wherein processing a series of return signals via the return signal processing chain further includes visually and / or aurally presenting marker localization information.

21. The method of claim 20 wherein visually and / or aurally presenting marker localization information further includes presenting a visual representation of a centroid of a marker relative to a visual representation of anatomy.

22. The method of claim 20 wherein visually and / or aurally presenting marker localization information further includes presenting an aural representation of movement of the ultrasound probe with respect to a centroid of a marker.

23. The method of any of claims 1 through 5 wherein generating a set of drive signals via the transmit section of the ultrasound system includes: generating a set of drive signals for an ensemble of ultrasound pulses, each of the pulses in the ensemble of ultrasound pulses having a respective frequency, and each of the frequencies of the pulses of the ensemble of pulses being different from other ones of the frequencies of the pulses of the ensemble of pulses; supplying the drive signals of the set of drive signals to the at least one ultrasound transducer to cause the at least one ultrasound transducer to emit the ultrasound signal with the ensemble of pulses, the frequencies of the pulses of the ensemble of pulses different from the other ones of the frequencies of the pulses of the ensemble of pulses.

24. An ultrasound system, comprising: a transmit section that generates and supplies a set of drive signals to an ultrasound probe having at least one ultrasound transducer to cause the at least one ultrasound transducer to emit ultrasound energy as ensembles of pulses, a respective ensemble of pulses emitted along a respective one of each of a plurality of beams and at a number of focal depths; and a receive section that processes a series of return signals via a return signal processing chain of a receive section of the ultrasound system, the series of return signals representative of ultrasound energy detected by the ultrasound probe, the return signal processing chain performing any of the methods of claims 1 through 23.

25. The ultrasound system of claim 26 wherein the transmit section generates and supplies a set of drive signals according to the method of claim 24.

26. An ultrasound system, comprising: a transmit section that generates and supplies a set of drive signals to an ultrasound probe having at least one ultrasound transducer to cause the at least one ultrasound transducer to emit ultrasound energy as ensembles of pulses, a respective ensemble of pulses emitted along a respective one of each of a plurality of beams and at a number of focal depths; and a receive section that includes a return signal processing chain which processes a series of return signals, the series of return signals representative of ultrasound energy detected by the ultrasound probe, wherein the return signal processing chain: generates a brightness map based at least in part on the series of return signals, the brightness map indicative of intensity levels of the series of return signals in a set of image data; generates a sigma map based at least in part on the series of return signals, the sigma map indicative of changes between frames of the set of image data; generates a segmentation input map based at least in part on the series of return signals, the segmentation input map representing one or more regions of interest in the set of image data; and performs target analysis based at least in part on the sigma map to detect a presence or an absence of a response signal from a tissue marker.

27. The ultrasound system of claim 26 wherein performing target analysis includes ranking each of a plurality of targets with respect to one another.

28. The ultrasound system of claim 26 wherein performing target analysis includes ranking each of a plurality of targets with respect to one another based on a set of target characterizing criteria.

29. The ultrasound system of claim 28 wherein ranking each of a plurality of targets with respect to one another based on a set of target characterizing criteria includes ranking each of the plurality of targets based on one, more or all of: frame metrics, region of interest metrics, region of interest relational metrics, and / or shape, of an ultrasound response of a marker.

30. The ultrasound system of claim 29 wherein performing target analysis further includes detecting the presence or the absence of the response signal from the tissue marker based at least in part on the ranking of each of the plurality of targets with respect to one another.31 . The ultrasound system of any of claims 26 thorough 30 wherein processing a series of return signals via the return signal processing chain includes mixing the return signals with a first multiple of a mixing frequency and mixing the return signals with a second multiple of a mixing frequency, the second multiple different from the first multiple.

32. The ultrasound system claim 31 wherein processing a series of return signals via the return signal processing chain further includes filtering the returns signals resulting from the mixing of the return signals with the first multiple and the second multiple to at least partially filter out ultrasound emitted by the at least one ultrasound transducer.

33. The ultrasound system of claim 31 wherein processing a series of return signals via the return signal processing chain includes performing envelope detection on each signal that results from the mixing with the first multiple of the mixing frequency and the mixing with the second multiple of the mixing frequency.

34. The ultrasound system of claim 31 wherein generating a sigma map includes performing a sigma mapping.

35. The ultrasound system of claim 34 wherein performing a sigma mapping includes performing frame-to-frame comparisons to identify changes in received ultrasound data from frame-to-frame.

36. The ultrasound system of claim 35 wherein performing a sigma mapping includes one or more of: ensemble focus blending, lateral canceling, summing of differences, and determining lateral standard deviations.

37. The ultrasound system of claim 36 wherein performing a sigma mapping further includes any one or more of: multiplying two streams of ultrasounddata, and performing frame cancellation.

38. The ultrasound system of claim 31 wherein performing target detection further includes generating beam histograms and generating frame histograms.

39. The ultrasound system of claim 31 wherein performing target detection further includes applying an adaptive threshold.

40. The ultrasound system of claim 31 wherein performing target detection further includes performing a focus merge to combine sets of ultrasound data from two or more focus levels.41 . The ultrasound system of claim 31 wherein performing target detection further includes generating connection map data representing connection information between cells along at least two axes, the at least two axes perpendicular to one another.

42. The ultrasound system of claim 31 wherein performing target detection further includes calculating distance to a blob edge for each cell of a plurality of cells.

43. The ultrasound system of claim 31 wherein performing target detection further includes any one or more of: determining a centroid for a blob; performing centroid tracking; and performing centroid merging.

44. The ultrasound system of claim 31 wherein processing a series of return signals via the return signal processing chain further includes any one or more of: focus mixing and performing scan conversion.

45. The ultrasound system of claim 44 wherein processing a series of return signals via the return signal processing chain further includes visually and / or aurally presenting marker localization information.

46. The ultrasound system of claim 45 wherein visually and / or aurally presenting marker localization information further includes presenting a visual representation of a centroid of a marker relative to a visual representation of anatomy.

47. The ultrasound system of claim 45 wherein visually and / or aurally presenting marker localization information further includes presenting an aural representation of movement of the ultrasound probe with respect to a centroid of a marker.

48. The ultrasound system of any of claims 26 through 30 wherein generating a set of drive signals via the transmit section of the ultrasound system includes: generating a set of drive signals for an ensemble of ultrasound pulses, each of the pulses in the ensemble of ultrasound pulses having a respective frequency, and each of the frequencies of the pulses of the ensemble of pulses being different from other ones of the frequencies of the pulses of the ensemble of pulses; and supplying the drive signals of the set of drive signals to the at least one ultrasound transducer to cause the at least one ultrasound transducer to emit the ultrasound signal with the ensemble of pulses, the frequencies of the pulses of the ensemble of pulses different from the other ones of the frequencies of the pulses of the ensemble of pulses.