Improved return signal processing and / or organization of emission sets for a marker detection system and method

Abstract

An ultrasound system and method transmits wideband ultrasound via a probe to excite and detect markers in body tissue (e.g., breast, lung). For example, a set of transmitted pulses can advantageously include pulses having different frequencies from one another. Returned ultrasound energy detected by the probe is processed via a return signal processing chain to discriminate the marker's response from other detected ultrasound. The processing is fast enough to accommodate movement of the probe, which is typically hand-held, while providing accurate localization. The 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 that makes inter-frame comparisons, and segmentation mapping. Target analysis can include ranking targets based on a set of target characterization criteria. Optionally, non-linearity is introduced in the transmission and used to discriminate the marker response.

Description

[0001] Cross-references to related applications

[0002] This patent application claims priority to U.S. Patent Application No. 63 / 625,167, filed January 25, 2024, the entire disclosure of which is hereby incorporated herein by reference for all purposes. Technical Field

[0003] This disclosure generally relates to ultrasound systems and methods for detecting markers that can, for example, facilitate the detection of the boundaries of body tissue (e.g., abnormal body tissue) to be monitored, biopsied, removed, or ablated during surgical procedures. Background of the Invention Background Technology

[0005] Various types of markers are used to label body tissue for monitoring over time, or for biopsy, removal, or ablation. Some markers can, for example, allow or enhance visual detection by a surgeon during surgical procedures. Some markers can be detected via various types of energy emission imaging modalities, such as ultrasound, radiographic imaging (e.g., X-ray imaging), computed tomography (CT), computed axial computed tomography (CAT), or magnetic resonance imaging (MRI). These different imaging modalities are often used by different clinicians or technicians in different scenarios, and markers detectable under various visual detection or imaging modalities often require different physical properties to be detectable.

[0006] Some markers may be permanent, while others may be absorbed by the body over time. For example, it may be useful to mark a part of body tissue for follow-up evaluation or testing over a considerable period of time (e.g., months, a year).

[0007] The applicant has developed a multimodal marker that can be detected by ultrasound and by additional imaging modalities (e.g., X-ray, MRI and / or other imaging techniques), and optionally is absorbed over time, and can be long-lasting (e.g., lasting approximately 9 months).

[0008] Markers for use in body tissues take various forms and may include multiple ultrasound-reflecting elements and one or more gels (e.g., hydrogels) binding the ultrasound-reflecting elements together. The ultrasound-reflecting elements may take the form of porous or mesoporous particles or porous or mesoporous hollow shells, for example. The cavities and / or pores of the ultrasound-reflecting elements (e.g., hollow shells, porous or mesoporous particles) may be filled with fluids (e.g., gases (such as air), liquids, or combinations of gases and liquids (e.g., vapors)) and may advantageously be optionally free of perfluorocarbons. The ultrasound-reflecting elements may be coated, for example, with a hydrophobic coating to at least temporarily seal these pores, preventing or delaying the entry of liquids into the cavities inside the ultrasound-reflecting elements (e.g., hollow shells, porous or mesoporous particles).

[0009] Ultrasonic reflective elements may include, or be composed of, silica in one or more forms. Gels (e.g., hydrogels) may be natural gels (e.g., gelatin) or synthetic gels (e.g., polyethylene glycol (PEG)), or markers may be composed of both natural and synthetic gels (e.g., natural and synthetic hydrogels). Gels may be partially or fully cross-linked. Gels (e.g., hydrogels) may be engineered to be absorbed by the body over a period of time, or alternatively may be non-absorbable.

[0010] The marker may optionally include a contrasting element or "contrast agent," allowing it to be detected via one or more imaging modalities in addition to ultrasound. For example, the marker may include one or more radiopaque materials (e.g., metals, gold, platinum, tantalum, bismuth, barium, etc.) to allow it to be detected via X-ray imaging. For example, the marker may include a metal element in the form of a clip (e.g., a wire with a defined shape, such as a spirally wound wire), a strand, or a coil, or a metal element in the form of multiple metal particles. Also, for example, the marker may include one or more MRI imaging contrast materials (e.g., gadolinium-containing compounds, such as gadolinium DTPA, ferrous gluconate, ferrous sulfate, etc.) to allow it to be detected via MRI imaging. Also, for example, the marker may include one or more dyes (e.g., fluorescent dyes, methylene blue) to allow it to be more easily detected visually. Summary of the Invention

[0011] There is a need for improved imaging techniques that do not employ ionizing radiation, such as improved ultrasound imaging techniques that can enhance the detection of markers in body tissues and / or the detection of the boundaries of certain body tissues marked with implanted markers (e.g., abnormal body tissues (e.g., tumors) or suspected abnormal body tissues). This could advantageously allow for marker localization in surgical scenarios where ionizing radiation sources may not be readily available, may be undesirable, or may otherwise be inconvenient to use.

[0012] This disclosure generally relates to the detection of markers in body tissues, and further to systems and methods that can, for example, employ ultrasound processing to facilitate more precise detection of tissue to be monitored, biopsied, removed, or ablated than would be achievable using conventional methods. In at least some setups or implementations, these systems and methods advantageously do not require ionizing radiation to perform marker localization. These systems and methods may be particularly suitable for use in surgical procedures, for example, by a surgeon or other personnel who are not specialized or dedicated medical imaging technicians or ultrasound technicians. Therefore, it is particularly advantageous if the operation of these systems and methods is simplified, for example, by eliminating the need for manual adjustment of settings or input of parameters by the operator (e.g., surgeon). Additionally, it is particularly advantageous if the operation of these systems and methods is adapted, for example, to the movement of the hand holding the probe (e.g., ultrasound probe) of an operator who is not typically a skilled or dedicated ultrasound technician, by accommodating, for example, the imprecise and / or rapid or uneven movement (e.g., varying speed) of the probe. Furthermore, it is particularly advantageous if the operation of these systems provides precise positioning, for example, using visual and / or auditory cues or alarms, in at least a two-dimensional area, and preferably in a three-dimensional volume. Even further, it is particularly advantageous if these systems provide accurate results, resulting in few or no erroneous results (e.g., false detections or false alarms; missing markers when they are present). User feedback can be provided visually (e.g., representation of markers or crosshairs relative to an anatomical image) and / or audibly (e.g., auditory alarms emitted as the probe moves toward or away from a marker in one, two, or even three dimensions).

[0013] Ultrasound systems (e.g., hardware, software, firmware) employ excitation and detection algorithms to discern responses from markers and provide intuitive indications (unique visual indications (which themselves do not represent body tissue) and unique auditory alerts). This is a very different approach compared to commercially available off-the-shelf ultrasound systems. While trained clinicians can use ultrasound images to locate markers in tissue, the method described herein enables faster acquisition and a hands-free, setup-free user experience. In contrast, conventional ultrasound requires trained clinicians to adjust the ultrasound machine settings. Conventional ultrasound is an interpretative visual activity that requires trained clinicians to visually interpret the displayed ultrasound images. In the method described herein, the ultrasound system alerts the clinician in real time whether a marker has been detected and its location within the tissue. Thus, the clinician receives information that can be characterized as a binary answer (e.g., a visually unique presence indication and an auditory presence indication when a marker is located), combined with automatic ranging (e.g., distance and orientation relative to the current location), rather than the clinician having to try to interpret anatomical structures in the ultrasound image. The method described in this article eliminates the need for knobs or clinician adjustments; clinicians can obtain rapid and simple tests through intuitive operation without disrupting normal operating room procedures. This is particularly important in surgical environments where patients are anesthetized, in sterile areas, and where clinicians are often surgeons who are not as experienced with ultrasound as ultrasound technicians and are busy with other aspects of surgery.

[0014] Unlike conventional methods that focus ultrasonic energy onto a specific region of interest (ROI), in one or more embodiments described herein, the transmit beam model disperses energy across the entire probe space. For example, an ultrasonic system may drive an ultrasonic probe to emit a set of ultrasonic pulses, where each pulse in a given set has a different frequency than the other pulses in that set. The frequencies of the pulses in a given set can extend partially or even entirely across the frequency range that the ultrasonic probe (e.g., a crystal) is capable of emitting. This can flatten and extend the response curve (e.g., the K-curve) of the ultrasonic energy returning from the ultrasonic reflector, thereby advantageously reducing variability and extending the time for the response from the ultrasonic reflector to be detectable. This emission method can be used in conjunction with the receive signal processing chain described herein, or with other receive signal processing methods (e.g., the receive signal processing methods described in U.S. Patent Application 63 / 441,558 and U.S. Patent Application 63 / 525,280, and patent applications claiming the benefit or priority of these two patent applications), while still providing technical advantages (e.g., moving away from the fundamental frequency and increasing the sensitivity of the response signal processing chain, increasing the persistence of the response, and / or reducing the transmit voltage and thus reducing background noise).

[0015] In one or more embodiments described herein, the returned ultrasonic energy detected by the probe is processed via a return signal processing chain to distinguish the marker's response from other detected ultrasound. This processing is fast enough to accommodate the movement of a typically handheld probe while providing accurate localization. Processing may include RF filtering and mixing, and demodulation. Processing may include target detection via "image" processing and target analysis based on the marker's known geometry and its response characteristics. Target detection may include brightness mapping, sigma mapping for inter-frame comparison, and segmentation mapping. Target analysis may include ranking targets based on a set of target characterization criteria. Optionally, nonlinearity (e.g., pulses in a given pulse set have different frequencies from each other) may be introduced into the transmission and used to distinguish the marker's response. The improved return signal processing chain offers various technical advantages compared to other receive signal processing methods (e.g., receive signal processing methods described in U.S. Patent Application 63 / 441,558 and U.S. Patent Application 63 / 525,280, and patent applications claiming the benefit or priority of these two patent applications), such as increased sensitivity and more stable, reliable, and consistent results (e.g., fewer false positives and fewer false negatives).

[0016] In at least some implementations, the algorithm executed by the GPU advantageously performs parallel processing back to the signal processing chain to distinguish the response from the marker from all other detected signals and noise.

[0017] The detection imaging system is designed to assist clinicians (e.g., surgeons) in locating implanted tissue markers (e.g., OneMark™ markers from View Point Medical). The system is used to scan and locate physically implanted tissue markers in body tissues (e.g., breast tissue, lung tissue). The system emits pulsed ultrasound energy to excite the tissue marker and then compares the motion changes between sets of pulses from the received ultrasound energy (e.g., return signals or a series of return signals that may constitute scattered or backscattered returns of ultrasound energy from or part of the tissue marker). The pulses cause greater changes at the location where the tissue marker has been placed compared to the energy levels in an unmarked area. The system highlights the location of the tissue marker, for example, on a display (e.g., a liquid crystal display (LCD)) using a color map superimposed on a low-resolution grayscale representation of the anatomical background. The system additionally or alternatively uses supplemental audio and visual feedback to indicate the location of the tissue marker to the clinician, for example, as an XY crosshair centered above the marker in a low-resolution grayscale representation of the anatomical background.

[0018] Generally, surgeons strive to center tissue markers at the site so they can perform resections around them and obtain reasonable confirmation that they have made correct resections. This system supports current standards of care for lesion localization and provides more visual information than currently used wireless localization devices that do not visually display tissue markers. The system and method described herein can generate localization information that advantageously represents the center of tissue marker material (e.g., visually represented by a crosshair), contrasting with the acoustic center of the tag or the center of the guidewire, and can provide real-time image centering of the tissue marker, which is particularly uniquely advantageous in the surgical setting.

[0019] The scanning process employs a non-diagnostic, customized, ultrasound-based approach to stimulate tissue markers and provide clinicians (e.g., surgeons) with real-time images of the tissue marker locations from the skin surface and within the wound during excision. Unlike traditional diagnostic ultrasound imaging, this system does not require quantitative information on any scanned material other than the tissue markers the system is designed to detect. Unlike ultrasound systems designed to show all structural characteristics of tissue (e.g., anatomy), the OneMark™ system optionally and preferably does not offer diagnostic ultrasound modes, is not intended as a tool for qualitative analysis of the tissue itself, and does not offer adjustment controls as commonly found in diagnostic tools. The system can be used to image the location of tissue markers to provide information to aid clinical localization. Advantageously, the system requires minimal setup and is designed for use by surgeons who are not specialized ultrasound technicians and those who do not typically operate ultrasound equipment in their daily practice. It is designed for maximum ease of use by automating the marker detection process and eliminating buttons and / or keypads or keyboards for better adaptation to sterile area applications. The system also advantageously supports rapid marker detection to efficiently support clinicians in treating patients under anesthesia.

[0020] Unlike most diagnostic ultrasound systems that attempt to focus emitted ultrasound energy onto a point of interest, the ultrasound systems and methods described herein distribute the emitted broadband ultrasound energy across the entire region of interest (e.g., the entire breast, the entire lung) in at least one mode. Therefore, the ultrasound systems and methods described herein attempt to achieve higher or even optimal power coupling with tissue markers, rather than attempting to improve resolution as in diagnostic ultrasound. Ultrasound can be emitted as a collection of pulses along various axes, angles, or beams, each associated with a corresponding piezoelectric element, crystal, or transducer of the ultrasound probe. Compared to most ultrasound systems that employ relatively low frame rates and relatively high pulse counts per collection, the ultrasound systems and methods described herein typically employ relatively high frame rates and relatively low pulse counts per collection (e.g., 3, 4, 5), and also typically employ relatively low depths of focus (e.g., 2), all to achieve sufficient speed to accommodate anticipated hand movements of the ultrasound probe. When operating in detector (D) mode, the ultrasound systems and methods described herein can, for example, employ a collection of 5 pulses, for example, down each beam and at 2 different depths of focus. When operating in B mode, the ultrasound systems and methods described herein can, for example, employ a set of four pulses down each beam. In at least some embodiments, the ultrasound systems and methods described herein can, for example, advantageously modify the characteristics (e.g., frequency, period) of each pulse in the set of pulses (pulse set) to flatten the response curve of the received response (e.g., K-curve) and increase the persistence of the detectable return response.

[0021] It is worth noting that the more pulses in the ensemble, the more time is spent transmitting, receiving, and processing ultrasound. This, along with the reliance on recognizing tissue markers in multiple consecutive frames to accurately determine marker location, and the fact that ultrasound probes are typically handheld and subject to movement, imposes constraints on technical operations, including the transmission model, frame rate, and receive signal processing chain. Furthermore, while a relatively large amplitude (e.g., voltage) of the transmitted ultrasound pulses can facilitate the detection of tissue marker responses, several practical considerations may impose constraints. For example, the thermal limits of piezoelectric elements, crystals or transducers, or the ultrasound probe head can limit the amplitude of the transmitted ultrasound pulses that can be used.

[0022] The ultrasound systems and methods described herein can employ a receive signal processing chain to process return signals or a series of return signals, which may constitute scattered or backscattered returns of ultrasound energy from or part of a tissue marker. One or more tissue markers are also referred to herein simply as one or more markers. The receive signal processing chain may include one, more, or all of the following: RF filtering and mixing, demodulation and envelope detection, and target detection and target analysis via “image” processing. The receive signal processing chain may employ target characterization criteria defined based on the known geometry of the marker and its response characteristics. Target detection may include brightness mapping, sigma mapping with inter-frame comparisons, and segmentation mapping. Target analysis may optionally include ranking targets based on a set of target characterization criteria. Target analysis may optionally include determining whether a marker has been detected based at least in part on the ranking. This processing is fast enough to accommodate movement of typically handheld probes while providing accurate localization.

[0023] In some implementations, the system (e.g., an ultrasound system) advantageously injects nonlinearity (e.g., frequency or periodic variations between pulses in a pulse set) into the drive signal, which generates nonlinearity in the ultrasound emission or probe signal, but preferably does not generally alter the emission direction of the ultrasound pulses. The nonlinearity can produce a nonlinear response or return from tissue markers (e.g., from the echogenic portion of a tissue marker), thereby facilitating the ultrasound system's detection of the tissue markers (e.g., matched filtering). The nonlinearity can be periodic, can form or follow a defined pattern, or can be pseudo-random or random.

[0024] In some implementations, the system (e.g., an ultrasound system) and method advantageously process the received ultrasound energy to identify responses from tissue markers and provide visual and / or auditory indications of the presence and / or location of tissue markers, and implementations of target detection in the target detection phase (detector mode or D mode) implemented by the received signal processing chain of the ultrasound system are described in particular in detail.

[0025] In summary, target detection may include executing a target ranking algorithm or process designed to assign each blob a value reflecting how well it matches a specified set of target characterization criteria. The target ranking algorithm or process operates on flattened sigma sector data (e.g., arranged in a 48 × 2640 matrix) to generate a connectivity matrix and a distance matrix of equal size. The segmentation map may represent a set of potential blob centroids and their extensions to the left, right, up, and down. These centroids are then evaluated, for example, to determine how well they match a specified set of target characterization criteria. This specified set of target characterization criteria may include, for example, one, several, or all of the following: a frame metric of the ultrasound response of a tissue marker, a region of interest metric, a region of interest relation metric, and / or shape. Each target characterization criterion may be assigned a weight based on its importance in characterizing the target. The target's centroid may be passed to a centroid tracking algorithm or process. The use of centroids is particularly advantageous in applications where tissue markers are used to label tissue for examination, monitoring, resection, and / or ablation. For example, the presence or absence of a response signal from a tissue marker can be detected, at least in part, based on the order of each of the plurality of targets relative to each other. Attached Figure Description

[0026] In the accompanying drawings, the same reference numerals identify similar elements or actions. The size and relative position of elements in the drawings are not necessarily drawn to scale. For example, the shapes and angles of different elements are not necessarily drawn to scale, and some of these elements are arbitrarily enlarged and positioned to improve the readability of the drawings. In addition, the specific shapes of the elements drawn are not intended to convey any information related to the actual shape of that particular element, and they are selected only for ease of identification in the drawing.

[0027] Figure 1A It is an isometric view of the distal portion of a marker for marking body tissue according to one of the illustrated embodiments, and an instrument selectively operable to implant the marker at a desired location in the body tissue, the marker including: a persistent (e.g., long-term) portion and two additional rapidly dissolving portions.

[0028] Figure 1B This is an isometric view of a marker according to one of the illustrated embodiments, the marker may, for example, employ a durable (long-term) portion ( Figure 1A The persistent (long-term) portion comprises a gel (e.g., hydrogel) carrier, multiple ultrasonic reflective elements, clips, strands or coils detectable via X-ray imaging, and optionally includes a contrast agent to enhance detection in imaging modalities other than ultrasound, wherein a magnified detailed view shows in detail one of multiple aggregates or clusters of ultrasonic reflective elements (e.g., ultrasonic reflective particles or ultrasonic reflective shells).

[0029] Figure 2 It is a schematic diagram of an ultrasound system according to at least one of the illustrated embodiments, wherein an ultrasound transducer is positioned relative to a marker that is ultrasonically reflective and is typically implanted in body tissue. The ultrasound imaging system is operable to induce a response that transmits broadband ultrasound signals into the body tissue and processes the received ultrasound energy to identify or recognize the marker, and to provide appropriate visual and / or auditory indication of the presence and / or location of the marker.

[0030] Figure 3 This is a block diagram illustrating an exemplary structure of an ultrasound system according to at least one of the illustrated embodiments.

[0031] Figure 4 This is a block diagram illustrating an exemplary receiving signal processing chain of an ultrasound system according to at least one of the illustrated embodiments, and its receiving signal processing chain is described in particular in detail.

[0032] Figure 5 It is a high-level block diagram of a receive signal processing chain according to at least one of the illustrated embodiments, the receive signal processing chain being operable to process received ultrasound energy to at least detect the presence or absence of a response from a marker (e.g., a tissue marker), and to provide visual and / or auditory indications of the presence and / or location of the marker.

[0033] Figure 6 It is a graph showing the generation of a set of transmitted pulses according to at least one of the illustrated embodiments.

[0034] Figure 7 This is a flowchart illustrating an operational method for a receive signal processing chain that performs initial processing on raw RF data received from an ultrasonic probe or transducer array, according to at least one of the illustrated embodiments.

[0035] Figure 8A and Figure 8B It is a flowchart illustrating an operation method of a received signal processing chain according to at least one of the illustrated embodiments.

[0036] Figure 9 This is a flowchart illustrating an operational method of a receive signal processing chain for performing GPU RF demodulation processing on raw RF data received from an ultrasonic probe or transducer array, according to at least one of the illustrated embodiments.

[0037] Figure 10 It is a flowchart illustrating an operational method of a received signal processing chain for implementing a GPU RF target sigma mapping level according to at least one of the illustrated embodiments.

[0038] Figure 11 This is a flowchart illustrating an operational method of a received signal processing chain for finding or detecting a region of interest (ROI) according to at least one of the illustrated embodiments.

[0039] Figure 12 It is a flowchart illustrating an operational method of a received signal processing chain for implementing a GPU amplitude segmentation processing chain to generate an amplitude segmentation output, according to at least one of the illustrated embodiments.

[0040] Figure 13 A GPU idle detection method for performing at least a portion of a received signal processing chain is illustrated, implemented between a single-board computer (SBC) and a GPU (SBC / GPU domain) according to at least one of the illustrated embodiments.

[0041] Figure 14 This is a flowchart illustrating a method for executing a single region of interest (ROI) finder sequence as part of a received signal processing chain, according to at least one of the illustrated embodiments.

[0042] Figure 15 This is a flowchart illustrating a target analysis method for finding, analyzing, and tracking a target as part of the operation of a received signal processing chain, according to at least one of the illustrated embodiments.

[0043] Figure 16 It is a flowchart illustrating an operational method of a received signal processing chain for finding, analyzing, tracking, and displaying a target, according to at least one of the illustrated embodiments.

[0044] Figure 17A and Figure 17B This is a schematic diagram showing the transmit (TX) signal path component and the receive (RX) signal path component of an ultrasound system implementing a transmit signal processing chain and a receive signal processing chain according to at least one of the illustrated embodiments. Detailed Implementation

[0045] In the following description, certain specific details are set forth in order to provide a full understanding of the various embodiments disclosed. However, those skilled in the art will recognize that the embodiments can be practiced without one or more of these specific details or using other methods, components, materials, etc. In other instances, well-known structures associated with processors (e.g., microcontrollers), piezoelectric elements, crystals or transducers, power supplies (such as DC / DC power converters), computing systems, and communication networks (e.g., cellular, packet switching), and other communication channels are not shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0046] Unless the context otherwise requires, throughout this specification and the appended claims, the word "comprise" and its variations such as "comprises" and "comprising" shall be interpreted in an open-ended, inclusive sense, that is, as "including, but not limited to".

[0047] Throughout this specification, references to "an embodiment" or "an embodiment" mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in at least one embodiment. Therefore, throughout this specification, the phrase "in one embodiment" or "in an embodiment" appearing in various places does not necessarily refer to the same embodiment. Furthermore, in one or more embodiments, a particular feature, structure, or characteristic may be combined in any suitable manner.

[0048] As used in this specification and the appended claims, unless otherwise expressly stated herein, the singular forms “a,” “an,” and “the” include the plural objects. It should also be noted that the term “or” is used generally to include “and / or” unless otherwise expressly stated.

[0049] As used in this specification and the appended claims, the terms "left," "right," "up," and "down" are used to indicate four directions along two vertical axes relative to a given position, location, or cell in a two-dimensional data array or layout. For example, the terms "left" and "right" may refer to the nearest neighbor in a row located on the corresponding side of a specified position, location, or cell in the array. Similarly, the terms "up" and "down" may refer to the nearest neighbor in a column that is spatially relative to the specified position, location, or cell above and spatially relative to the cell below. It should be noted that the terms "left," "right," "up," and "down" are used for convenience and in a relative sense, not an absolute sense. Therefore, the orientation of the data array or layout can be changed, for example, rotated 90 degrees, 180 degrees, or mirrored.

[0050] Unless otherwise stated, the use of ordinal adjectives such as “first,” “second,” and “third” to describe a common object merely indicates that different instances of the same object are being referred to, and is not intended to imply that the objects described in this way must be in a given order, whether temporally, spatially, sequentially, or in any other way.

[0051] As used in this specification and the appended claims, when referring to executable instructions, the term "one or more modules" includes, by way of example, components such as software components, object-oriented software components, class components and task components, processes, functions, attributes, programs, subroutines, program code segments, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. Functionality implemented in components and modules can be combined into fewer components and modules, or further separated into additional components and modules.

[0052] As used in this specification and the appended claims, the terms “tissue marker” and “marker” are used interchangeably, as are the terms “multiple tissue markers” and “multiple marks”.

[0053] The titles and abstracts provided herein are for convenience only and do not explain the scope or meaning of the embodiments.

[0054] In particular, this article describes systems and methods that can be used to determine the presence or absence and / or location of tissue markers in body tissues using ultrasound. This can be used, for example, to more precisely define the boundaries of abnormal or suspicious tissues (e.g., tumors) in body tissues.

[0055] Figure 1A A marker 100 for marking body tissue according to one of the illustrated embodiments is shown, along with a distal portion of an instrument 101 that can be selectively operated to implant the marker 100 or a portion thereof into a desired location within the body tissue.

[0056] The distal portion of the instrument 101 is shown in cross-section to better illustrate the marker 100. The instrument 101 may be in the form of an applicator, and the distal portion of the instrument 101 may be in the form of a needle or a similar structure having a lumen 101a 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 inward) from the inner wall 101b defining the lumen 101a to better illustrate the outer periphery of the marker 100, but typically the marker 100 will be tightly received and even in contact with the inner wall defining the lumen 101a. The distal portion of the instrument 101 has an opening 101c at its distal end. The distal portion is shown with a pointed or sharp end, for example, for piercing or cutting body tissue.

[0057] exist Figure 1A In the illustrated embodiments, marker 100 includes a durable (e.g., long-term) portion 100a and two additional rapidly dissolving portions 100b, 100c. In some embodiments, one or both of the additional two rapidly dissolving portions 100b, 100c may be optional and therefore may be omitted in some embodiments.

[0058] The durable portion 100a includes a gel 104a, a plurality of ultrasonic reflective elements 102a, 102b (only two are shown) that can be detected ultrasonically (e.g., in detector (D) mode), and one or more detectable objects 106 that can be detected using an imaging modality other than ultrasound. The ultrasonic reflective elements 102a, 102b may, for example, employ porous or mesoporous hollow shells (such as… Figure 1A (as shown) and / or porous or mesoporous particles (such as...) Figure 1B The form shown herein (will be described in more detail). In at least some embodiments, a porous or mesoporous hollow shell can be distinguished from porous or mesoporous particles in that the porous or mesoporous particles do not include a single main internal cavity to which two, more, or generally all the pores are connected (providing a fluid communication path between the exterior of the shell and its single main internal cavity or interior, if not due to a sealing coating (hydrophobic coating)), unlike a shell that includes at least a single main cavity to which two, more, or all the pores are fluidly coupled. The detectable object 106 may, for example, take the form of a clip or strand or coil (e.g., metal) that can be detected using X-ray imaging, as described in more detail herein.

[0059] The gel 104a can, for example, take the form of a partially or fully cross-linked hydrogel to enhance its lifespan when implanted in body tissue, allowing for detection via ultrasound and other imaging modalities throughout diagnostic and therapeutic procedures. The partially or fully cross-linked gel 104a can also advantageously promote bioadhesion between the marker 100 and the implanted marker 100 in body tissue, which is achieved through wound healing processes. For example, the gel 104a provides a fibrotic scaffold, thereby promoting bioadhesion without glue or adhesives. For example, the polymer composition of the gel 104a is engineered to promote minimal intrusion for natural fibrotic healing.

[0060] The first rapid dissolving portion 100b (the relatively inner portion near the durable portion 100a) of the other two rapid dissolving portions 100b and 100c may also include a gel body 104b and multiple ultrasonic reflective elements 102c (only one is shown). The gel body 104b of the first rapid dissolving portion 100b may be polyethylene glycol (PEG) and is generally uncrosslinked or not highly crosslinked, thereby allowing rapid hydration and thus rapid activation of its ultrasonic reflective elements 102c. This rapidly provides a response to ultrasound, thereby assisting clinicians in using the system for detection during the initial implantation of the marker 100. The first rapid dissolving portion 100b is allowed to dissolve after its purpose of providing an ultrasonic response (e.g., backscattering) during the implantation of the marker 100 is completed.

[0061] The second rapid dissolving portion 100c (outermost portion) of the other two rapid dissolving portions 100b and 100c includes a gel body 104c and typically omits the ultrasonic reflective element. A portion of the gel body 104c of the second rapid dissolving portion 100c extends slightly beyond the opening 101c at the distal end of the lumen 101a of the device 101. The portion of the gel body 104c of the second rapid dissolving portion 100c extending slightly beyond the opening 101c has a spherical end 104d to retain the remainder of the marker 100 within the lumen 101a before embedding into body tissue. The gel body 104c of the second rapid dissolving portion 100c may be composed of or constituted of PEG and is typically uncrosslinked or not highly crosslinked, thereby allowing rapid hydration and rapid dissolution after fulfilling its function of retaining the marker 100 within the lumen 101a of the device 101.

[0062] As best shown in the enlarged portion, each of the ultrasonic reflective elements 102a, 102b, 102c has one or more orifices 108 (e.g., mesopores) and contains a fluid 110 (e.g., air or other gas). Each of the ultrasonic reflective elements 102a, 102b, 102c also includes a coating (e.g., a hydrophobic coating 112) that seals the orifices 108 or the interior of the ultrasonic reflective elements 102a, 102b to prevent the ingress of liquids (e.g., water) when implanted into body tissue. The hydrophobic coating 112 may be composed of or contain silicone, for example, or may be composed of or constituted by monoalkoxysilanes, dialkoxysilanes, trialkoxysilanes, or tetraalkoxysilanes.

[0063] Ultrasonic reflective elements 102a, 102b, 102c may comprise, or be composed of, silica or another inert material (e.g., titanium dioxide). When implemented as porous shells, ultrasonic reflective elements 102a, 102b, 102c may be formed, for example, by deposition onto a template followed by removal of the template (e.g., via calcination). An exemplary process for forming ultrasonic reflective elements 102a, 102b, 102c as porous hollow shells begins with a styrene template in solution. TMOS and DETA are added to coat the template with silica. The styrene template is then removed by calcination, and the resulting porous hollow shell is washed and coated with a hydrophobic coating (e.g., silane) to seal the pores and / or internal cavities. The resulting porous hollow shell is then dried. Some or all of the resulting porous hollow shells are then tested to ensure they produce an ultrasonic response. The resulting porous hollow shell is then prepared for addition to a hydrogel to construct marker 100. The ultrasonic reflective elements 102a, 102b, and 102c may, for example, have an overall size or dimension of about 2 μm and a wall thickness of about 30 nm.

[0064] Ultrasonic reflective elements 102a, 102b, and 102c may alternatively comprise titanium dioxide (TiO2) having the same or similar overall structure (e.g., holes, cavities, surface roughness, size (including overall size or dimensions, e.g., 2 μm), shape, wall thickness (e.g., 30 nm)), although this tends to be more toxic and may require FDA approval. Other materials having the same overall structure may be viable candidates for ultrasonic reflective elements 102a, 102b, and 102c, particularly inert materials that can be retained in vivo for relatively long periods (e.g., 9 months, 18 months) without adverse effects, are otherwise suitable for long-term in vivo use, and do not require separate FDA approval.

[0065] Typically, ultrasonic reflective elements 102a, 102b, and 102c tend to aggregate or cluster within gels 104a and 104b, for example, as described in the reference below. Figure 1B What is shown and discussed.

[0066] The cross-linked gel 104a of the persistent portion 100a allows for implantation and retention at a precise location within the target tissue. Multiple ultrasound-reflecting elements 102a, 102b provide unique responses to ultrasound. Clips, strands, or coils (e.g., metal) 106 can be detected via X-ray imaging or potentially some other imaging modality. The shape of the clips, strands, or coils (e.g., metal) 106 can vary between the persistent portions 100a and the persistent portions 100a of the marker 100, allowing for easy identification of two or more distinct persistent portions 100a. As described above, the hydrophobic coating 112 seals fluid 110 (e.g., air) within the orifices 108 of the ultrasound-reflecting elements 102a, 102b, 102c. The hydrophobic coating of the ultrasonic reflective elements 102a, 102b of the durable portion 100a of marker 100 is selected to seal these pores 108 for a long period (e.g., 9 months, 18 months) when implanted in body tissue and thus hydrated by bodily fluids. The relatively inner first rapid-dissolving portion (with a porous shell) 100b facilitates implantation because the cross-linked gel 104a of the durable portion 100a does not hydrate quickly enough during implantation to be visible via ultrasound. The relatively outermost rapid-dissolving portion (without a porous shell) 100b serves as a plug.

[0067] The ultrasonic reflective elements 102a, 102b of the persistent portion 100a of marker 100 are the primary source of the ultrasonic response. The ultrasonic reflective elements 102a, 102b provide the basic scattering surface, and reflection is enhanced due to their porous nature and the fluid 110 sealed within the pores 108 via a hydrophobic coating 112. The surface roughness and wall thickness of the ultrasonic reflective elements 102a, 102b, 102c can affect the response to ultrasound (e.g., backscattering). The housing structure and its porous or mesoporous nature are controlled by chemical composition and chemical processes, for example, by depositing a silica sheet on a template and subsequently calcining it to remove the template and create cavities in the ultrasonic reflective elements 102a, 102b, 102c. The porous or mesoporous nature allows acoustic energy to enter one or more cavities of the ultrasonic reflective elements 102a, 102b, 102c, for example, into bubbles trapped within one or more cavities, thereby initiating or enhancing the type of scattering that facilitates detection in detector (D) mode operation. The overall size of the ultrasonic reflective elements 102a, 102b, 102c and / or the overall size of the aggregates of the ultrasonic reflective elements 102a, 102b, 102c can alter the performance spectrum. A hydrophobic coating 112 seals these orifices 108 to prevent fluid from entering the ultrasonic reflective elements 102a, 102b, 102c, thus preventing them from "wetting out," which would otherwise reduce the signal-to-noise ratio (SNR) of the ultrasonic response. The ultrasonic reflective elements 102a, 102b, 102c generate a B-mode response in ultrasonic imaging, a composite effect because the color mode is superimposed on the B-mode. The B-mode signal output transmits multiple sets of B-mode imaging data (also referred to as B-image data or B-images), which, in some embodiments, are then interpreted into color Doppler images using color Doppler techniques. This structure (especially when suspended in a gel matrix that allows movement in response to ultrasonic energy) advantageously provides a wide harmonic spectrum that can be detected via the detector (D) mode operation described herein. The amount of ultrasonic reflective elements 102a, 102b, 102c used to achieve detection is very low.

[0068] In some embodiments, ultrasonic reflective elements 102a, 102b, 102c may leak from the cross-linked gel 104a or otherwise leach out, but tend to remain near the site of the marker 100 and can still be detected using the ultrasonic techniques and processes described herein.

[0069] An example process for forming marker 100 includes cooking a gel (e.g., a hydrogel component). An ultrasonic reflective element may be coated with a hydrophobic polymer. The coated ultrasonic reflective element is added, for example, via an injection mixer to a hot mixture of the gel, to form a colloidal dispersion or suspension of the coated ultrasonic reflective element in the gel. Gel tubes with ultrasonic reflective elements are formed, for example, using a custom syringe for the durable portion 100a and the first rapid-dissolving portion 100b of marker 100. Tubes without ultrasonic reflective elements are formed, for example, using a custom syringe for the second rapid-dissolving portion 100c. The tubes can then be cut to the desired size, for example, based on the corresponding portions 100a, 100b, 100c of marker 100. A detectable object 106 (e.g., a clip, strand, coil, or metal) is added, for example, via a mandrel to the tube to be used in the durable portion 100a of marker 100. The tube is then removed from the mandrel and dried.

[0070] Figure 1B An exemplary marker 120 for marking body tissue is shown, which can be detected via the systems and methods described herein. Various implementations and embodiments are not limited to use with the exemplary marker 120, but can be advantageously used with other markers including ultrasound-detectable elements. Marker 120 may, for example, be or utilize the persistent portion 100a of marker 100 (… Figure 1A (in the form of ).

[0071] The marker 120 includes a gel 124, a plurality of ultrasonic reflective elements 102a (only two are shown in the detailed view) that can be detected ultrasonically (e.g., detected using detector (D) mode operation), and one or more detectable objects 106a that can be detected using an imaging modality other than ultrasound. The ultrasonic reflective elements 102a may, for example, employ a porous or mesoporous hollow shell (such as… Figure 1A (as shown) and / or porous or mesoporous particles (such as...) Figure 1B The detectable object 106a can take the form of a clip, strand, or coil (e.g., metal) that can be detected using X-ray imaging, as described in more detail herein.

[0072] The ultrasonic reflective elements 102 may tend to aggregate or form aggregates or clusters 122, as shown. A gel 124 binds together the aggregates or clusters 122 of the plurality of ultrasonic reflective elements 102. The aggregates or clusters 122 may be dispersed throughout the gel 124, for example, in the form of a colloidal dispersion. When the gel 124 is hydrated, the aggregates or clusters 122 of the plurality of ultrasonic reflective elements 102 are suspended or in a suspended state and may move relative to each other and / or relative to an external reference frame over at least a distance and in one or more directions, which may advantageously induce or increase ultrasonic backscattering. In some embodiments, the aggregates or clusters 122 of the plurality of ultrasonic reflective elements 102 may leak from or otherwise leach out of the cross-linked gel 124, but still tend to remain near the site of the marker 120 and can still be detected using the ultrasonic techniques and processes described herein.

[0073] Gel 124 can take various forms. Gel 124 may, for example, comprise one or more hydrogels. Gel 124 may comprise a natural hydrogel (e.g., gelatin). Gel 124 may comprise a synthetic hydrogel (e.g., polyvinyl alcohol (PVA) hydrogel or polyethylene glycol (PEG) hydrogel). Gel 124 may comprise a combination of natural hydrogels (e.g., gelatin) and synthetic hydrogels (e.g., PVA hydrogel, PEG hydrogel). In at least some embodiments, gel 124 is at least partially crosslinked hydrogel. In at least some embodiments, gel 124 is gelatin (e.g., crosslinked gelatin). In at least some embodiments, gel 124 is a PVA hydrogel (e.g., crosslinked PVA hydrogel). In at least some embodiments, gel 124 is a PEG hydrogel (e.g., crosslinked PEG hydrogel). In at least some embodiments, gel 124 comprises a combination of natural and synthetic hydrogels, for example, as corresponding gels coupled to each other.

[0074] The gel 124 may be non-absorbable by the body (e.g., lasting 60 years or longer) or may be absorbable by the body over a period of time. In the absorbable case, the gel 124 may be engineered (e.g., via the degree and / or strength of cross-linking) to persist in the body for a period of time, such as hours, days, weeks, months, months, or even years. In at least some embodiments, upon implantation, the outer or exposed portions of the absorbable gel 124 may be absorbed earlier than the more internal portions of the gel 124, with absorption occurring when the various portions of the gel 124 are exposed to body tissues (including bodily fluids). In at least some embodiments, the gel 124 may be engineered (e.g., with a controlled cross-linking distribution profile) to cause some portions to be absorbed faster than others and / or to ensure that some portions persist longer than others. Therefore, various absorption distribution profiles may be formed across the gel 124 or throughout the entire gel.

[0075] Each ultrasonic reflective element is highly reflective of ultrasound. Each ultrasonic reflective element preferably has an irregular surface, such as a rough outer surface, to cause scattering or dispersion of ultrasonic energy. The ultrasonic reflective element 102 can be in the nanometer size range (e.g., from 1.8 micrometers to about 2.2 micrometers).

[0076] The ultrasonic reflective element 102 is typically echogenic and can take any of a variety of forms.

[0077] The ultrasonic reflective element 102 may be porous or mesoporous, having pores and / or cavities to hold gas. (See reference...) Figure 1A and Figure 1B The ultrasonic reflective element 102 discussed may include a hydrophobic coating to prevent liquid ingress, thereby protecting gases (e.g., air) from “wetting” that would otherwise significantly impair functionality.

[0078] In at least one embodiment, each ultrasonic reflector includes a porous hollow shell, such as a porous hollow silica shell, the shape of which may or may not be spherical. In at least one embodiment, each ultrasonic reflector includes particles that are not hollow shells but porous, and may or may not be porous non-spherical particles. Each ultrasonic reflector may, for example, include a corresponding particle comprising, or composed of, silica having pores but not a single defined hollow internal cavity. Each particle may include one or more layers ( Figure 1A and Figure 1B (Not shown in the image). The one or more layers may include a contrast agent to enhance detection via modalities other than ultrasound imaging, as discussed below. Alternatively, one or more ultrasound reflective elements may include, or consist of, one or more contrast agents.

[0079] Some or all of the gel 124 (e.g., a hydrogel carrier) and / or the ultrasonic reflective element 102 may optionally carry one or more contrast agents 126. Contrast agents 126 may, for example, include one or more contrast agents that enhance naked-eye visual detection or detection using X-ray or MRI imaging modalities. Contrast agents 126 may, for example, include dyes to enhance detection by direct visual observation (whether naked-eye or assisted (e.g., via UV or “black light” illumination)). Dyes may advantageously be fluorescent dyes. Dyes may, for example, contain methylene blue, or be composed of it. Contrast agents 126 may, for example, include radiopaque materials (e.g., gold, platinum, tantalum, bismuth, barium, etc.), or be composed of it. Contrast agents 126 may, for example, include MRI imaging materials (e.g., compounds containing gadolinium, such as gadopentetate dimeglumine, ferrous gluconate, ferrous sulfate), or be composed of it.

[0080] Alternatively, one or more contrast agents 126 (e.g., the contrast agent 126 identified above) may be incorporated into or around the gel 124. Detectable objects 106a (e.g., clips, strands of wire, spring coils, or spirally wound wires or other radiopaque elements) may be incorporated into or around the gel 124.

[0081] In at least one embodiment, each ultrasonic reflective element 102 includes a hollow shell. Each hollow shell has at least one outer wall forming a cavity. In at least some embodiments, the hollow shell is a multi-layered hollow shell, for example, a shell having an inner layer and an outer layer. Each hollow shell is highly reflective of ultrasound. Each hollow shell preferably has an irregular surface, for example, a rough outer surface, to cause scattering or dispersion of ultrasonic energy. The hollow shell can be in the nanometer size range.

[0082] In at least some embodiments, each hollow shell may comprise, or alternatively comprise, silicon dioxide or titanium dioxide. Some techniques for forming hollow shells in the nanoscale range are described, for example, in the following documents: 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; US Patent Application 15 / 706446; US Patent Application 62 / 135653; US Patent Application 15 / 559764; International Patent Application PCT / US2016 / 23492; US Patent Application 62 / 483274; US Patent Application 62 / 645677; US Patent Application 15 / 946479; and International Patent Application PCT / US2018 / 26291.

[0083] In some embodiments, the hollow shell or porous particles, or one or more layers of the hollow shell or porous particles, may include one or more contrast agents (e.g., the contrast agents identified above) to enhance visual inspection, radiological inspection, or MRI inspection.

[0084] In at least some embodiments, the cavity and / or aperture of the ultrasonic reflector element 102 contains a fluid, i.e., a gas, a liquid, or a combination or mixture of one or more gases and one or more liquids; however, it is generally preferred that the gas remain in a gaseous state even during ultrasonic energy probing during use. The gas may be in the form of one material, while the liquid may be in the form of a different material than the material forming the gas. Alternatively, the gas and liquid may be the same material, just in different phases. The combination or mixture of gas and liquid may, for example, be in the form of vapor, whether at rest or when subjected to ultrasound at a certain threshold energy level that causes heating. The cavity of at least one hollow shell may, for example, contain air. Alternatively, the cavity and / or aperture of the ultrasonic reflector element 102 may contain an inert gas (e.g., nitrogen, argon) or even, less desirable, perfluorocarbons. The cavity and / or aperture preferably does not contain any perfluorocarbons, whether in gaseous or liquid form.

[0085] Each ultrasonic reflector 102 may be porous or mesoporous. In the case where the ultrasonic reflector 102 contains a fluid (i.e., a gas, a liquid, or a combination or mixture of gas and liquid), the ultrasonic reflector 102 may optionally and preferably include a coating, preferably a hydrophobic coating, for sealing cavities and / or pores, which at least temporarily seals its cavities and / or pores, thereby preventing fluid from entering the pores or cavities of the ultrasonic reflector 102 from body tissue.

[0086] In some embodiments, the gel 124 may be expandable, for example, when implanted into body tissue. In some embodiments, the marker 120 may have a length of about 2 mm to about 40 mm and a lateral dimension of about 0.5 mm to about 2 mm in its unexpanded state. The marker may have a size expansion ratio from a dry, unexpanded state to a water-saturated expanded state of about 1:1.5 to about 1:10. The marker 100 may have a size expansion ratio from a dry, unexpanded state to a water-saturated expanded state of about 1:2 to about 1:3.

[0087] This disclosure also generally relates to markers 100, 120 (e.g., tissue markers) that possess physical properties that make markers 100, 120 more easily identifiable via detector (D) mode operation when implanted into body tissue. Such markers 100, 120 may include gels 104a, 104b, 124 having, for example, a plurality of ultrasonic reflective elements 102a, 102b, 102c (e.g., porous shells, porous particles) suspended and fixed within the gels 104a, 104b, 124. The ultrasonic reflective elements 102a, 102b, 102c may, for example, be dispersed throughout the gels 104a, 104b, 124, for example, as a colloidal dispersion or colloidal suspension.

[0088] Gels 104a, 104b, and 124 may be in the form of hydrogels. Gels 104a, 104b, and 124 may be fully or partially cross-linked, provided that when gels 104a, 104b, and 124 are hydrated, ultrasonic reflective elements 102a, 102b, and 102c are free to move (e.g., vibrate or oscillate) to a sufficient degree or distance in at least one dimension (e.g., along at least one axis, and preferably along two or more axes) to enhance any scattering return from ultrasonic reflective elements 102a, 102b, and 102c in response to ultrasonic probing of markers 100 and 120.

[0089] The ultrasonic reflective elements 102a, 102b, and 102c will typically have irregular surfaces that cause scattering (e.g., backscattering) in response to ultrasonic probing of the markers 100 and 120. The ultrasonic reflective elements 102a, 102b, and 102c will typically contain a fluid (i.e., a gas, liquid, or a combination of gas and liquid) that enhances the backscattering in response to ultrasonic probing of the markers 100 and 120. The ultrasonic reflective elements 102a, 102b, and 102c will typically include a hydrophobic coating (e.g., silicone) that retains the fluid (e.g., air) within the housing for an extended period of time (e.g., 3 months, 9 months, 18 months) while preventing liquid ingress even when the markers 100 and 120 are subjected to the receiver fluid during the extended period of time. This advantageously prevents the ultrasonic reflective elements 102a, 102b, and 102c from "wetting," which would otherwise reduce or even eliminate detectable scattering. Gels 104a, 104b, and 124 can be dried, dehydrated, or freeze-dried until implanted into body tissue, and will then hydrate over time as fluids (e.g., water) are absorbed from the body tissue. Gels 104a and 124 also provide a framework for bioadhesion via the natural healing process of fibers in body tissue where markers 100 and 120 are implanted. This allows markers 100 and 120 to be secured in the appropriate location within the body tissue without the use of glue or adhesives.

[0090] The various physical structures or properties of these described physical structures or properties of markers 100, 120 provide or enhance the scattering (e.g., backscattering) of ultrasound from markers 100, 120, and particularly contribute to the variation of the position and / or velocity of ultrasound reflecting elements 102a, 102b, 102c (whether individually or in the form of aggregates or clusters 122), resulting in a broad velocity spectrum that contributes to detectability using the detector (D) mode ultrasound techniques described herein. The physical properties of the aggregates or clusters 122 of the ultrasonic reflective elements 102a, 102b, 102c or the ultrasonic reflective elements 102a, 102b, 102c may vary from the persistent portion 100a to the persistent portion 100a and / or from its rapidly dissolving portion 100b to the rapidly dissolving portion 100b of the different markers 100, allowing two or more different persistent portions 100a to be easily distinguished from each other based on unique response signals, and / or allowing two or more rapidly dissolving portions 100b to be easily distinguished from each other based on unique response signals.

[0091] Unbound by theory, it is assumed that the response of markers 100 and 120 depends on the vibration of ultrasonic reflective elements 102a, 102b, and 102c within the hydrogel matrix or upon immersion in body tissue. Vibration and / or immersion are influenced by numerous factors. For example, vibration within the hydrogel matrix is ​​achieved through a limited crosslinking length of the PEG (between 50 nm and 100 nm between the four arm junctions). This limits the range of motion of ultrasonic reflective elements 102a, 102b, and 102c within the matrix of at least partially crosslinked gel bodies. Also, for example, the motion of ultrasonic reflective elements 102a, 102b, and 102c induced by incident emitted waves is limited by the size range of the ultrasonic reflective elements 102a, 102b, and 102c (e.g., about 2 μm) and the size range of the aggregates or clusters 122 of the ultrasonic reflective elements 102a, 102b, and 102c (each cluster consisting of approximately 2 to approximately 6 porous shells, with an overall size of approximately 12 μm). For example, vibrations in the hydrogel matrix are affected by the span of the interstitial hydrogel between the hydrophobic aggregates or clusters 122 of the ultrasonic reflecting elements 102a, 102b, 102c (i.e., where ultrasonic reflecting elements 102a, 102b, 102c are absent), which ranges from about 3 μm to about 15 μm (inclusive), with a typical distance of about 6 μm to about 9 μm (inclusive). As another example, vibrations in the hydrogel matrix are affected by the crosslinking density of the polymer mixture, which can be characterized, for example, by a measure of water swelling, such as 15 times the dry mass of the polymer matrix.

[0092] Furthermore, the excitation frequency affects the motion behavior of the ultrasonic reflective elements 102a, 102b, and 102c, with a maximum value at a specific frequency (e.g., MHz). For example, a PEG-PEG amine hydrogel design with an 8 mg / ml concentration of ultrasonic reflective elements 102a, 102b, and 102c per gel pad exhibits peak variance at 2.76 MHz, 3.33 MHz, and 4.44 MHz.

[0093] In one example, the aggregates or clusters 122 of the ultrasonic reflective elements 102a, 102b, 102c have dimensions from about 10 μm to about 30 μm and are coated or sealed to prevent liquid ingress and / or gas escape. Backscattering perturbed by the ultrasonic reflective elements 102a, 102b, 102c generates additional harmonics in the returned signal. This can be enhanced by selecting the frequency. Changing the wavelength of the ultrasonic probe or emitted signal to suit the scattering structure (e.g., across 500 ultrasonic reflective elements 102a, 102b, 102c) advantageously produces a broad spectral response. Crosslinking affects the range of motion of the ultrasonic reflective elements 102a, 102b, 102c, as well as the aggregates. Crosslinking is typically characterized on the order of angstroms, while the size of the ultrasonic reflective elements 102a, 102b, 102c is typically characterized on the order of micrometers.

[0094] Figure 2 A marker 200 implanted in body tissue 202 according to at least one of the illustrated embodiments is shown, as well as an ultrasound system 204 having an ultrasound probe or transducer array 206 positioned to detect the marker 200.

[0095] The ultrasound system 204 includes a transmitting section 208 and a receiving section 210. The transmitting section 208 generates a drive signal and drives an ultrasound probe or transducer array 206 to emit ultrasound energy pulses (e.g., a set of pulses along each beam or angle from a respective ultrasound piezoelectric element, crystal, or transducer of the ultrasound probe or transducer array 206). The receiving section 210 receives a signal representing the ultrasound energy detected by the ultrasound probe or transducer array 206 (e.g., a return signal or a series of return signals, which may constitute a scattered or backscattered return of ultrasound energy from or part of a marker), and processes the received signal using a received signal processing chain (examples of which are described herein) based on a known emission model (e.g., pulse set, pulse repetition frequency) to identify and / or locate the marker. The ultrasound system 204 can operate in any one or more operating modes (e.g., mode A, mode B, mode M, color Doppler mode, energy Doppler mode). In some implementations, the ultrasound system 204 will alternate between modes (e.g., between capturing B-mode frames to image, for example, an anatomical structure, and capturing detector (D) mode frames to detect responses from markers with echogenic features (e.g., without generating an image of the anatomical structure).

[0096] In some embodiments, the transmitting section 208 has an associated fundamental frequency or baseband, i.e., the fundamental frequency or baseband of the ultrasonic signal emitted by the ultrasonic probe or transducer array 206. This can be, for example, in the range of 2 MHz to 20 MHz (inclusive). In some embodiments, the transmitting section 208 can cause the ultrasonic probe or transducer array 206 to emit pulses at various different frequencies, for example, emitting pulse sets (e.g., four pulses per set), wherein each pulse in the pulse set is emitted at a corresponding frequency different from the frequency of the other pulses in that set. This is in Figure 6 The text is presented in the middle and discussed below. Figure 6 This will be discussed in more detail. It should be noted that, compared to relying on a single fundamental frequency or baseband for all pulses in the pulse set, this method can advantageously reduce the variability of the response curve and prolong the time (persistence) for which the response from the marker can be detected in the returning ultrasound.

[0097] The ultrasound system 204 includes a master clock or oscillator 212 that outputs a timing signal. The timing signal output by the master clock or oscillator 212 can, for example, set or be used to set the nominal pulse repetition frequency (PRF), i.e., the frequency at which ultrasound pulses repetite (e.g., a default frequency, an automatically set frequency, or even a user-set frequency). In at least some embodiments, the nominal pulse repetition frequency can advantageously be a default value or automatically set, for example, based on the type of marker being used and / or based on the type of ultrasound probe or transducer array 206 being used. Less preferably, the nominal pulse repetition frequency value can be set by the operator, at least within a certain defined range. In other embodiments, the nominal pulse repetition frequency can be a fixed characteristic of a particular ultrasound system 204 and / or marker 200 and / or ultrasound probe or transducer array 206.

[0098] As described herein, in some embodiments, the transmitting section 208 of the ultrasound system 204 may optionally introduce variations (e.g., nonlinearities) in the ultrasound energy emitted by the ultrasound probe or transducer array 206, and the receiving section 210 may employ variations (e.g., nonlinearities) in the received ultrasound energy (e.g., a return signal or a series of return signals that may constitute a scattering or backscattering return of ultrasound energy from or a portion of a marker) to facilitate marker detection (e.g., via matched filtering). For example, in at least some embodiments, the transmitting section 208 preferably includes a variation circuit (VAR) 214 that introduces one or more variations (preferably nonlinear variations) in the ultrasound emission. This can advantageously result in or otherwise produce artifacts in the returned ultrasound that can make the response from the marker more detectable or discernible. Nonlinear variations in the ultrasound emission can take any one or more forms and enhance the ability of the systems and methods described herein to reliably detect markers in body tissues, advantageously without requiring the reading or interpretation of ultrasound images. It should be noted that various embodiments of the receiving section 210 and the associated receiving signal processing chain can operate successfully without introducing changes or nonlinearities into the emitted ultrasonic transmission. It should also be noted that when changes (e.g., nonlinearities) are introduced into the transmission model, various embodiments of the receiving section 210 and the associated receiving signal processing chain can be simplified relative to the illustrated embodiment in at least some instances; for example, it may allow the omission or simplification of some filtering, signal or image processing, and / or culling originally included in the illustrated receiving signal processing chain.

[0099] Nonlinear variations in ultrasonic emission can include, for example, variations in amplitude or voltage, and therefore variations in the output power of the ultrasonic emission. Alternatively or additionally, nonlinear variations can include, for example, variations in the pulse repetition frequency (PRF), which indicates the number of ultrasonic pulses emitted by the ultrasonic probe or transducer array 206 within a specified time period (e.g., typically between 1 kHz and 10 kHz). Alternatively or additionally, nonlinear variations can include, for example, variations in the fundamental frequency or phase of the ultrasonic emission emitted by the ultrasonic probe or transducer array 206. Therefore, optional variations can be variations in any one or more of the following: amplitude or voltage, time, frequency, and / or phase. Optional variations can be implemented, for example, via one or more resistors, resistor networks, or varistors to adjust the amplitude, or via one or more delay circuits or capacitors, such as delaying a clock signal. Variations can be periodic, can follow a certain pattern, or can be pseudo-random, for example, generated via a pseudo-random number generator (also known as a random number generator (RNG)). As an example, as indicated by the dashed arrow, optional variations can be provided to amplifier 218 to change the amplitude or voltage, or to gate generator 216 to change the PRF or phase, or otherwise to change the fundamental frequency or baseband of the ultrasonic transmission. These variations can also be provided to receiver section 210 to identify which received ultrasonic signals correspond to the response returned by the marker.

[0100] The receiving section 210 receives signals (e.g., raw RF) representing ultrasonic energy detected by the ultrasound probe or transducer array 206 (e.g., a return signal or a series of return signals, which may constitute a scattered or backscattered return of ultrasonic energy from or a portion of a marker). These signals typically represent ultrasonic energy reflected or otherwise returned from an object in the field of view of the ultrasound probe or transducer array 206. These objects may include the marker itself as well as body tissue. The signals representing ultrasonic energy detected by the ultrasound probe or transducer array 206 may also represent outgoing ultrasonic emissions (i.e., ultrasonic pulses emitted from the ultrasound probe or transducer array 206 toward body tissue) and other noise. The receiving section 210 includes a complex receive signal processing chain 220 comprising various receive signal processing stages to remove noise, increase the signal-to-noise ratio, and identify, recognize, and / or locate or locally localize those signals representing ultrasonic energy returned from the marker. For ease of discussion, the signals representing ultrasonic energy detected by the ultrasound probe or transducer array 206 are sometimes referred to herein as received signals. The emitted ultrasound is preferably broadband. As described herein, frame-by-frame analysis can be performed to isolate the emitted frequency from other frequencies in the response, and the relatively large response of the echogenic material is preferably identified via artifacts representing the response to the set of emitted pulses.

[0101] The receiving section 210 may include one or more amplifiers 222 to amplify the received signal (e.g., a return signal or a series of return signals that may constitute a scattering or backscattering return of ultrasonic energy from or part of a marker) detected by the ultrasonic probe or transducer array 206. Any one or more of a variety of amplifiers suitable for amplifying signals from the ultrasonic probe or transducer array 206 may be employed.

[0102] The received signal processing chain 220 may optionally include a DC canceller 224 (e.g., a high-pass filter) that removes or eliminates the DC component from the received signal detected by the ultrasonic probe or transducer array 206.

[0103] The receiving signal processing chain 220 may optionally include one or more matched filters (e.g., pulse matched filters) that filter the amplified signal, for example, allowing detected reflected or returned ultrasonic pulses that match the pattern of the outgoing ultrasonic pulses to pass through, and rejecting noise and other signals.

[0104] The receive signal processing chain 220 includes a set of RF stages 228. The RF stages 228 process beamforming RF data, for example, by applying RF filters and mixing. The following section discusses... Figure 4 (See RF Class 416) RF Class 228 is described in more detail.

[0105] The receive signal processing chain 220 includes a set of detector stages 230. Detector stages 230 demodulate the raw RF data. The following section discusses... Figure 4 (See detector level 418) Detector level 230 is described in more detail.

[0106] The receiving signal processing chain 220 may include a set of target stages 232. Target stages 232 represent pairs of signals generated by an ultrasonic probe or transducer array 206 ( Figure 2 The detected ultrasound signal data undergoes "image" processing. The following section discusses... Figure 4 (See object detection level 424) Object level 232 is described in more detail below, and further details are provided below. Figure 5 as well as Figures 7 to 16 The operation of the receive signal processing chain is described in more detail. The target level 232 typically seeks unique return signals (e.g., artifacts) from markers without requiring assessment of anatomical structures.

[0107] The receiving segment 210 may include one or more presentation stages 234. The presentation stage 234 processes data (e.g., data representing the location or centroid of a marker, and optionally data representing anatomical structures) to allow presentation to a user, for example, via a display screen or other visual and optionally auditory cues. For example, a representation of the location of a marker or the centroid of a marker (e.g., captured during detector mode or “D” mode operation) may be visually represented on a display screen overlaid or superimposed on a low-resolution representation of the anatomical structure (e.g., captured during B mode operation) to facilitate visualization of the marker’s position relative to various anatomical features of the body. In at least some instances, the centroid of a marker may correspond to the location of a flickering or glittering effect or artifact in ultrasound imaging. The following section discusses… Figure 4 For a more detailed description of presentation stage 234 (see scan converter 430 and associated beam geometry 431 and associated B-graph data 432, image filter stage 434, scan converter 436, image filter stage 440, image merger 442 and image pane 444).

[0108] Figure 3 An exemplary structure of an ultrasound system 300 according to at least one of the illustrated embodiments is shown. The ultrasound system 300 may, for example, be an ultrasound system 204 ( Figure 2 The implementation method of ).

[0109] The ultrasound system 300 may include a housing or console housing electronics, such as a circuit card with three custom sub-components, a single-board computer, and a custom power supply sub-component. The ultrasound system 300 is preferably fully self-contained, wherein all executable instructions (e.g., software, firmware) are executed internally on appropriate hardware (e.g., a processor), and user output is provided to an LCD screen and speakers, which are part of the ultrasound system 300 and preferably housed within the housing or console. In normal use, only two additional electrical connections are made to the ultrasound system 300: one to the ultrasound probe or transducer array 206, and the other to an AC line power supply (e.g., a power outlet).

[0110] The ultrasonic probe or transducer array 206 is preferably a self-contained transducer assembly (e.g., a linear or two-dimensional array comprising piezoelectric elements, crystals, or transducers). The ultrasonic probe or transducer array 206 is attached to the back of the housing of the ultrasonic system 300. The ultrasonic probe or transducer array 206 can be removed and replaced, for example, if defective. The ultrasonic probe or transducer array 206 is managed by and specifically matched to the ultrasonic system 300. In at least some embodiments, the ultrasonic probe or transducer array 206 may be, for example, in the form of a passive ultrasonic probe. In at least some embodiments, the ultrasonic probe or transducer array 206 may, for example, provide identification capabilities (e.g., identifying a specific ultrasonic probe or transducer array 206 or at least its brand and model). Preferably, user interaction with the ultrasonic system 300 is minimized, for example, turning on the ultrasonic system 300, placing and / or moving the ultrasonic probe or transducer array 206 on or relative to a part of the body until a response is achieved, without requiring the user to set any values ​​or operating parameters.

[0111] The ultrasound system 300 may include, for example, a computer, preferably a single-board computer (SBC) 302 (e.g., a processor, memory, or storage device), and may also include an ultrasound motherboard 304 communicatively coupled to the SBC 302 via a hardware interface 306 and any associated driver (e.g., a software or firmware communication driver).

[0112] The ultrasound system 300 may, for example, additionally include one or more cards or plates ( Figure 3 (Not shown in the diagram), for example, for managing and distributing power and / or communication (e.g., referred to herein as a carrier card). The carrier card can, for example, connect to and power all components of the ultrasound system 300, such as: system power supply, SBC 302, ultrasound motherboard 304, display monitor, USB connector, audio speaker, fan, thermistor, and power ON switch. The carrier card may also have circuit components such as: tracking transmitter regulator, magnetic high-voltage power supply (magnetic element), audio amplifier, and / or fan motor controller.

[0113] SBC 302 may have one or more processors and one or more memories or other non-transitory storage media communicatively coupled to the one or more processors. Processors may include, for example, one or more of the following: microprocessor, microcontroller, central processing unit (CPU), digital signal processor (DSP), graphics processing unit (GPU), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), and / or programmable logic controller (PLC), etc. Memory may include, for example, one or more of the following: read-only memory (ROM), random access memory (RAM), EEPROM, flash memory, and / or registers, etc. Other non-transitory storage media may include, for example, one or more of the following: disk and associated disk drive, optical disk and associated optical disk drive, and / or solid-state drive (SSD), etc. In the illustrated embodiment, single-board computer 302 is shown as including CPU 308 (e.g., the CPU of a microprocessor) and GPU 310 communicatively coupled to CPU 308; however, those skilled in the art will understand that other sets of components and arrangements of these components are possible, and the illustrated embodiment is not intended to be limiting.

[0114] The SBC 302 controls the overall operation of the ultrasound system 300 and communicates through many different types of interfaces, such as: front panel interface, front audio interface, USB 2.0 and 3.0 interfaces, PCIe interface, and power input interface. The carrier card routes these signals to their appropriate destination connectors. Using a separate card or board (e.g., a carrier card) facilitates modifications to the ultrasound system 300, for example, allowing future modifications to the SBC 302 to use different hardware and / or operating systems.

[0115] The SBC 302 can be powered by the system's +12 V power supply distributed via the carrier card. The SBC 302 also shares a common ground with the ultrasound system 300. The connector can be, for example, a 2-pin Samtec IPL type connector, which supports both the maximum inrush current from the SBC 302 and the steady-state current.

[0116] The front panel connector connects the system power ON switch interface to the SBC 302 via a PSWIN connection and GND. The PWSIN signal is active low and signals the SBC 302 to power on or off. This signal is preferably momentarily shorted to ground to activate the power-on or power-off sequence, so the power switch can be implemented as a momentarily on single-pole switch. There may also be two LED signals indicating system power status (SUS) and hard disk activity (HD). These signals may be active low and connected to the P3v3 SBC power pins for operation. Two LEDs and two resistors are used, one for each signal, to visually indicate the status of these two signals appropriately. There may also be a GND pin for power and signal return current, which will be connected to the common system ground, and a +3.3V power supply for powering the LEDs as described above. The front audio connector is used for interfacing with the audio amplifier on the carrier card. The audio connection may be pseudo-differential, thus routing to the audio amplifier input via appropriate audio ground.

[0117] The power distribution network can consist of switches and linear regulators, where these switches can be synchronized with the system image clock. For example, a P5v2 SMPS and a P5V0 regulator can be used to power the circuitry on the carrier card. The SMPS output voltage can be set by the differential voltage of the P5v0 linear regulator. The SMPS monitors the amplitude of the P12v0 signal and uses two threshold voltages to determine when to change the state of the power normal signal (PG_P5v2). This signal is used to enable or disable the HV clamping circuitry and disable or enable the HVP and HVM power supplies. Alternatively, an M5v6 SMPS and an M5V0 regulator can also be used to power the circuitry on the carrier card. The SMPS output voltage can be set, for example, by the differential voltage of the M5v0 linear regulator.

[0118] Transmit clamping and enable circuitry can be used to place the transmit power supply into a safe state during system power-down or power-on sequences. This circuitry employs an appropriate timing sequence between the two signals to ensure sufficient dead time. The FPGA preferably implements a break-before-make switching topology. To implement the appropriate power-on and power-off sequence for the HVP and HVM power supplies, an active clamping circuit with an active power enable circuit can be used. These two signals can be hardware-controlled to implement a timing sequence for implementing the break-before-make switching topology. The HV clamping and HV enable circuitry has two operating states: active clamping with power disabled, and clamping disabled with power active. Both states are triggered by the P5v2 SMPS power normal signal, which is the output of the P5v2 SMPS regulator that actively monitors the voltage on the P12v0 power supply using the SMPS UVLO circuitry. A high level on the PG signal or +12V indicates that the P12v0 voltage is higher than the UVLO. 上升The threshold indicates that the P12v0 power supply is fully powered on, and the HVP and HVM power supplies can now be safely powered on as well. A low level or 0V on the PG signal indicates that the P12v0 power supply is below UVLO. 下降 The threshold indicates either a system failure or a system shutdown. In either case, both the HVP and HVM power supplies are disabled and then clamped to ground.

[0119] The SBC USB 2.0 connector can be in the form of a ribbon cable connector, used for interface connection between the SBC 302 and the carrier card. Two sets of HS USB 2.0 signaling are used for communication between the SBC 302 and the touch panel or maintenance port. These interfaces are standard USB 2.0 interfaces, including vBus, Gnd, and a pair of differential signals.

[0120] The USB 3.0 connector can be a standard USB 3.0 compatible connector. The connection between the SBC 302 and the carrier card is achieved by connecting a standard USB 3.0 interface cable between these two connectors. This is the primary communication path for data transfer between the SBC 302 and the ultrasonic motherboard 304.

[0121] The single-board computer 302 implements an operating system 312 that controls the overall operation of the ultrasound system 300 (including system startup and system checks) and optionally controls specific operations of the presentation of outputs (e.g., visual and / or auditory) regarding the detection of markers and / or the location of detected markers.

[0122] The single-board computer 302 executes detector (D) application 313, which controls specific detector-related operations of the ultrasound system 300, for example, via a receive signal processing chain, on the ultrasound probe or transducer array 206 ( Figure 2 The processing of the detected ultrasonic energy is as follows.

[0123] In at least some embodiments, CPU 308 executes a workflow state machine and performs configuration management 314. For example, the workflow or operation of the ultrasound system 300 from startup to processing of received signals and data presentation can be specified as various states of the state machine, which CPU 308 executes. Also, for example, CPU 308 can configure the ultrasound system 300 based on a default set of parameters.

[0124] CPU 308 can also execute logic for handling user feedback management and control 316. For example, CPU 308 can generate a visual representation of the position of a detected marker relative to a visual representation of the anatomical structure and / or a visual representation of the position of the ultrasound probe or transducer (e.g., an anatomical structure captured during an operating mode different from the mode in which the marker was detected (e.g., mode D) (e.g., mode B), wherein the visual representation of the marker's position is superimposed on the representation of the anatomical structure, and vice versa). Also, for example, CPU 308 can generate an auditory representation of the position of the detected marker relative to the position of the ultrasound probe or transducer and / or an auditory representation of the direction of movement of the ultrasound probe or transducer relative to the detected marker in one, two, or even three dimensions (e.g., a beep or other sound, e.g., based on loudness or frequency, corresponding to movement away from and / or toward the marker).

[0125] CPU 308 can also execute logic for handling system settings management and control 318. For example, CPU 308 can manage a set of settings for ultrasound system 300, for example, using a default set of system settings or using system settings based on: i) the type (e.g., brand and model) of the ultrasound probe or transducer communicatively coupled to ultrasound system 300, ii) the type of marker being used, and / or iii) the type of body tissue with the marker implanted (e.g., breast, lung).

[0126] GPU 310 can implement an ultrasonic processing pipeline 320 to process ultrasonic waves generated by an ultrasonic probe or transducer array 206. Figure 2 The received ultrasound signals, which are discussed in more detail in this paper (see, for example, [link to relevant documentation]). Figure 4 (Receive signal processing chain 402). GPU 310 can execute logic for implementing detection metric 322 to detect markers from detected ultrasound, which is discussed in more detail herein (see, for example, see...). Figure 4 (Receive signal processing chain 402). GPU 310 can execute logic for implementing image composition 324 to produce image data that can be presented (e.g., displayed) to a user, which is discussed in more detail herein (see, for example, see...). Figure 4 The scan converter 430 and associated beam geometry 431, as well as associated B-map data 432, image filter stage 434, scan converter 436, image filter stage 440, image merger 442, and image pane 444.

[0127] The ultrasound motherboard 304 can perform local and ultrasound probe control and is used for various image timing events. The ultrasound motherboard 304 may, for example, embody firmware 323. Although the ultrasound motherboard 304 is shown as a processor 325 in the form of an FPGA, the ultrasound motherboard 304 could more preferably employ one or more GPUs to improve operating speed.

[0128] The ultrasound motherboard 304 may include software and firmware stack (e.g., Cypress USB) 326 to implement communication between the ultrasound motherboard 304 and external devices, which may allow communication with attached ultrasound probes or transducer arrays 206. Figure 2 This allows communication and enables programming of the processor 328 (e.g., FPGA or GPU) of the ultrasonic motherboard 304. For example, the ultrasonic motherboard 304 may include one or more communication ports (e.g., two communication ports) providing an interface for communication with external devices. Figure 3 (Not shown in the image). For example, a port can be in the form of a probe port, which is used to interface with an ultrasonic probe and carry ultrasonic transmit (TX) and ultrasonic receive (RX) electrical signals to and from the ultrasonic probe or transducer array 206, respectively. The probe port can have suitable contacts or pins to connect with the ultrasonic probe or transducer array 206 (…). Figure 2 The complementary structure on the communication ground (e.g., electrical ground) interface connection, and / or includes physical coupling features or structures. Optional communication ports, referred to as magnetic resonance ports, may be included to provide synchronous magnetic pulses, as described elsewhere herein.

[0129] The ultrasound motherboard 304 may include a processor 325 (e.g., an FPGA or GPU) which is central for imaging and diagnostic control via an ultrasound probe port and optionally via a magnetic port. While the processor 325 is shown as an FPGA, in some implementations, one or more GPUs may be advantageously employed.

[0130] The processor 325 of the ultrasound motherboard 304 can, for example, implement a scanning state machine 330 to control the ultrasound probe or transducer array 206. Figure 2 The ultrasound motherboard 304's processor 325 can, for example, execute logic for providing front-end chip register access 332. The ultrasound motherboard 304's processor 325 can, for example, perform beamforming 334 on received or returned ultrasound signals, activating transducer array elements in a controlled manner during ultrasound energy reception to form a high-quality ultrasound image dataset of the field of interest. Any of a variety of beamforming methods can be employed.

[0131] Figure 4An exemplary receiving signal processing chain 400 for an ultrasound system according to at least one of the illustrated embodiments is shown. This ultrasound system may be, for example, ultrasound system 204 (…). Figure 2 ) or 300 ( Figure 3 The implementation method of ).

[0132] An ultrasound probe or transducer, typically having multiple individual piezoelectric elements, crystals, or transducers, emits ultrasound pulses, for example, grouped into sets of pulses along each of multiple beam directions (e.g., a set of pulses from each piezoelectric element, crystal, or transducer along the main emission axis of the respective piezoelectric element, crystal, or transducer). The ultrasound probe detects the ultrasound energy, and the receiving section of the ultrasound system performs processing to identify or locate the detected ultrasound energy corresponding to the response of the marker, in order to distinguish it from all other detected ultrasound energies. This processing should balance the accuracy and speed of the calculations. In particular, the processing should be fast enough to be useful in a surgical setting and robust enough to accommodate the movement of ultrasound probes that are typically handheld and can be moved at varying speeds (e.g., velocity and direction) and may even wobble. For example, it is desirable to locate the response from the marker multiple times to improve accuracy. However, this may increase the time spent emitting pulses, receiving responses, and processing the received responses. In at least some embodiments, a marker is considered detected if a response characteristic of the marker is found in a defined plurality (e.g., three (3)) consecutive frames of the captured ultrasound data.

[0133] The ultrasonic energy emitted by the ultrasonic probe or transducer array 206 can advantageously be distributed across the frequency range that the ultrasonic probe or transducer array 206 can generate. For example, each pulse set may include four pulses of different frequencies spanning the frequency range that the ultrasonic probe or transducer array 206 can generate. This can, for example, advantageously improve or increase the persistence of the detectable return signal. The following section discusses... Figure 6 An example is described.

[0134] Composed of an ultrasonic probe or transducer array 206 ( Figure 2The detected ultrasonic energy can be represented by a signal (received signal) 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 non-transitory form on one or more tangible media (e.g., non-volatile memory, rotating storage media (e.g., magnetic hard disk drive, optical disk drive), or solid-state storage media (e.g., solid-state drive (SSD)) or flash memory), which can be executed by one or more processors (e.g., microcontroller, microprocessor, central processing unit (CPU), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), digital signal processor (DSP), and / or graphics processing unit (GPU)). The receive signal processing chain 402 can be executed, for example, via an FPGA, or more preferably by one or more GPUs.

[0135] Specifically, the ultrasonic probe or transducer array 206 ( Figure 2 Signals can be transmitted via cable 404 and communication driver 406 (e.g., USB driver, PCIe driver) and hardware interface 408 (e.g., USB-compatible port or connector, PCIe-compatible port or connector).

[0136] 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., beammaps) RF beam data in an arrangement or format anticipated by the receive signal processing chain 402, for example, by storing signals in a specified format into the frame stream buffer 410. This format or arrangement can be specified, for example, in a storage medium (e.g., non-volatile memory or read-only memory or EEPROM, referred to as the beam SIM 412). It should be noted that, in addition to the components comprising the receive signal processing chain 402, the receive signal chain may also include a cable 404, a communication driver 406, a hardware interface 408, the frame stream buffer 410, and / or the beam SIM 412.

[0137] Therefore, the receive signal processing chain 402 can, for example, begin with a full frame of beamformed RF data dispatched from the frame stream buffer 410 by the frame data manager.

[0138] The receive signal processing chain 402 may optionally implement a DC canceller 414 to eliminate the DC component in the beamformed RF data received from the frame stream buffer 410. The DC canceller 414 (which may also be referred to as a set canceller) may, for example, apply mean cancellation and depth-based gain to remove the average value to make the differences apparent (e.g., via the set canceller).

[0139] The receive signal processing chain 402 may include one or more RF stages 416 to process beamforming RF data, thereby improving the signal-to-noise ratio, for example. RF stages 416 may, for example, implement RF filtering and / or mixing. RF stages 416 may, for example, split the raw RF data. For example, RF stages 416 may separate or split raw RF data representing the response from a marker (pulse set data) from raw RF data representing other types of returns or reflections that may represent reflections from anatomical structures (e.g., non-pulse set data or B data). For example, RF stages 416 may employ one or more RF filters (e.g., finite impulse response (FIR) bandpass filters) to perform such real-time digital signal processing. RF stages 416 may, for example, process multiple RF data streams, such as two pulse set RF data streams and one B RF data stream. For example, RF stages 416 may include multiple mixers that generate RF in-phase or directly quadrature (IQ) signals for various pulse set RF data streams and non-pulse set RF data streams. For example, a mixer can mix two or more pulse sets of data streams (e.g., two streams) with corresponding multiples of the mixing frequency. RF mixing can produce two or more different mixing multiples, which can advantageously address potential "blinding effects" by eliminating ultrasound signals detected by the ultrasound probe that are actually the outgoing transmitted ultrasound signals rather than the returned signals. RF stage 416 can also employ one or more low-pass filters, for example, to remove negative frequencies from the IQ signal. RF stage 416 can also employ one or more notch filters, for example, to filter out the fundamental frequency of the ultrasound.

[0140] The receive signal processing chain 402 may include one or more detector stages 418. Detector stages 418 may demodulate the split raw RF data. Demodulation (also known as detection) removes the carrier signal and reconstructs the signal envelope for each element in the RF data stream (e.g., envelope detection). Therefore, detector stages 418 may, for example, remove the transducer pulse frequency from the data, thereby preventing or reducing ripple. Envelope detection may, for example, demodulate or convert the RF signal back to an amplitude representation.

[0141] Several methods can be used to perform demodulation or envelope detection, such as i) implementing quadrature (IQ) detection, or ii) applying the Hilbert transform. Quadrature (IQ) detection mixes (essentially multiplies) the input signal with in-phase and quadrature-phase sine waves, such that the signal content at that frequency is enhanced while all other content is reduced. This can be implemented in hardware or software. The original signal after IQ detection may still contain ripple (e.g., at twice the carrier frequency), which can be advantageously addressed by low-pass filtering. Applying the Hilbert transform shifts the peak value of the ripple in the RF data by half in time towards the trough. The resulting modified signal can be combined with the original signal, such that one signal fills in the ripple of the other, thereby estimating the envelope amplitude. The result is a good approximation of the pulse energy, thus reducing ripple while maximizing detail.

[0142] The receive signal processing chain 402 may optionally perform log compression (i.e., log compression) 420 on the output from the RF stage 416.

[0143] The receive signal processing chain 402 may optionally perform log compression (i.e., log compression) 422 on the output from the detector stage 418.

[0144] The receiving signal processing chain 402 may include one or more target stages 424 to represent the signal processed by the ultrasonic probe or transducer array 206. Figure 2 The data of the detected ultrasound signals undergoes target or "image" processing. Target level 424 may, for example, perform inter-frame comparisons (referred to herein as sigma mapping) to identify, for example, inter-frame variations or differences in the received ultrasound data. Sigma mapping can maximize the signal-to-noise ratio by, for example, extracting the response of the target (e.g., the return signal from the marker) from the received signal data. Target level 424 may also include target analysis via a target analyzer, for example, employing various metrics (e.g., frame metrics including line density and background noise; region of interest metrics including mean, maximum, variance, aspect ratio or dimensionality and / or area; region of interest relation metrics including relative location of the ROI) to rank various targets and / or select targets based on these metrics and / or the ranking of targets. The target analyzer ranks the blob based on specified target characterization criteria (e.g., frame metrics, region of interest metrics, region of interest relation metrics, and / or shape of the marker's ultrasound response). Each target characterization criterion may be assigned a corresponding weight based on its importance in characterizing the target. The ordering of each of multiple targets relative to each other can be used to detect the presence or absence of response signals from tissue markers.

[0145] The receive signal processing chain 402 may include one or more focus mixers 426 (also referred to as focus combiners) operable for performing focus combining. The focus mixer 426 acquires data from multiple depths of focus from a previous stage and flattens the data. For example, the focus mixer 426 may acquire data from, for example, two depths of focus (e.g., 48 × 2640 × 2 data points) and produce a smaller dataset (e.g., 48 × 2640 data points). Focus combining combines the focus sets. Focus combining may, for example, acquire a dataset from a previous stage (e.g., 48 × 2640 × 2 data points) and flatten the data to create a smaller flattened dataset (e.g., 48 × 2640 data points). This facilitates alternating focus splitting by replicating data from depth sets in at least one embodiment. Other embodiments may be able to omit this operation and / or employ other methods. The focus mixer 426 may combine B-focus beams and allow detectors to cross into the B-stream.

[0146] The receive signal processing chain 402 can perform one or more decimations 428 to reduce the size of the dataset. For example, the receive signal processing chain 402 can perform detector decimation (e.g., detector decimation and B-sample decimation) on samples in the beam.

[0147] The receive signal processing chain 402 may include one or more scan converters 430, 436 and associated beam geometry 431, as well as associated B-mode image data 432 and associated color map data 438. The scan converters 430, 436 output scan conversions (e.g., D-mode scan conversion, B-mode scan conversion) of the B-mode image data and the detected or “D”-mode image data.

[0148] The receive signal processing chain 402 may include one or more image filter stages 434, 440 to filter various components of an image or image data (e.g., B-mode image data; D-mode image data).

[0149] The receiving signal processing chain 402 may include one or more image mergers 442 operable for merging image data (e.g., B-mode image data and D-mode image data).

[0150] The receiving signal processing chain 402 may include one or more image panes 444 operable for presenting merged image data.

[0151] The receiving signal chain 400 of the ultrasound system may include, for example, a system interface (Vdevice model) 446 for reading registers and tables.

[0152] The receiving signal chain 400 of the ultrasound system may include a graphics interface (pipeline DeviceVM view model) 448, which interfaces between, for example, a graphics engine (C++ CLR interface) 450 and a rendering framework (e.g., WPF for Windows applications) 452 to render images via a display screen and / or display driver (view) 454, for example via a markup language layer (XAML, UI, DEF) 456. The pipeline DeviceVM view model 448 reads and writes external files (e.g., configuration or rendering files 458) and external libraries (e.g., scripting 460).

[0153] Figure 5 A high-level block diagram of a receive signal processing chain 500 according to at least one of the illustrated embodiments is shown. This receive signal processing chain is operable to process received ultrasound energy to at least detect the presence or absence of a response from a marker (e.g., a tissue marker), and to provide visual and / or auditory indications of the marker's presence and / or location. The receive signal processing chain 500 may, for example, consist of a receiving segment 210 of an ultrasound system 204. Figure 2 ) Implementation.

[0154] According to at least one of the illustrated embodiments, the receive signal processing chain 500 can be implemented in hardware, software, and / or firmware. The hardware may include, for example, an analog-to-digital converter (ADC); a processor-based computer system employing one or more processors and memory or other non-transitory storage media; and / or one or more of the following: a field-programmable gate array (FPGA), a graphics processing unit (GPU), and / or an application-specific integrated circuit (ASIC), which may be implemented, for example, on one or more cards or boards. The processor may include, for example, one or more of the following: a microprocessor, a microcontroller, a central processing unit (CPU), a digital signal processor (DSP), a graphics processing unit (GPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), and / or a programmable logic controller (PLC), etc. The memory may include, for example, one or more of the following: read-only memory (ROM), random access memory (RAM), EEPROM, flash memory, and / or registers, etc. Other non-transitory storage media may include, for example, one or more of the following: a magnetic disk and associated disk drive, an optical disk and associated optical disk drive, and / or a solid-state drive (SSD), etc.

[0155] Although not shown, it can be inferred from the ultrasound probe or transducer array 206 ( Figure 2The system receives an analog transducer signal. The received analog transducer signal has a center frequency, for example, 2.76 MHz. Optionally, the received analog transducer signal is digitized, for example, via an analog-to-digital converter (not shown).

[0156] The received signal processing chain 500 described herein can advantageously process multiple samples (e.g., four spots) in parallel, and sort samples with properties indicating that the corresponding sample may represent a response from a marker for later analysis, as described below. Each target characterization criterion can be assigned a corresponding weight based on its importance in characterizing the target. Therefore, instead of identifying a single sample as a response during detection, the method described herein can identify a larger number of samples as potentially representing a response from a marker and intelligently sort these samples based on defined target characterization criteria for later analysis, thereby improving stability, reliability, and consistency.

[0157] At 502, the signal processing chain 500 receives the signal (e.g., the receiving section 210 of the ultrasound system 204). Figure 2 It receives and processes RF data.

[0158] At 504, the signal processing chain 500 receives the signal (e.g., the receiving section 210 of the ultrasound system 204). Figure 2 Envelope data is generated. For example, envelope detection can be performed to demodulate RF data. Envelope detection can be performed, for example, on two different multiples of the corresponding transmit frequency of each pulse in the pulse set, or on two different multiples of a defined frequency (e.g., the average transmit frequency of the pulses in the pulse set, or a default frequency).

[0159] At 506, the signal processing chain 500 receives the signal (e.g., the receiving section 210 of the ultrasound system 204). Figure 2 Focus fusion is performed. For example, an ultrasound system may employ or apply aggregate focus fusion to fuse transmit (tx) focus patterns, for example, for data generated by envelope detection. For example, once the envelope is detected, the receive signal processing chain 500 of the ultrasound system 204 fuses alternating depths of focus (e.g., a first depth of focus and a second depth of focus) at the transition depth. Adding two or more depths can eliminate some transmit noise. In the current embodiment, two depths of focus are used because including additional depths of focus would significantly increase the time involved in transmitting, detecting, and processing ultrasound, and thus impose undesirable limitations on hand and ultrasound probe movement. Processing beyond this level can be performed laterally for the same depth positioning.

[0160] At 508, the signal processing chain 500 receives the signal (e.g., the receiving section 210 of the ultrasound system 204). Figure 2The receiver signal processing chain 500 generates one or more brightness maps that indicate the intensity, strength, or loudness levels (e.g., amplitude dB) of a series of returned signals from a set of image data. The brightness maps can be generated, for example, using ensemble averaging or ensemble mean.

[0161] At 510, the receiving signal processing chain 500 (e.g., the receiving section 210 of the ultrasound system 204) is located. Figure 2 Generate one or more sigma plots. A sigma plot represents the inter-frame differences in image data. A sigma plot can represent ensemble differences. It can also represent the lateral standard deviation (e.g., 3:N angular width). It can also be squared, for example, to enhance the dynamic range of the variant response.

[0162] At 512, the receiving signal processing chain 500 (e.g., the receiving section 210 of the ultrasound system 204) is located. Figure 2 The received signal processing chain 500 generates one or more segmentation input maps. The received signal processing chain 500 may, for example, employ ensemble discriminant and / or convolution (e.g., 0.25, 0.5, 0.25) to segment the image data. The segmentation input map may, for example, represent radii and / or blobs (with consecutive pixels or voxels indicating detected returned values). The segmentation input map may represent ensemble discriminant. This may employ convolution (e.g., 0.25, 0.5, 0.25).

[0163] Optionally, at 514, a receiving signal processing chain 500 (e.g., the receiving section 210 of an ultrasound system) is included. Figure 2 Log compression is applied to the luminance map, sigma map, and segmentation input map.

[0164] At 516, the receiving signal processing chain 500 (e.g., the receiving section 210 of the ultrasound system 204) is located. Figure 2 Amplitude segmentation is performed. The received signal processing chain 500 can, for example, segment the "image" data into radii and / or spots (with consecutive pixels or voxels indicating the detected amplitude values). Amplitude segmentation can advantageously reduce the data, for example, by using a histogram (e.g., 4096 bins).

[0165] For example, to perform amplitude segmentation, the receive signal processing chain 500 can advantageously perform K-means clustering (e.g., by amplitude). For example, the receive signal processing chain 500 can advantageously employ multiple centroids (e.g., three centroids: centroid 0: non-zero mean; centroid 1: non-zero mean + (0.25)). (Value range); and centroid 2: non-zero mean + (0.50) (Value range). Also, for example, the receive signal processing chain 500 can advantageously employ various periods (e.g., 5 to 20 periods, such as 11 periods, ideally until convergence). Also, for example, the receive signal processing chain 500 can advantageously attempt to minimize the amplitude difference with respect to the centroid.

[0166] For example, in order to perform amplitude segmentation, the received signal processing chain 500 can advantageously perform assignment mapping or generate an assignment map. For example, each sample can be assigned to one of the centroids (e.g., centroid 0, centroid 1, or centroid 2).

[0167] For example, to perform amplitude segmentation, the receive signal processing chain 500 can advantageously perform assignment graph smoothing. For instance, the receive signal processing chain 500 can perform assignment graph smoothing in two vertical directions (referred to as the vertical and horizontal directions for convenience) of the dataset. The receive signal processing chain 500 can perform vertical assignment graph smoothing, for example, via convolution (e.g., height 12, center weight 0.25, all other weights 0.75 / (height-1)). The receive signal processing chain 500 can perform horizontal assignment graph 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)).

[0168] For example, to perform amplitude segmentation, the received signal processing chain 500 can advantageously generate and / or employ a segmentation mask. For instance, the received signal processing chain 500 can generate and / or employ a segmentation mask in which all samples with values ​​less than 1 are assigned a Boolean value of 0 or false, and all samples with values ​​equal to or greater than 1 are assigned a Boolean value of 1 or true. This can advantageously reduce data and improve computational efficiency.

[0169] At 518, the receiving signal processing chain 500 (e.g., the receiving section 210 of the ultrasound system 204) is located. Figure 2 The receiver signal processing chain 500 can find up to N (e.g., N = 4) consecutive spots, for example, by sorting them by size in a segmentation mask.

[0170] At 520, the receiving signal processing chain 500 (e.g., the receiving section 210 of the ultrasound system 204) is located. Figure 2The receive signal processing chain 500 performs target analysis. It may, for example, determine (e.g., calculate) one or more, or even all, of the following: frame metrics (e.g., line density; noise floor); region of interest metrics (e.g., mean, maximum, variance, aspect ratio, area); and / or region of interest relation metrics (e.g., relative location of the ROI). The receive signal processing chain 500 may, for example, use the determined frame metrics, region of interest metrics, and / or region of interest relation metrics to rank various targets (e.g., spots or ROIs) and / or select targets with the best or highest ranking.

[0171] Figure 6 It is a graph showing a waveform 600 for generating a set of emission pulses to emit an ultrasonic beam, thereby producing a response from a marker, according to at least one of the illustrated embodiments.

[0172] It should be noted that the ultrasound system can employ two or more operating modes. In one operating mode, known as detector (D) mode, the ultrasound system causes the ultrasound probe or transducer array to emit ultrasound energy designed to elicit a response from a marker. The ultrasound energy designed to elicit a response from a marker is referred to herein as the target beam. In another optional operating mode, the ultrasound system causes the ultrasound probe or transducer array to emit ultrasound energy using conventional ultrasound B mode for imaging anatomical structures. B mode operation is independent of D mode operation. In at least some embodiments, B mode operation is fixed, for example, at approximately 6 MHz.

[0173] In detector mode (D-mode) operation, the ultrasonic energy emitted or output by the probe is distributed over the probe's effective frequency range (the range of frequencies the probe can emit and detect). For example, a transducer probe or transducer array can be driven to emit pulse sets (e.g., two or more pulses per set, such as a pulse set of four to six pulses), where the characteristics (e.g., frequency, period) of each pulse in a given pulse set are different from each other. This can advantageously be far removed from the fundamental frequency, as the fundamental frequency may constitute a noise source (i.e., a noise source). For example, while this described emission model distributes energy over a relatively wide range (2 MHz to 6 MHz), the receive signal processing chain can sample the relatively quiet portion of the detected or returned ultrasound (e.g., 2.75 MHz) to assess whether it contains a response from a marker. Thus, in addition to extending the detectable response in time, this can also improve sensitivity. This broadband transmission method allows for a significant reduction in the voltage of the transmitted beam (e.g., down to around 65 V), which in itself can advantageously reduce unwanted background noise and advantageously reduce the thermal load on the ultrasonic probe or ultrasonic transducer array.

[0174] like Figure 6 The illustrated method uses a sine wave to modulate the frequency between four pulses constituting a pulse set, for example, where the timing is centered at 4 MHz. In at least some embodiments, each pulse differs from the preceding pulse in the form of frequency or period. In at least some embodiments, the pulses in the set begin at a relatively low frequency and progress to a relatively high frequency (e.g., from 2 MHz to 6 MHz). This can be implemented, for example, using a table (e.g., a wavetable) to specify differences in a given characteristic of corresponding pulses in the pulse set or otherwise alter the pulses in a given pulse set. Alternatively or additionally, this can be implemented using a pseudo-random number generator to change the characteristics of the pulses within a defined range. The transmitted (TX) waveform is... Figure 6 The composite waveform is shown at the bottom.

[0175] Figure 7 This is a flowchart illustrating an operation method 700 of a receive signal processing chain 500 for performing initial processing on raw RF data received from an ultrasonic probe or transducer array, according to at least one of the illustrated embodiments. The receive signal processing chain 500 may, for example, consist of the receiving section 210 of the ultrasonic system 204 (…). Figure 2 ) Implementation.

[0176] At 702, the receiving signal processing chain 500 receives the incoming frame of the received raw RF data (e.g., raw sample data of the incoming frame, such as 64x ADC data channels, 64 channels of 14-bit signed data, at a rate of 40 megasamples per second (Msps), originally 32 msps). The receiving section 210 can, for example, receive the raw sample data of the incoming frame received via an ultrasound probe or transducer.

[0177] At 704, the receive signal processing chain 500 uses one or more low-pass filters to low-pass filter the received raw RF data (e.g., 16-bit signed integer samples). For example, the receive signal processing chain 500 low-pass filters the received RF data (e.g., 40 Msps, originally 32 msps) (e.g., 10 MHz low-pass filter).

[0178] At 706, the receive signal processing chain 500 buffers the filtered received raw RF data (e.g., a 16-bit signed integer sample) in one or more buffers for final transmission.

[0179] At 708, the receive signal processing chain 500 performs raw channel interpolation (e.g., upsampling 2x, rate 80 Msps) on the received raw RF data (e.g., 14-bit signed integer samples).

[0180] At 710, the receive signal processing chain 500 then performs low-pass filtering (e.g., 10 MHz FIR low-pass filtering) on ​​the output of the original channel interpolation (e.g., 8 Msps, 14-bit signed integer samples).

[0181] At 712, the receive signal processing chain 500 performs aperture growth on the low-pass filtered output of the raw channel interpolation and the received raw RF data (received at 702) to select which beams are used for beamforming. The output of the aperture growth can be, for example, 80 / 40 Msps 20-bit, 1-beam.

[0182] At 714, the receive signal processing chain 500 performs apodization on the aperture growth output to weight the effect of each receive (RX) stream according to the steering angle and focus. The apodized output can be, for example, an 80 / 40 Msps 20-bit, 1-beam output.

[0183] At 716, the receive signal processing chain 500 performs receive (RX) beamforming on the apodized output. This can advantageously delay and combine the analog-to-digital (ADC) streams to produce a corresponding single output beam. The beamformed output can be, for example, an 80 / 40 Msps 20-bit, 1-beam output.

[0184] At 718, the receive signal processing chain 500 performs digital time gain compensation (TGC) on the beamforming output to perform depth-dependent gain. The output of the digital TGC may include, for example, 80 Msps, 16-bit, 1-beam and 40 Msps, 16-bit, 1-beam. At 706, one output of the digital TGC may be buffered (e.g., 40 Msps, 16-bit, 1-beam).

[0185] At 720, the receive signal processing chain 500 decimates another output of the digital TGC (e.g., 80 Msps 16-bit, 1 beam). For example, the receive signal processing chain 500 can perform 2x decimation, which advantageously further reduces the data (e.g., 40 Msps 16-bit, 1 beam) and improves computational efficiency.

[0186] At 722, the receive signal processing chain 500 performs low-pass filtering (e.g., 15 MHz low-pass) on the decimated output via one or more low-pass filters. The low-pass filtered output can be 40 Msps 16-bit signed data, 1 beam.

[0187] At position 706, the output of the low-pass filter buffered by the 500-buffered signal processing chain is received.

[0188] At 724, the receive signal processing chain 500 provides buffered data (e.g., 40 Msps 16-bit, 1 beam) for further processing by the receive signal processing chain 500. The receive signal processing chain 500 may provide the buffered data, for example, via a Universal Serial Bus (USB) connection or link.

[0189] Figure 8A and Figure 8B This is a flowchart illustrating an operation method 800 of a received signal processing chain 500 according to at least one of the illustrated embodiments.

[0190] Method 800 can be implemented as part of a processor-based algorithm, for example, executed by one or more GPUs, and is therefore referred to herein as GPU computation processing 801. GPU computation processing 801 can implement RF demodulation and object detection (referred to herein as GPU RF demodulation and object detection 801a), and can also implement pixel image processing (referred to herein as GPU pixel image processing 801b).

[0191] At 802, the receive signal processing chain 500 performs RF demodulation (e.g., GPU RF demodulation) on the incoming frames of received raw RF data (e.g., raw sample data of the incoming frames, such as 64x ADC data channels). RF demodulation can employ multiple stages. The receive section 210 can, for example, receive the raw sample data of the incoming frames received via an ultrasound probe or transducer. Then, method 800 proceeds along two parallel paths, one processing the received B-mode ultrasound signal and the other processing the received D-mode ultrasound signal, and then combines them again (at image stream mixing 810).

[0192] Along one of these two parallel paths, the GPU's R-Theta block 804 processes the received B-mode ultrasound signal as part of the received signal processing chain 500. The received B-mode ultrasound signal is provided as the output of the GPU RF demodulation 802. This may include performing R-Theta filtering 804a on the received B-mode ultrasound signal. In some implementations, R-Theta filtering 804a may include bilateral filtering of the B-mode data (B-bilateral filtering), for example, smoothing the R-Theta filter using an N×N kernel.

[0193] At 806, the receive signal processing chain 500 uses the GPU to perform a scan conversion (B scan conversion) on the R-Theta filtered B image frame data.

[0194] At 808, the receive signal processing chain 500 uses the GPU to perform image persistence (B persistence) on the scanned and converted B image frame data, and then passes the image persistence to the image stream mixer 810.

[0195] Along another of these two parallel paths, a D-sigma mapping block 812 of the processor (e.g., GPU) performs sigma mapping on the D-ultrasound signal as part of the receive signal processing chain 500. This can take multiple stages. The D-ultrasound signal is provided as the output of the GPU RF demodulation 802. This can include generating a sigma map (referred to herein as GPU RF sigma map 812a). The sigma map represents the inter-frame variations of the D-ultrasound image data. Although the term "image" is used herein, D-ultrasound image data may reflect responses from markers (e.g., tissue markers) and may not reflect responses from anatomical structures or images of anatomical structures.

[0196] The D-detection block 814 of the processor (e.g., GPU) uses a sigma map (e.g., RF sigma map 812a) to perform RF detection as part of the received signal processing chain 500. The sigma map represents or otherwise indicates inter-frame differences in image data (e.g., detector image data). This can also be done at multiple levels. This can include performing RF detection using the GPU, and is therefore referred to herein as GPU RF detection 814a.

[0197] The D target determination block 816 of the processor (e.g., GPU) performs target determination using the output of the D detection block 814 as part of the received signal processing chain 500. This can also be performed in multiple stages. Target determination may include processing pixels or voxels in image data to identify contiguous regions or areas (e.g., blobs, regions of interest) and / or evaluating or analyzing such contiguous regions or areas as potential targets. This may include performing target determination using the GPU, and is therefore referred to herein as GPU target determination 816a.

[0198] The D display block 818 of the processor (e.g., GPU) performs the target display or rendering as part of the received signal processing chain 500. This can also take multiple stages. This could include using the GPU to perform the target display, and is therefore referred to herein as GPU target display 818a.

[0199] At 820, the receive signal processing chain 500 uses a GPU to perform D-scan conversion as part of the receive signal processing chain 500, for example, to perform scan conversion on R-theta frame data.

[0200] At 822, the receive signal processing chain 500 employs a GPU to optionally perform D-final smoothing as part of the receive signal processing chain 500. D-final smoothing may, for example, include performing a 3×3 rectangular window filter on the D image.

[0201] 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.

[0202] Optionally, at 830, the receive signal processing chain 500 employs a GPU to perform image overlay as part of the receive signal processing chain 500, thereby providing image overlay information to the image stream mixer 810. Image overlay can overlay labels, scale marks, etc., onto an image.

[0203] At 810, the image stream mixer combines the processed B-image data, the processed D-image data, and optional image overlay 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 two processing paths, one for processing the B-data and the other for processing the D-data. Thus, a resulting composite or overlay image can be generated, where the B-data represents anatomical structures and the D-data represents the response of markers to ultrasound emitted by the ultrasound probe (e.g., artifacts).

[0204] At 826, the receive signal processing chain 500 uses a GPU to send the resulting composite or overlaid image to a display as part of the receive signal processing chain 500.

[0205] At 828, the receive signal processing chain 500 employs a GPU to optionally save or store the composite or overlay image 830 to a non-transitory storage medium (e.g., flash memory, hard disk drive, RAM) as part of the receive signal processing chain 500.

[0206] Figure 9 This is a flowchart illustrating an operation method 900 of a receive signal processing chain 500 for performing GPU RF demodulation processing on raw RF data received from an ultrasound probe or transducer array, according to at least one of the illustrated embodiments. The receive signal processing chain 500 may, for example, consist of the receiving section 210 of the ultrasound system 204 (… Figure 2 ) Implementation.

[0207] At 902, the receiving signal processing chain 500 of the ultrasound system 204 performs beamforming on the incoming frames of the received RF data (e.g., raw sample data of the incoming frames). The receiving section 210 can, for example, process the raw sample data of the incoming frames received via an ultrasound probe or transducer.

[0208] At 904, the receiving signal processing chain 500 of the ultrasound system 204 performs beam mapping, time gain compensation (TGC), and splits the incoming beam into a specified or otherwise defined format. The receiving signal processing chain 500 may, for example, map the incoming beam to a specified format, apply TGC, and then split the received ultrasound signal into a B-beam, a D-path 1 beam, and a D-path 2 beam for subsequent processing, where the letter "D" represents the detector.

[0209] The receiving signal processing chain 500 of the ultrasound system 204 can perform RF splitting, for example, by separating non-converging beams (e.g., beams without a specified pulse mode) from convergent beams (e.g., beams with a specified pulse mode), and generate multiple sets of RF data, such as multiple sets of convergent beam RF data and one set of non-converging beam RF data. The output may, for example, include two sets of convergent beam RF data (referred to as D-beampath 1 and D-beampath 2) and one set of non-converging beam RF data (referred to as the B-beam). The multiple sets of convergent beam RF data will primarily represent the response from a marker (e.g., resonance or beat frequency response or artifact), while the set of non-converging beam RF data may primarily represent the structure (e.g., reflections from anatomical structures). Although the RF splitter is shown as having three branches providing two sets of convergent beam RF data and one set of non-converging beam RF data, in other embodiments, the RF splitter can be implemented with a different number of branches. This can advantageously separate the B data from a minimum defined number (e.g., four) of convergent beams. In some instances, this can be implemented or referred to as RF detector filtering, for example, when the RF detector filter is enabled. The receive signal processing chain 500 of the ultrasound system 204 can, for example, apply an FIR bandpass filter to separate the cohesive beam (e.g., the beam with a specified pulse pattern) from the non-cohesive beam (the beam lacking the specified pulse pattern).

[0210] The output data from the RF split is processed by three parts of the signal chain. These three parts of the signal chain consist of sets of operations that are generally parallel to each other, performed on two sets of data, including pulse set response data from the marker (e.g., resonance or beat response or artifact) and B data (i.e., generated by B-mode ultrasound imaging). The operations of the generally parallel sets of operations are indicated below by a common three-digit reference numeral followed by the lowercase letters “a”, “b”, and “c”, respectively. Thus, the receive signal processing chain 500 can be processed along three paths: parallel i) B beam, ii) D path 1 beam, and iii) D path 2 beam. The B beam can be processed along one path, while the D path 1 and D path 2 beams can be processed along a pair of parallel paths, which are merged at the target detection processing 917 (discussed below).

[0211] At locations 910a, 910b, and 901c, the receiving 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 generate 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 produce two or more different multiples of the mixing frequency. This can advantageously address the potential "blinding effect" of the emitted ultrasound energy and / or improve the ability to distinguish which signals correspond to the response of a marker.

[0212] At locations 912a, 912b, and 912c, the receiving signal processing chain 500 of the ultrasound system 204 may optionally perform low-pass filtering via low-pass filters (D low-pass filter 1, D low-pass filter 2, and B low-pass filter 1, respectively). This can, for example, remove negative frequencies from the IQ signal.

[0213] At locations 914a, 914b, and 914c, the receiving signal processing chain 500 of the ultrasound system 204 demodulates the low-pass filtered RF IQ signal, for example, by performing envelope detection (D-envelope detection 1, D-envelope detection 2, and B-envelope detection, respectively). This advantageously removes the carrier signal and reconstructs the signal envelope, for example, converting the IQ signal back to amplitude representation.

[0214] For example Figure 9 As indicated, the signal processing chain 500 of the ultrasound system 204 may further include performing sample extraction on the data from the two D-path branches (referred to as DT sample extraction 1 915a and DT sample extraction 2 915b, respectively) and performing sample extraction on the data from the B-path (referred to as B sample extraction 915c). This can, for example, reduce the sampling rate or sample count (e.g., N = 4) and potentially prevent aliasing.

[0215] Along the B path, the signal processing chain 500 of the ultrasound system 204 may further include performing Blog compression on the B data at 916, for example, to compress the data range to a desired range (e.g., 0 to 255). At 930, the result can be provided to the focus mixer.

[0216] As described above, the D path 1 and D path 2 processing chains can be merged at the target detection processing 917. In particular, the outputs of the extractions (DT sample extraction 1 915a, DT sample extraction 2 915b) are provided to the target detection processing 917 of the signal processing chain 500.

[0217] Target detection processing 917 may include a sigma mapping processing chain 918 to perform sigma mapping on the D-envelope detection 1 and the sampling results of the D-envelope detection 1. The sigma mapping maps the differences between image data frames. The sigma mapping processing chain 918 may include multiple stages. Target detection processing 917 may further include performing region of interest (ROI) detection at 920 using the sigma map generated by the sigma mapping chain 918. ROI detection 920 may include multiple stages. ROI detection 920 detects ROIs (e.g., contiguous regions or areas (e.g., blobs, regions of interest)) in the image data. Target detection processing 917 may further include performing target finding and display at 921. Target finding and display 921 evaluates the detected ROIs to identify or select which ROIs constitute targets. Refer to the following additional figures (e.g., Figure 11 The document provides a more detailed explanation of the target discovery and display at Sigma Mapping Chain 918, Target or ROI Detection 920, and 921.

[0218] At position 924, the target lookup and display of the output of position 921 are provided for D-scan conversion.

[0219] The output of Target Find and Display 921 is also provided to Focus Mixer 930, which performs focus mixing on the output from Target Find and Display 921 and the output from B log Compression 916 to combine the B focus beam and allow the detector (D) beam to cross into the B data stream.

[0220] At 932, the B-scan converter of the receiving signal processing chain 500 performs B-scan conversion on the output from the focus mixer 930, for example, to produce a scan conversion suitable for visual presentation.

[0221] Figure 10 This is a flowchart illustrating an operation method 1000 of a receive signal processing chain 500 for implementing a GPU RF target sigma mapping level according to at least one of the illustrated embodiments. The receive signal processing chain 500 may, for example, consist of the receiving segment 210 of an ultrasound system 204 ( Figure 2 ) Implementation.

[0222] Along one path, the receiving signal processing chain 500 of the ultrasound system 204 performs DT sample extraction 1 at 1002, for example to reduce the sampling rate or sample count (e.g., N = 4).

[0223] At 1004, the receiving signal processing chain 500 of the ultrasound system 204 performs ensemble focus fusion (ensemble focus fusion 1) on the output of DT sample extraction 1 to fused transmit (TX) focus mode.

[0224] At position 1006, the receiving signal processing chain 500 of the ultrasound system 204 determines or calculates the sum of differences in the outputs of the ensemble focus fusion. This can, for example, reduce two beams in the ensemble to one beam by taking the absolute difference at each position in the beam. This operation helps to extract the temporal differences in the RF data.

[0225] At 1008, the receiving signal processing chain 500 of the ultrasound system 204 determines the lateral standard deviation (also known as the cross-beam standard deviation) based on the sum of these differences; for example, it calculates the cross-beam standard deviation. For example, the receiving section 210 calculates the standard deviations of multiple beams (e.g., 3 beams) around the target or "current" beam. The window size (e.g., 3) is set by the environment variable VPM_LATERAL_WINDOW. This operation helps extract spatial differences in the lateral plane.

[0226] At 1010, the received signal processing chain 500 of the ultrasound system 204 multiplies, cancels, and compresses the data (e.g., log compression). In some embodiments, the lateral canceller may, for example, subtract the mean of other beams from each set sample. For example, the lateral canceller subtracts the mean of surrounding beams (e.g., four surrounding beams) from the active or "current" beam (i.e., the beam currently being processed). The lateral canceller has a window size set by an environment variable (e.g., a window size of 5). The ultrasound system may optionally employ or apply frame cancellation, such as performing inter-frame cancellation and smoothing. Alternatively, frame cancellation may be disabled, allowing the data to pass through the operation without alteration.

[0227] At 1012, the receiving signal processing chain 500 of the ultrasound system 204 creates a forced target (forced target 1) in the output, resulting in an unmasked target sigma source. The resulting target sigma source is provided to the sigma detector output 1014, which is used as a source of target sigma data, as discussed below. The resulting target sigma source is also provided to generate a luminance mask 1016, which can be used as described below. The generation of the luminance mask 1016 can reduce incoming sigma at high luminance levels.

[0228] Along another path, the receiving signal processing chain 500 of the ultrasound system 204 performs DT sample extraction 2 at 1018, for example to reduce the sampling rate or sample count (e.g., N = 4).

[0229] At 1020, the receiving signal processing chain 500 of the ultrasound system 204 performs ensemble focus fusion (ensemble focus fusion 2) on the output of DT sample extraction 2, for example in fused emission (TX) focus mode. The output of ensemble focus fusion 2 is processed by two processing chains (i.e., luminance processing chain 1022 and amplitude segmentation chain 1024). Luminance processing chain 1022 will be discussed first, followed by amplitude segmentation chain 1024.

[0230] As part of the luminance processing chain 1022, the receive signal processing chain 500 of the ultrasound system 204 determines the ensemble average at 1026, for example, the average of the output DT ensemble. Then, at 1026, the receive signal processing chain 500 performs logarithmic compression (DT LOGCOMPRESS) on the data. Logarithmic compression can advantageously map the data to a specified range (e.g., a range of 0 to 235, where 235 equals 160 dB). In this example, the step size is 0.681 dB per step. Log compression (DT LOGCOMPRESS) is used for the generation of the luminance mask 1016 described above.

[0231] The luminance processing chain 1022 then determines a beam histogram (DT beam histogram) at 1028 by the receive signal processing chain 500, for example, generating a per-beam histogram. The beam histogram (e.g., average, peak, maximum) can be used to inform dynamic threshold / flooding sector assessment during implementation. Then, at 1030, the receive signal processing chain 500 determines a frame histogram (DT frame histogram). The frame histogram (e.g., average, peak, maximum) can be used to inform dynamic threshold / flooding sector assessment during implementation. The receive signal processing chain 500 then estimates the density (DT density estimator) at 1032, for example, generating frame statistics and density estimation output. Finally, as part of the luminance processing chain 1022, the receive signal processing chain 500 provides a histogram output 1038, for example, as a source for histogram display.

[0232] As part of amplitude segmentation chain 1024, the receive signal processing chain 500 of the ultrasound system 204 determines the sum of differences at 1040. Then, the receive signal processing chain 500 performs deinterleaving at 1042, for example, fusion of adjacent DT beams. The receive signal processing chain 500 then performs log compression at 1044, thereby generating a segmentation mask source. Finally, as part of amplitude segmentation processing chain 1024, the receive signal processing chain 500 provides amplitude segmentation output 1046 (see [link to documentation on amplitude segmentation output 1046]). Figure 12 ), that is, the source used for amplitude segmentation (discussed below).

[0233] Figure 11 This is a flowchart illustrating an operation method 1100 of a receive signal processing chain 500 for performing the search or detection of a region of interest (ROI) according to at least one of the illustrated embodiments. The receive signal processing chain 500 may, for example, consist of the receiving segment 210 of an ultrasound system 204 ( Figure 2 ) Implementation.

[0234] The receiving signal processing chain 500 of the ultrasound system 204 receives the amplitude segmentation (AS) sigma source (AS sigma source) 1102, that is, the amplitude segmentation processing chain sigma data.

[0235] The received signal processing chain 500 of the ultrasound system 204 executes an amplitude segmentation processing chain 1104. This may include executing an amplitude segmentation sequence 1106, which itself may employ multiple stages.

[0236] In some implementations, the receive signal processing chain 500 may optionally perform sigma threshold culling to filter out any out-of-bounds regions. The receive signal processing chain 500 may remove regions, for example, based on a sigma threshold. For instance, the receive signal processing chain 500 checks for positions in the distance data where the left, right, top, and bottom distances are zero and sets culling codes accordingly. The receive signal processing chain 500 then checks for positions in the sigma data whose values ​​are less than a target minimum sigma threshold and sets culling codes accordingly. The culling code may be a Boolean flag or value indicating a binary state of culling or not culling.

[0237] In some implementations, the receive signal processing chain 500 may optionally perform region culling. Region culling may be based on sigma content and B content from the B processing chain and from B log compression to remove regions. For example, the receive signal processing chain 500 checks for locations in the distance data where the join width is too wide and sets a culling code accordingly. Also, for example, the receive signal processing chain 500 checks for locations in the B data where the value exceeds a B threshold and sets a culling code accordingly.

[0238] In some implementations, the receive signal processing chain 500 optionally performs orphan cull. Orphan cull can remove blobby orphans created in a previous stage. For example, the receive signal processing chain 500 searches within the region of interest (ROI) associated with the current active position to find positions previously culled for being too wide, and if any such positions are found, a cull code is set accordingly. The ROI is defined by the left, right, top, and bottom distances of the active position. The receive signal processing chain 500 searches for smaller ROIs and tracks the number of positions culled for being below a sigma threshold. Smaller ROIs are defined by subranges of the left, right, top, and bottom distances of the current active position. If the ratio of culled positions to valid positions exceeds a threshold, a cull code is set.

[0239] In some implementations, the receive signal processing chain 500 may optionally refine the distance calculation, for example, by recalculating the distance if no rejection value is found. For example, the receive segment 210 may step from the active position in the left, right, up, and down directions, counting the steps in each direction until a rejection value is reached. These counts are saved as new left, right, up, and down distances for the active position. The receive signal processing chain 500 then evaluates the rejected areas, for example, filtering out out-of-bounds areas. The receive signal processing chain 500 may, for example, check whether the width (sum of left and right distances) and height (sum of up and down distances) of the active position meet a minimum size requirement. The minimum size requirement may, for example, be defined by a set of registers, referred to herein as the DT target minimum width and DT target minimum height. If the minimum size requirement is not met, the receive signal processing chain 500 sets a rejection code accordingly. The receive signal processing chain 500 may then optionally refine the distance again, for example, by recalculating the distance again if no rejection value is found. The received signal processing chain 500 can, for example, step from the active position in the left, right, up, and down directions, and count the number of steps in each direction until a rejection value is reached. These counts will be saved as new left, right, up, and down distances of the active position.

[0240] In some implementations, the receive signal processing chain 500 optionally performs a first pass of centroid reduction. The receive signal processing chain 500 may, for example, reduce the distance set to the highest match within a specified range. For example, the receive signal processing chain 500 may calculate the width ratio, height ratio, and area / distance product for each valid centroid. The receive signal processing chain 500 may recursively compare these values ​​in pairs until a single best fit is reached. 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 may, for example, reduce the set again to the highest match within a specified range.

[0241] The receive signal processing chain 500 of the ultrasound system 204 generates or accesses a connectivity map 1108. The connectivity map 1108 can represent or indicate pixels or voxels that can form continuous regions or areas (e.g., spots, regions of interest), for example, determining the left, right, top, and bottom (LRUD) connectivity state of each sample. For example, the receive signal processing chain 500 calculates the horizontal and vertical connectivity information for each cell. This connectivity map establishes left, right, top, and bottom connections (i.e., nearest neighbors in rows and columns) for active samples.

[0242] At 1110, the receiving signal processing chain 500 of the ultrasound system 204 can determine (e.g., calculate) the distances between continuous regions or areas (e.g., spots, regions of interest) based on the connection diagram 1108. For example, the receiving signal processing chain 500 of the ultrasound system 204 determines or calculates distances, such as the LRUD distance to the edge of the spot in each unit. For example, the receiving segment 210 calculates the left, right, top, and bottom distances (i.e., row distances and column distances) from the active sample to the non-connected edges.

[0243] The receiving signal processing chain 500 of the ultrasound system 204 can execute multiple (e.g., three) region of interest (ROI) finder sequences, referred to herein as ROI finder sequence 1 1112a, ROI finder sequence 2 1112b, and ROI finder sequence 3 1112c. Specifically, the ROI finder sequences can depend on the output of the amplitude segmentation sequence 1106, the connection diagram 1108, and the determined distance (DT distance) 1110, and subsequent ROI finder sequences can depend on the output of previous ROI finder sequences. For example, the second ROI finder sequence (ROI finder sequence 2 1112b) can depend on the output of the first ROI finder sequence (ROI finder sequence 1 1112a), and the third ROI finder sequence (ROI finder sequence 3 1112c) can depend on the output of the second ROI finder sequence (ROI finder sequence 2 1112b), as shown in the figure. In some implementations, the ROI finder (also known as a blob finder) can find up to four blobs (indicated as occupied consecutive pixels or voxels) in the segmentation mask and sort them by size.

[0244] Each region of interest finder sequence (ROI finder sequence 1 1112a, ROI finder sequence 2 1112b, ROI finder sequence 3 1112c) can include finding the corresponding target (target 1 1114a, target 2 1114b, target 3 1114c), and each can use multiple levels to find the corresponding target.

[0245] Figure 12 This illustrates a GPU amplitude segmentation processing chain for generating amplitude segmentation output according to at least one of the illustrated embodiments. Figure 10 A flowchart of the operation method 1200 of the receiving signal processing chain 500 (1046). The receiving signal processing chain 500 can be, for example, composed of the receiving section 210 of the ultrasound system 204 ( Figure 2 ) Implementation.

[0246] At 1202, the receiving signal processing chain 500 of the ultrasound system 204 begins with amplitude-segmented sigma data, which is the sigma source used for amplitude segmentation.

[0247] At 1204, the receiving signal processing chain 500 of the ultrasound system 204 generates amplitude-segmented (AS) beam histograms (ASBE AM HISTOGRAMS). This generates a per-beam histogram of the AS sigma data (e.g., size 256).

[0248] At 1206, the received signal processing chain 500 of the ultrasound system 204 generates amplitude segmentation (AS) frame histograms (ASFRAMEHISTOGRAMS). This generates a total frame histogram of AS sigma data (e.g., size 356).

[0249] At 1208, the receiving signal processing chain 500 of the ultrasound system 204 determines or otherwise generates frame histogram statistics (FAME HISTO STATS), such as calculating summary statistics about the total frame histogram.

[0250] At 1210, the received signal processing chain 500 of the ultrasound system 204 determines or otherwise generates K-means beam histograms, such as determining per-beam histograms (e.g., 4096 bins) of AS sigma data scaled to minimum / maximum values.

[0251] At 1212, the received signal processing chain 500 of the ultrasound system 204 determines or otherwise generates K-means frame histograms, such as determining a total frame histogram (e.g., 4096 bins) of AS sigma data scaled to minimum / maximum values.

[0252] At 1214, the receiving signal processing chain 500 of the ultrasound system 204 performs K-means preparation (K-Means Prep) to prepare data for round segmentation and determine seed segments.

[0253] At 1216, the receiving signal processing chain 500 of the ultrasound system 204 performs amplitude segmentation, for example, by performing K-means segmentation on the data.

[0254] At 1218, the receiving signal processing chain 500 of the ultrasound system 204 determines or otherwise generates the segmentation mask 1218, for example, based on amplitude segmentation sigma 1202 and amplitude segmentation 1216. This can, for example, create a marker mask for the upper two (2) segments.

[0255] At 1220, the received signal processing chain 500 of the ultrasonic system 204 performs smoothing on the segmentation mask. This may include, for example, generating a smoothing mask, filling holes, and reducing tendrils.

[0256] At 1222, the receiving signal processing chain 500 of the ultrasound system 204, for example, forces a target in the mask when enabled.

[0257] The receiving signal processing chain 500 of the ultrasound system 204 then determines, generates, or otherwise provides an amplitude segmentation output (segmented amplitude segmentation) 1224.

[0258] Figure 13 A GPU idle detection method for executing at least a portion of a receive signal processing chain 500, implemented between a single-board computer (SBC) 1300 and a GPU (SBC / GPU domain) 1302 according to at least one of the illustrated embodiments, is shown. The receive signal processing chain 500 may, for example, be comprised of the receiving segment 210 of an ultrasonic system 204 ( Figure 2 For example, it can be implemented via one or more GPUs and one or more CPUs.

[0259] 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 perform idle detection, for example at 1304, by calculating the frame differential sum of the background set and using a consecutive number of low-differential frames to determine the state (e.g., idle, non-idle). The SBC / GPU domain 1302 can also apply an adaptive threshold to the data, for example at 1306. This could, for example, zero out the sigma data if an idle state is set, or otherwise set all values ​​less than the sigma threshold to zero (0). The sigma threshold can be set by a harmonic sigma threshold register. As an example, the sigma threshold could be 75, which is equal to 51.08 dB. The sigma threshold lays the foundation for establishing spatial connectivity. This value can be intentionally set below the expected target minimum to ensure that objects of wider sizes are measured, including objects that may have sub-regions that satisfy the target minimum.

[0260] SBC 1300 includes a CPU (SBC / CPU domain) 1308 that executes a set of processor-executable instructions or logic. SBC / CPU domain 1302 can, for example, monitor scan status at 1310, respond to idle status from the GPU, and set the total frame clock register to control the scan rate.

[0261] Figure 14This is a flowchart illustrating a method 1400 for performing a single region of interest (ROI) finder sequence as part of a receive signal processing chain 500 according to at least one of the illustrated embodiments. The receive signal processing chain 500 may, for example, consist of the receive segment 210 of the ultrasound system 204 ( Figure 2 ) Implementation.

[0262] The receiving signal processing chain 500 of the ultrasound system 204 generates or accesses connection diagram 1402. Connection diagram 1108 can represent or indicate pixels or voxels that can form continuous regions or areas (e.g., spots, regions of interest), and can determine the left, right, top, and bottom (LRUD) connection status of each sample.

[0263] At 1404, the receiving signal processing chain 500 of the ultrasound system 204 determines (e.g., calculates) the distances (DT DISTANCES) to each sample according to the connection diagram 1108, such as determining the left, right, top, and bottom (LRUD) distances between continuous regions or areas (e.g., spots, regions of interest).

[0264] At 1406, the receiving signal processing chain 500 of the ultrasound system 204 determines the centroids (DT_CENTROIDS) of each sample (e.g., each contiguous region or area (e.g., spot, region of interest)) connecting Figure 1108. This may include finding the maximum centroid within specified constraints.

[0265] The receiving signal processing chain 500 of the ultrasound system 204 then marks multiple (e.g., three) targets in connection diagram 1108, for example, target A is marked at 1408a (marked target A), target B is marked at 1408b (marked target B), and target C is marked at 1408c (marked target C). The receiving signal processing chain 500 can mark targets using connection diagram 1402, the determined distances (DTDistances) 1404, and the determined centroid (DT_Centroid) 1406. This can advantageously extend the centroid of the target around corners.

[0266] The receiving 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 for identifying other targets when more than one target is present.

[0267] The receiving signal processing chain 500 of the ultrasound system 204 generates or receives amplitude segmentation output 1412, which constitutes the previously described segmented amplitude segmentation data (see amplitude segmentation output 1046). Figure 10 ) and the method for generating this amplitude segmentation output ( Figure 12 )).

[0268] At 1414, the receiving signal processing chain 500 of the ultrasound system 204 applies a mask that relies on the incoming target map 1410, the amplitude segmentation output 1412, and the mask marking the target. Applying this mask can isolate the target and provide a range map with the target removed.

[0269] The receiving signal processing chain 500 of the ultrasound system 204 receives or generates incoming target boundaries 1416, which specify the boundaries of targets other than the identified target in the image data when more than one target is present.

[0270] The receiving signal processing chain 500 of the ultrasound system 204 determines or otherwise generates target boundaries 1418, such as finding bounding boxes for targets, based on the output of the application mask 1414 and the incoming target boundaries 1416.

[0271] The receiving signal processing chain 500 of the ultrasound system 204 generates or provides a target sigma map 1420 based on the output of the application mask 1414. The target sigma map 1420 is a sigma map of only the identified targets.

[0272] The receiving signal processing chain 500 of the ultrasound system 204 generates or provides non-target distances 1422 based on the output of the application mask 1414. The non-target distances 1422 may take the form of a distance map of unidentified targets.

[0273] The receiving signal processing chain 500 of the ultrasound system 204 generates or provides a merged target ID map 1424 based on the output of the application mask 1414. The merged target ID map 1424 may take the form of a marked target ID map merged with a previous target ID map.

[0274] Figure 15 This is a flowchart illustrating a target analysis method 1500 for locating, analyzing, and tracking a target as part of the operation of a receive signal processing chain 500 according to at least one of the illustrated embodiments. The receive signal processing chain 500 may, for example, consist of the receiving segment 210 of an ultrasound system 204 ( Figure 2 ) Implementation.

[0275] The receiving signal processing chain 500 of the ultrasound system 204 identifies multiple (e.g., three) targets in the connection diagram. The receiving signal processing chain 500 may, for example, identify a first target (FIND TARGET 1) 1502a, a second target (FIND TARGET 2) 1502b, and a third target (FIND TARGET 3) 1502c. The resulting information (e.g., TARGET A ISOLATED SIGMA data, TARGET B ISOLATED SIGMA data, and TARGET C ISOLATED SIGMA data) can be output and provided to the PREP TARGET ANALYZER 1504.

[0276] The PREP TARGET ANALYZER 1504 combines target data in preparation for analysis, such as combining identified targets (e.g., first target, second target, third target).

[0277] The output from the PREP TARGET ANALYZER 1504, along with the outputs from the first target lookup, second target lookup, and third target lookup (FIND TARGET 1 1502a, FIND TARGET 2 1502b, FIND TARGET 3 1502c) (e.g., CENTROID 1, CENTROID 2, CENTROID 3, COMBINED BOUNDS), are provided to the target analyzer 1506. The target analyzer 1506 also receives the luma mask output 1508 (see luma mask for details). Figure 10 (1016). The target analyzer 1506 performs substantive processing (critical work) to determine whether a blob or ROI is a marker target that should be tracked. The target analyzer 1506 analyzes targets and ranks them based on defined target characterization criteria. Target characterization criteria include, for example, measures such as: frame measures including line density and background noise; region of interest (ROI) measures including mean, maximum, variance, area and / or aspect ratio; brightness map (mean); and region of interest relation measures including the relative location of the ROI. The background noise measure is used to disable detection output on frames saturated with high sigma. The line density measure is used to selectively exclude blobs / ROIs that are part of larger reflective objects (such as the posterior wall of tissue). Ranking is essentially an assessment of how "similar" each response is to a response from a marker, which is at least in part based on the physical geometry of the marker and the expected response pattern (e.g., artifacts) of the marker's ultrasonic reflective elements.

[0278] The target analyzer 1506 also applies weights. For example, to apply weights, the target analyzer 1506 applies high-pass, low-pass, or band-pass forms to the ROI metric and applies linear scaling to the data in the transition band between 0 and 1. It then applies weight values ​​to each scaled metric.

[0279] Sigmar average Qualcomm Lower cutoff value: 26.56 Qualcomm: 58.35 Scaled weights: 0.4 Maximum value Qualcomm Lower cutoff value: 41.24 Qualcomm: 90.08 Scaled weights: 0.05 variance Qualcomm Low cutoff value: 50.61 Qualcomm 355.85 Scaled weights: 0.25 Aspect Ratio Bandpass Low cutoff value: 0 All-pass: 0.38 High cutoff value: 1.1 Scaled weights: 0.3 area Bandpass Low cutoff value: 0 Full pass: 700 High cutoff value: 1400 Scaled weights: 0.2 Brightness diagram average Low-pass filter: 50.0 High cutoff value: 60.0 Scaled weights: 0.2 At 1510, the receiving signal processing chain 500 of the ultrasound system 204 tracks multiple targets (e.g., spots, regions of interest) frame by frame, for example receiving current tracking information from the target analyzer 1506 and providing the target analyzer 1506 with previous target tracking information.

[0280] For example, the receive signal processing chain 500 may optionally perform centroid tracking, such as generating a centroid tracking table or other data structure. The receive signal processing chain 500 may acquire the sigma matrix and distance matrix, as well as the best-fit centroid, and track the blob over time (e.g., frame-by-frame). The receive signal processing chain 500 may maintain a state machine that updates target tracking attributes across various states, such as the following two main states: search and track. Within each main state, there may be sub-states that control, for example, responsiveness, persistence, and confidence.

[0281] The received signal processing chain 500 can, for example, characterize ROIs or spots. This stage tests a series of gated metrics that qualify spots as valid marker targets and generate a goodness-of-fit metric for the spots / ROIs that pass the test.

[0282] The qualification assessment may include two gates, referred to as Gate 1 and Gate 2. In Gate 1, if no tracking is performed, it determines whether the weighted measures of the mean, maximum, variance, aspect ratio, and luminance mean are non-zero. In Gate 2, it determines whether the sum of the weighted mean, maximum, variance, aspect ratio, and previous goodness of fit is >= 0.6.

[0283] For the fit, for all ROIs or spots that pass the qualification, the weighted mean, maximum, variance, aspect ratio, area, brightness mean, and previous fit are summed to obtain the final fit measure for each ROI or spot.

[0284] The receive signal processing chain 500 can then sort the ROIs or spots. For example, the receive signal processing chain 500 sorts the ROIs or spots in descending order of fit. The receive signal processing chain 500 checks whether the top two spots are horizontally aligned (one above the other) and have similar strength. If so, their order is swapped so that the ROI or spot in the higher position gets a higher ranking. Among the sorted ROIs or spots, the higher-ranked ROI or spot is the primary target.

[0285] Figure 16 This is a flowchart illustrating a method 1600 for operating a receive signal processing chain 500 for locating, analyzing, tracking, and displaying targets according to at least one of the illustrated embodiments. Those skilled in the art will note that there is some overlap between method 1600 and method 1500, but method 1600 provides additional details, particularly regarding the tracking of multiple targets. The receive signal processing chain 500 can, for example, consist of the receiving segment 210 of an ultrasound system 204 (… Figure 2 ) Implementation.

[0286] As discussed earlier, the receiving signal processing chain 500 of the ultrasound system 204 finds multiple (e.g., three) targets in the connection diagram, such as finding a first target (FIND TARGET 1) 1602a, a second target (FIND TARGET 2) 1602b, and a third target (FIND TARGET 3) 1602c. The resulting information (e.g., TARGET A ISOLATED SIGMA data, TARGET B ISOLATED SIGMA data, and TARGET C ISOLATED SIGMA data) can be output and provided to the PREP TARGET ANALYZER 1604. The output from the PREP TARGET ANALYZER 1604 is optionally provided to the target analyzer 1606 along with other outputs (e.g., CENTROID 1, CENTROID 2, CENTROID 3, COMBINED BOUNDS) from the first target lookup, second target lookup, and third target lookup (FIND TARGET 1 1502a, FIND TARGET 2 1502b, FIND TARGET 3 1502c). The target analyzer 1506 also receives the luma mask output 1508 (see luma mask for details). Figure 10 (1016). The Target Analyzer (TARGET ANALYZER) 1606 analyzes targets and can even sort them.

[0287] As discussed earlier, the received signal processing chain 500 includes a multi-target tracker 1610 and a target analyzer 1506 that work together to track multiple targets (e.g., spots, regions of interest) frame by frame.

[0288] The target analyzer 1506 provides output to multiple (e.g., two) target selectors (TARGET SELECTOR 11608a, TARGET SELECTOR 2 1608b), which select targets based on analysis (e.g., based on ranking, which itself may be based on various target characterization criteria or metrics, such as: frame metrics including line density and background noise; region of interest metrics including mean, maximum, variance, aspect ratio or / or area; region of interest relation metrics including relative positioning of ROIs). The target selectors (TARGET SELECTOR 11608a, TARGET SELECTOR 2 1608b) can select appropriate targets and can provide sigma (sigma output for target 1, sigma output for target 2) and other information about the selected targets.

[0289] As previously explained, the multi-target tracker 1610 exchanges information with the target analyzer 1606 (e.g., information specifying the current state or current tracking information, and information specifying the previous tracking state). The multi-target tracker 1610, for example, receives current tracking information from the target analyzer 1506 and provides the target analyzer 1506 with previous target tracking information.

[0290] The multi-object tracker 1610 also receives histograms from the sigma estimator (DT ESTIMATOR) 1612. The sigma estimator (DT ESTIMATOR) 1612 can estimate density (density estimator) and statistics from the main sigma processing chain.

[0291] The multi-target tracker 1610 also receives left, right, top, and bottom (LRUD) distances 1614, which can represent the original distances in the segmentation map.

[0292] The output from the multi-target tracker 1610 is provided to the multi-target merger 1622. The multi-target merger 1622 also receives outputs from target selector 2 and target selector 1 via a bilateral filter 1616. The multi-target merger 1622 further receives outputs from the Sigma Chain A process 1618 and the raw luminance mask 1620. The multi-target merger 1622 determines the output to be displayed and causes the determined output to be displayed. The output from the multi-target merger 1622 (DETECTOR CHAIN ​​OUTPUT) is provided as the detector processing chain output 1624. For example, the receive signal processing chain 500 may optionally implement or apply centroid merging. Centroid merging can be used to format and / or route desired data for display. In standard operating mode, centroid merging can route isolated best-fit blobs with target emphasis elements (e.g., crosshairs, shading), but can also route distance data, culling codes, test patterns, etc. The receiving section 210 can update the centroid tracking table accordingly.

[0293] As mentioned above, there can be two main states: searching and tracking.

[0294] While in the search state, the receive signal processing chain attempts to detect the same target over 500 times, for example, attempting to detect the same target in three (3) consecutive frames. This can provide an enhanced level of confidence on a single detection. While three (3) consecutive frames are provided as an example, more or fewer frames can be used, although three (3) frames are considered to provide a good balance between speed and accuracy. A subsequent detection is qualified as a continuous detection if the centroid of each subsequent detection is within the target reach range of the target in the previous frame. The continuous detection counter is incremented on each successful detection. In response to a specified number of detections (e.g., three (3)) of the same target, initial tracking properties are set, and the state machine is transitioned to the tracking state. The continuous detection counter is immediately reset when the target is not detected in a frame.

[0295] When in tracking mode, the receiving signal processing chain 500 determines whether the target is within the target tracking region of interest (ROI).

[0296] If the target is within the target tracking ROI, the receiving signal processing chain 500 updates the tracking attributes, and the state machine is maintained in the tracking state.

[0297] On the other hand, if the target is not within the target tracking ROI, the receive signal processing chain 500 may optionally execute the following algorithm.

[0298] The received signal processing chain 500 increments a set of persistent counters (referred to as the ROI persistent counter; and the precision persistent counter).

[0299] The receive signal processing chain 500 determines whether the target is a trusted (e.g., level 2) detection. If so, the receive signal processing chain 500 updates the tracking attributes of the new target, and the state machine is maintained in tracking mode.

[0300] When the ROI persistence counter is less than or equal to 0, the receive signal processing chain 500 enters the outer loop.

[0301] When the precision persistence counter is less than or equal to 0, the receive signal processing chain 500 enters the inner loop.

[0302] The receiving signal processing chain 500 then clears the current target's tracking attributes (clears the TARGET_CURRENT tracking attribute), and the state machine's state is transitioned to the tracking lost state.

[0303] Once the ROI persistence counter is greater than zero (0), the receive signal processing chain 500 exits the outer loop. Then, the receive signal processing chain 500 clears the tracking attributes, and the state machine's state is changed to search.

[0304] Tracking attributes may include, for example, target confidence and target tracking ROI. Target confidence is determined by accumulating a counter across all locations within centroid tracking for a high sigma (e.g., greater than 125.957 dB) and a non-zero sigma within the target's reach range. If the ratio of high sigma to non-zero sigma is greater than a threshold (e.g., 25%), the confidence increases, for example, from 1 to 2. The target ROI is the full beamwidth of the sector plus the top and bottom, which are the exact top and bottom of the target plus a margin.

[0305] Figure 17A and Figure 17B The diagram illustrates a transmit (TX) signal path component and a receive (RX) signal path component of an ultrasonic system 1700 implementing a transmit signal processing chain and a receive signal processing chain according to at least one of the illustrated embodiments. This can be implemented using various types of processors, such as 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. It can also be implemented using analog circuitry.

[0306] The ultrasound system 1700 includes a field-programmable gate array (FPGA) domain 1702. The ultrasound system 1700 includes a 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 (i.e., ultrasound analog circuitry).

[0307] The Field Programmable Gate Array (FPGA) domain 1702 executes the programming logic programmed into the FPGA. The CPU (SBC / CPU domain) 1704 executes a corresponding set of processor-executable instructions, which can be stored on a non-transitory computer-readable medium or a processor-readable medium (e.g., ROM, RAM, flash memory, disk drive, optical disc drive). The GPU (SBC / GPU domain) 1706 executes a corresponding set of processor-executable instructions, which can be stored on a non-transitory computer-readable medium or a processor-readable medium (e.g., ROM, RAM, flash memory, disk drive, optical disc drive).

[0308] FPGA domain 1702 includes or implements a receive beamformer (RX BEAM FORMER) 1714 that beamforms the ultrasonic energy received by an ultrasonic transducer or probe, for example, focusing raw beam data into a single receive beam. The receive beamformer (RX BEAM FORMER) 1714 can buffer the beam and transmit or dispatch the buffered beam to a CPU (SBC / CPU domain) 1704, for example, via a Universal Serial Bus (UBS) communication interface (USB DISPATCH) 1716. FPGA domain 1702 may also include or implement a scan controller 1718. The scan controller 1718 is communicatively coupled to a transducer interface 1710 and is operable for controlling ultrasonic scans, for example, configuring per-beam transmission and reception of ultrasound. The scan controller 1718 is also communicatively coupled to an analog domain 1712 (i.e., ultrasonic analog circuitry).

[0309] CPU (SBC / CPU domain) 1704 includes a USB receive interface (USB RECEIVE) 1720 for receiving beams from the communication interface (USB DISPATCH) 1716.

[0310] CPU (SBC / CPU domain) 1704 includes a frame assembler 1722 operable to receive beams on a beam-by-beam basis and assemble or otherwise combine the received beams into frames. CPU (SBC / CPU domain) 1704 includes a communication interface (FRAME DISPATCH) 1724 operable to transmit (e.g., load) frames to GPU (SBC / GPU domain) 1706.

[0311] The GPU (SBC / GPU domain) 1706 receives frames from the CPU (SBC / CPU domain) 1704. The GPU (SBC / GPU domain) 1706 includes a GPU computation process 1726 and a GPU image process 1728. The GPU computation process 1726 performs RF processing (e.g., demodulation; filtering in the RTheta space). The GPU image process 1728 renders and / or performs image processing on the image data, preparing it for display.

[0312] The display 1708 may take the form of a display driver 1730, for example, that sends or otherwise renders images to a display, screen, or monitor.

[0313] Transducer interface 1710 includes an ultrasonic transducer or probe 1732 (e.g., an ultrasonic transducer crystal array) operable to transmit ultrasonic energy or signals and detect returned ultrasonic energy or signals. Transducer interface 1710 includes a multiplexer (TI MUX) 1734 communicatively coupled to scan controller 1718 and communicatively coupled (e.g., 64 channels, analog transmit / receive) to the ultrasonic transducer or probe 1732 to exchange signals with it. Multiplexer (TI MUX) 1734 can, for example, multiplex 128 channels into 64 channels.

[0314] Analog domain 1712 typically includes analog circuitry for an ultrasound system. For example, analog domain 1712 may include a pulse generator 1736 operable to drive an ultrasound transducer (e.g., a crystal) to emit ultrasound energy. Pulse generator 1736 may, for example, perform 64-channel transmit delay and waveform generation, and switch the ultrasound transducer or probe 1732 between transmit and receive modes. Also, for example, analog domain 1712 may include an analog front end (AFE) 1738 communicatively coupled to a scan controller 1718 to exchange information with it, and communicatively coupled to the pulse generator 1736 to receive information from it. This may, for example, perform TGC and / or ADC conversion.

[0315] The above detailed description has illustrated various implementations of the device and / or process using block diagrams, schematic diagrams, and examples. Where such block diagrams, schematic diagrams, and examples contain one or more functions and / or operations, those skilled in the art will understand 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 subject matter may be implemented via an application-specific integrated circuit (ASIC). However, those skilled in the art will recognize that the implementations disclosed herein can be implemented, in whole or in part, equivalently 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 circuitry and / or writing code for software and / or firmware in accordance with this disclosure will fall entirely within the skill of those skilled in the art.

[0316] Those skilled in the art will recognize that many of the methods or algorithms described herein may employ additional actions, omit some actions, and / or perform actions in a different order than specified.

[0317] Furthermore, those skilled in the art will understand that the mechanisms taught herein can be distributed as program products in various forms, and the illustrative implementations are equally applicable, regardless of the specific type of signal-bearing medium actually used to perform the distribution. Examples of signal-bearing media include, but are not limited to, recordable media such as floppy disks, hard disk drives, CD-ROMs, digital magnetic tapes, and computer memory.

[0318] The various embodiments described above can be combined to provide further embodiments. 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 / 483274; U.S. Patent Application 62 / 645677; U.S. Patent Application 15 / 946479; International Patent Application PCT / US2018 / 26291; U.S. Patent Application 62 / 892952; U.S. Patent Application 63 / 441558; U.S. Patent Application 63 / 441558; and U.S. Patent Application 63 / 525,280; U.S. Patent Application 63 / 625,167 are each incorporated herein by reference in their entirety. Various aspects of the embodiments may be modified as necessary to provide further embodiments utilizing the systems, circuits, and concepts in the various patents, applications, and publications.

[0319] In view of the above detailed description, these and other changes may be made to the embodiments. Generally, the terminology used in the appended claims should not be construed as limiting the claims to the specific embodiments disclosed in the specification and claims, but should be interpreted to include all possible embodiments and the entire scope of equivalents entitled to be obtained by this claim. Therefore, the claims are not limited by this disclosure.

Claims

1. A method for operating in an ultrasound system having a transmitting section and a receiving section to detect at least the presence or absence of a response from a tissue marker, the method comprising: A set of driving signals is generated via the transmitting section of the ultrasound system; The set of drive signals is supplied to an ultrasonic probe having at least one ultrasonic transducer, so that the at least one ultrasonic transducer emits ultrasonic energy as a set of pulses, the corresponding set of pulses being emitted along a corresponding one of the multiple beams and at multiple focal depths. as well as A series of return signals, representing the ultrasonic energy detected by the ultrasonic probe, are processed via a return signal processing chain in the receiving section of the ultrasonic system. The processing of this series of return signals includes: A luminance map is generated, at least in part, based on the series of returned signals, which indicates the intensity or loudness (dB) level of the series of returned signals in a set of image data; A sigma plot is generated, at least in part, based on this series of return signals, which indicates the changes between frames of the set of image data; A segmentation input map, representing one or more regions of interest in the set of image data, is generated at least in part based on this series of return signals; and Target analysis is performed, at least in part, based on this sigma plot, to detect the presence or absence of response signals from the tissue markers.

2. The method as described in claim 1, wherein, Execution target analysis involves ranking each of the multiple targets relative to each other.

3. The method as described in claim 1, wherein, Execution target analysis involves ranking each of multiple targets relative to each other based on a set of target characterization criteria.

4. The method of claim 3, wherein, Ranking each of a plurality of targets relative to each other based on a set of target characterization criteria includes ranking each of the plurality of targets based on one, more or all of the following: frame measure of the ultrasonic response of the marker, region of interest measure, region of interest relation measure and / or shape.

5. The method of claim 4, wherein, The target analysis further includes detecting the presence or absence of a response signal from the tissue marker, at least in part based on the order of each of the plurality of targets relative to each other.

6. The method according to any one of claims 1 to 5, wherein, Processing a series of return signals via the return signal processing chain includes mixing these return signals with a first multiple of the mixing frequency and mixing these return signals with a second multiple of the mixing frequency, which is 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 return signals generated by mixing these return signals with the first multiple and the second multiple, so as to at least partially filter out the ultrasound emitted by the at least one ultrasonic transducer.

8. The method of claim 6, wherein, Processing a series of return signals via this return signal processing chain includes performing envelope detection on each signal generated by mixing with a first multiple of the mixing frequency and mixing with a second multiple of the mixing frequency.

9. The method of claim 6, wherein, Generating a sigma graph involves performing a sigma mapping.

10. The method of claim 9, wherein, Performing sigma mapping involves performing inter-frame comparisons to identify inter-frame variations in the received ultrasound data.

11. The method of claim 10, wherein, Performing a sigma mapping includes one or more of the following: set focus fusion, lateral elimination, difference summation, and determination of lateral standard deviation.

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

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 object detection further includes applying adaptive thresholds.

15. The method of claim 6, wherein, Performing object detection further includes performing focus merging to combine ultrasound datasets from two or more focus levels.

16. The method of claim 6, wherein, Performing target detection further includes generating connection graph data representing connection information between cells along at least two axes that are perpendicular to each other.

17. The method of claim 6, wherein, Performing object detection further includes calculating the distance to the edge of the blob for each of the multiple cells.

18. The method of claim 6, wherein, Performing object detection further includes any one or more of the following: determining the centroid of the blob; performing centroid tracking; and performing centroid merging.

19. The method of claim 6, wherein, The return signal processing chain further processes a series of return signals, including any one or more of the following: focus blending, and performing scan conversion.

20. The method of claim 19, wherein, The return signal processing chain processes a series of return signals, which further includes visually and / or audibly presenting marker location information.

21. The method of claim 20, wherein, Presenting marker location information visually and / or aurally further includes presenting a visual representation of the marker's core relative to anatomical structures.

22. The method of claim 20, wherein, Presenting marker positioning information visually and / or audibly further includes presenting an auditory representation of the movement of the ultrasound probe relative to the marker's center of mass.

23. The method according to any one of claims 1 to 5, wherein, A set of drive signals generated via the transmitting section of the ultrasound system includes: A set of driving signals is generated for an ultrasonic pulse set, each of the pulses in the ultrasonic pulse set having a corresponding frequency, and each of the frequencies of the pulses in the pulse set being different from the other frequencies of the pulses in the pulse set. The drive signal from the set of drive signals is supplied to the at least one ultrasonic transducer so that the at least one ultrasonic transducer emits an ultrasonic signal having the pulse set, wherein the frequencies of the pulses in the pulse set are different from other frequencies of the pulses in the pulse set.

24. An ultrasound system, comprising: The transmitting section generates a set of driving signals and supplies them to an ultrasonic probe having at least one ultrasonic transducer, so that the at least one ultrasonic transducer emits ultrasonic energy as a set of pulses, the corresponding set of pulses being emitted along a corresponding one of a plurality of beams and at a plurality of focal depths. as well as The receiving section processes a series of return signals, representing the ultrasonic energy detected by the ultrasonic probe, via a return signal processing chain of the receiving section of the ultrasonic system, the return signal processing chain performing any of the methods described in claims 1 to 23.

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

26. An ultrasound system, comprising: The transmitting section generates a set of driving signals and supplies them to an ultrasonic probe having at least one ultrasonic transducer, so that the at least one ultrasonic transducer emits ultrasonic energy as a set of pulses, the corresponding set of pulses being emitted along a corresponding one of a plurality of beams and at a plurality of focal depths. as well as The receiving section includes a return signal processing chain that processes a series of return signals representing the ultrasonic energy detected by the ultrasonic probe, wherein the return signal processing chain performs the following operations: A luminance map is generated, at least in part, based on the series of returned signals, which indicates the intensity level of the series of returned signals in a set of image data; A sigma plot is generated, at least in part, based on this series of return signals, which indicates the changes between frames of the set of image data; A segmentation input map, representing one or more regions of interest in the set of image data, is generated at least in part based on this series of return signals; and Target analysis is performed, at least in part, based on this sigma plot, to detect the presence or absence of response signals from tissue markers.

27. The ultrasound system of claim 26, wherein, Execution target analysis involves ranking each of the multiple targets relative to each other.

28. The ultrasound system of claim 26, wherein, Execution target analysis involves ranking each of multiple targets relative to each other based on a set of target characterization criteria.

29. The ultrasonic system of claim 28, wherein, Ranking each of a plurality of targets relative to each other based on a set of target characterization criteria includes ranking each of the plurality of targets based on one, more or all of the following: frame measure of the ultrasonic response of the marker, region of interest measure, region of interest relation measure and / or shape.

30. The ultrasonic system of claim 29, wherein, The target analysis further includes detecting the presence or absence of a response signal from the tissue marker, at least in part based on the order of each of the plurality of targets relative to each other.

31. The ultrasonic system according to any one of claims 26 to 30, wherein, Processing a series of return signals via the return signal processing chain includes mixing these return signals with a first multiple of the mixing frequency and mixing these return signals with a second multiple of the mixing frequency, which is different from the first multiple.

32. The ultrasound system of claim 31, wherein, Processing a series of return signals via the return signal processing chain further includes filtering the return signals generated by mixing these return signals with the first multiple and the second multiple, so as to at least partially filter out the ultrasound emitted by the at least one ultrasonic transducer.

33. The ultrasound system of claim 31, wherein, Processing a series of return signals via this return signal processing chain includes performing envelope detection on each signal generated by mixing with a first multiple of the mixing frequency and mixing with a second multiple of the mixing frequency.

34. The ultrasound system of claim 31, wherein, Generating a sigma graph involves performing a sigma mapping.

35. The ultrasound system of claim 34, wherein, Performing sigma mapping involves performing inter-frame comparisons to identify inter-frame variations in the received ultrasound data.

36. The ultrasound system of claim 35, wherein, Performing a sigma mapping includes one or more of the following: set focus fusion, lateral elimination, difference summation, and determination of lateral standard deviation.

37. The ultrasonic system of claim 36, wherein, Performing sigma mapping further includes any one or more of the following: multiplying two ultrasound data streams and performing frame elimination.

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 object detection further includes applying adaptive thresholds.

40. The ultrasound system of claim 31, wherein, Performing object detection further includes performing focus merging to combine ultrasound datasets from two or more focus levels.

41. The ultrasound system of claim 31, wherein, Performing target detection further includes generating connection graph data representing connection information between cells along at least two axes that are perpendicular to each other.

42. The ultrasound system of claim 31, wherein, Performing object detection further includes calculating the distance to the edge of the blob for each of the multiple cells.

43. The ultrasound system of claim 31, wherein, Performing object detection further includes any one or more of the following: determining the centroid of the blob; performing centroid tracking; and performing centroid merging.

44. The ultrasound system of claim 31, wherein, The return signal processing chain further processes a series of return signals, including any one or more of the following: focus blending, and performing scan conversion.

45. The ultrasound system of claim 44, wherein, The return signal processing chain processes a series of return signals, which further includes visually and / or audibly presenting marker location information.

46. ​​The ultrasound system of claim 45, wherein, Presenting marker location information visually and / or aurally further includes presenting a visual representation of the marker's core relative to anatomical structures.

47. The ultrasound system of claim 45, wherein, Presenting marker positioning information visually and / or audibly further includes presenting an auditory representation of the movement of the ultrasound probe relative to the marker's center of mass.

48. The ultrasonic system according to any one of claims 26 to 30, wherein, A set of drive signals generated via the transmitting section of the ultrasound system includes: A set of driving signals is generated for a set of ultrasonic pulses, each pulse in the set having a corresponding frequency, and each of these frequencies being different from the other frequencies of the pulses in the set; and The drive signal from the set of drive signals is supplied to the at least one ultrasonic transducer so that the at least one ultrasonic transducer emits an ultrasonic signal having the pulse set, wherein the frequencies of the pulses in the pulse set are different from other frequencies of the pulses in the pulse set.

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