Ultrasonic imaging system having digital ultrasonic imaging device

Abstract

To provide a system, method, and tangible non-transient computer-readable medium adapted to be executed by a processor for providing a contrast ultrasonic (CEUS) image.SOLUTION: A CEUS system includes: an ultrasonic probe adapted so as to provide an ultrasonic image; a processor; a tangible non-transient computer readable medium for storing an instruction to cause the processor to determine an outersurface frame of the ultrasonic image when executed by the processor; and a display configured so as to display an instruction to remove the outersurface frame from the ultrasonic image on the basis of a criterion for providing an optimized set of the frame, and the optimized set of the frame by communicating with the processor.

Description

[Technical field]

[0001] CROSS-REFERENCE TO PRIOR APPLICATIONS (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of European Patent Application No. 22194740.1, filed on September 9, 2022, and Chinese Patent Application No. PCT / CN2022 / 104036, filed on July 6, 2022, all of which are incorporated by reference herein. [Background technology]

[0002] Contrast-enhanced ultrasound (CEUS) is an ultrasound imaging technique used in various clinical applications. CEUS is able to detect nonlinear signals received from microbubbles circulating in the bloodstream after intravenous injection of an ultrasound contrast agent. Thus, CEUS images allow the recording of tissue perfusion due to the relatively slow flow at the capillary level, as well as the visualization of blood flow in arteries and veins. As a result, CEUS can provide a dynamic visualization of blood flow at both the macro- and microcirculatory levels. Among other clinical applications, the CEUS imaging mode is recommended in the diagnosis and treatment of lesions on the liver that may be malignant.

[0003] The sonographer operates the probe to collect images and loops, which can typically span several minutes. The representative images and loops collected by the sonographer are then often transmitted to another location for review of the data, for example, by a radiologist or other trained clinician. In some cases, the radiologist / clinician performs the sonogram and collects / evaluates the frames and loops used to diagnose and treat the medical condition. Additionally, the radiologist / clinician typically is not present during the CEUS examination, which is typically a US radiology case, but rather reviews the case at a remote workstation. Thus, data from the procedure must be stored and transmitted from the sonographer's location to the radiologist / clinician. This data transfer can be difficult due to the relatively long duration of the CEUS sequences acquired.

[0004] During a CEUS procedure, a scan is often performed in a two-dimensional plane through the portion of the body (e.g., the liver) being examined. Multiple frames and loops are collected during the procedure and sent for review by a trained clinician, such as a radiologist / clinician. As will be appreciated, when a sonographer is scanning a region of interest (ROI), there are many sources of motion that can affect the quality of the images being collected. For example, patient motion due to breathing can result in a shift in the location of the image plane, resulting in images out of the image plane of the current scan, ultimately resulting in lower quality images and an unproductive scan.

[0005] Although some types of motion compensation are used to reduce the effects of respiratory motion on the images collected, motion artifacts in the form of out-of-plane images remain when using known advanced CEUS imaging systems. Of the relatively large amount of image data collected in a scan, much of the data is out-of-plane and may be of undesirable quality due to motion during the CEUS scan. This data is often stored in memory and transmitted to a clinician for review. As will be appreciated, more stored or transmitted data, or both, places a strain on computer systems used to store, transmit, and share image data from the scan. These large amounts of out-of-plane image data are of poor quality and therefore not useful to the clinician reviewing the images, yet are stored in scarce memory. Furthermore, a clinician reviewing a scan from a CEUS procedure must sort through many images to find one that is of sufficient quality to adequately assess the patient's condition. Thus, the out-of-plane image data is not only a drain on memory resources, but also occupies a clinician's time during review of a CEUS procedure. Summary of the Invention [Problem to be solved by the invention]

[0006] What is needed is a system that overcomes at least the above-mentioned shortcomings of the known systems mentioned above. [Means for solving the problem]

[0007] According to one aspect of the present disclosure, a system for providing contrast enhanced ultrasound (CEUS) images comprises an ultrasound probe adapted to provide an ultrasound image, a processor, a tangible non-transitory computer readable medium storing instructions that, when executed by the processor, cause the processor to determine out-of-plane frames of an ultrasound image based on a criterion to provide an optimized set of frames, and a display in communication with the processor and configured to display the optimized set of frames.

[0008] According to another aspect of the disclosure, a tangible, non-transitory computer readable medium stores instructions that, when executed by a processor, cause the processor to determine out-of-plane frames of a contrast-enhanced ultrasound image (CEUS), remove the out-of-plane frames from the ultrasound image based on a criterion to provide an optimized set of frames, and, in communication with the processor, cause a display configured to display the optimized set of frames.

[0009] According to another aspect of the present disclosure, a method for providing an ultrasound image is disclosed, determining out-of-plane frames of the ultrasound image, removing the out-of-plane frames from the ultrasound image based on a criterion to provide an optimized set of frames, and displaying the optimized set of frames.

[0010] Representative embodiments are best understood from the following detailed description when read in conjunction with the accompanying drawings. It is emphasized that the various features are not necessarily drawn to scale. In fact, dimensions may be arbitrarily increased or decreased for clarity of illustration. Wherever applicable and practical, like reference numerals refer to like elements. [Brief description of the drawings]

[0011] [Figure 1]1 is a simplified block diagram of a CEUS imaging system for imaging a portion of a body, according to a representative embodiment. [Figure 2A] 2 is a flowchart of a method of acquiring images using the CEUS imaging system of FIG. 1 to provide a frame of images to a clinician for review, according to a representative embodiment. [Figure 2B] 2B is a flowchart of a method for reviewing all cinematic loops (cineloops) acquired with the method of FIG. 2A by a radiologist or other trained clinician, according to a representative embodiment. [Diagram 3] 1 is a flowchart of a method for removing an out-of-plane frame according to a representative embodiment. [Figure 4] 1 is a graph of CEUS intensity versus time (also called a TIC curve) for an ideal wash-in and wash-out cycle. [Diagram 5] 2 is a graph of a CEUS intensity versus time curve (TIC curve) and a fitted TIC curve based on actual data collected with the CEUS imaging system of FIG. 1 in accordance with a representative embodiment. [Figure 6A] 1 is a flowchart of a method for determining whether a frame is an in-plane frame or an out-of-plane frame using changes in a TIC curve, according to a representative embodiment. [Figure 6B] 1 is a flowchart of a method for selecting a representative CEUS frame or short loop at or near a feature point of a TIC curve, according to a representative embodiment. [Figure 7] 1 is a flowchart of a method for determining whether a frame is an in-plane frame or an out-of-plane frame using a normalized cross-correlation coefficient (NCCC) between adjacent frames, according to a representative embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] In the following detailed description, for purposes of explanation and not limitation, representative embodiments disclosing specific details are described to provide a thorough understanding of the embodiments according to the present teachings. Descriptions of known systems, devices, materials, methods of operation, and methods of manufacture may be omitted to avoid obscuring the description of the representative embodiments. Nevertheless, systems, devices, materials, and methods within the scope of those skilled in the art may be within the scope of the present teachings and used in accordance with the representative embodiments. It is understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. Defined terms are given the technical and scientific meaning of the defined terms as commonly understood and accepted in the art of the present teachings.

[0013] It is understood that terms such as first, second, third, etc. may be used herein to describe various components or components, but these components or components should not be limited by these terms. These terms are used only to distinguish one component or component from another component or component. Thus, a first element or component described below can be called a second element or component without departing from the teachings of the inventive concept.

[0014] The terms used herein are for the purpose of describing particular embodiments only and are not intended to be limiting. As used in this specification and the appended claims, the singular forms of the terms "a," "an," and "the" are intended to include both the singular and the plural unless the context clearly dictates otherwise. In addition, the terms "comprises," "comprises," and / or similar terms specify the presence of stated features, elements, and / or components, but do not exclude the presence or addition of one or more other features, elements, components, and / or groups thereof. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0015] As used herein and in the appended claims, and in addition to their ordinary meaning, the terms "approximately" are meant to have an acceptable limit or degree. For example, "about 20 GHz" means that one of ordinary skill in the art would consider a signal to be 20 GHz within a reasonable measure.

[0016] As used in this specification and the appended claims, the term "substantially" means within an acceptable limit or degree in addition to its ordinary meaning. For example, "the transducer ports are substantially the same" means that one of ordinary skill in the art would consider the transducer ports to be the same.

[0017] As described more fully below, the present teachings relate to a CEUS system, method, and tangible non-transitory computer readable medium that provides a representative short limited number of frames, or loop selection, or both, to a CEUS workflow. In particular, the workflow according to the present teachings reduces the time and effort required for the review procedure because 1) a required subset of representative images with TIC curves and two pre-contrast B-mode images are transferred to a workstation, and 2) the radiologist or other trained clinician's efforts are focused on reviewing a relatively small data set containing essential diagnostic information that is automatically abstracted from the entire CEUS cine loop. This novel CEUS workflow simplifies and facilitates the efforts of CEUS image acquisition and interpretation. Thus, the CEUS system, method, and tangible non-transitory computer readable medium that provide a CEUS workflow provide valuable practical applications and improvements in this and potentially other technical fields.

[0018] FIG. 1 is a simplified block diagram of an imaging system 100 for imaging a region of interest of a subject, according to a representative embodiment.

[0019] 1, imaging system 100 includes an imaging device 110 and a computer system 115 for controlling imaging of a region of interest of a patient 105 on a table 106. Imaging device 110 is illustratively an ultrasound imaging system capable of providing a contrast enhanced ultrasound (CEUS) image scan of a region of interest (ROI) of patient 105.

[0020] Computer system 115 receives image data from imaging device 110 and stores and processes the imaging data according to representative embodiments described herein. Computer system 115 includes a controller 120, a memory 130, a display 140 with a graphical user interface (GUI) 145, and a user interface 150. Display 140 may also include a loudspeaker (not shown) for providing audible feedback.

[0021] The memory 130 stores instructions executable by the controller 120. When executed, and as described more fully below, the instructions cause the controller 120 to perform different steps for a user to use the GUI 145 or the user interface 150, or both, and to initialize an ultrasound imaging device with a transducer, among other tasks. Additionally, the controller 120 may implement additional operations based on executing the instructions, such as instructions or communications with other elements of the computer system 115, including the memory 130 and the display 140, to perform one or more of the processes described above.

[0022] Memory 130 may include main memory and / or static memory, and such memories may communicate with each other and with controller 120 via one or more buses. Memory 130 stores instructions used to implement some or all aspects of the methods and processes described herein.

[0023] As will become clearer as this description continues, the instructions stored in memory 130 may be referred to as "modules," with various modules comprising executable instructions that, when executed by a processor, perform various functions described in connection with the various representative embodiments described below. These modules include, but are not limited to, a module for automatically identifying and removing out-of-plane (OOP) frames and loops, and a module for selecting short loops of representative frames and images for storage and transmission to a radiologist or other clinician for review.

[0024] Memory 130 may be implemented, for example, by any number, type, and combination of random access memory (RAM) and read only memory (ROM) and may store various types of information, such as software algorithms that, when executed by the processor, act as instructions that cause the processor to perform various steps and methods in accordance with the present teachings. Additionally, updates to the methods and processes described herein may be provided to computer system 115 and stored in memory 130.

[0025] The various types of ROM and RAM may include any number, type, and combination of computer readable storage media, such as disk drives, flash memory, electrically field programmable gate array read only memory (EPROM), electrically erasable field programmable gate array read only memory (EEPROM), registers, hard disks, removable disks, tapes, compact disk read only memory (CDROM), digital versatile disk (DVD), floppy disk, Blu-ray disk, universal serial bus (USB) drive, or any other form of storage media known in the art. Memory 130 is a tangible storage medium that stores data and executable software instructions and is non-transient while the software instructions are stored. As used herein, the term "non-transient" should not be interpreted as a permanent characteristic of a state, but as a characteristic of a state that persists over a period of time. The term "non-transient" specifically negates fleeting characteristics, such as the characteristics of a carrier wave or signal, or other formation that exists only temporarily at any place at any time. Memory 130 may store software instructions and / or computer readable code that enable the performance of various functions. Memory 130 may be encrypted and / or masked, or may be unencrypted and / or masked.

[0026] A "memory" is an example of a computer-readable storage medium, and should be construed as multiple memories or databases, as the case may be. The memory or database may be, for example, multiple memories or databases local to the computer and / or distributed among multiple computer systems or computing devices, or located in a "cloud" according to known components and methods. A computer-readable storage medium is defined as any medium that constitutes patentable subject matter under 35 USC §101, and excludes any medium that does not constitute patentable subject matter under 35 USC §101. Examples of such media include non-transitory media, such as computer memory devices that store information in a format readable by a computer or data processing system. More specific examples of non-transitory media include computer disks and non-volatile memories.

[0027] The controller 120 represents one or more processing devices, configured to execute software instructions stored in the memory 130 to perform functions as described in various embodiments herein. The controller 120 may be implemented using any combination of hardware, software, firmware, hardwired logic circuitry, or combinations thereof, such as a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a general purpose computer, a central processing unit, a computer processor, a microprocessor, a graphics processing unit (GPU), a microcontroller, a state machine, a programmable logic device, or combinations thereof. Furthermore, any processing unit or processor herein may include multiple processors, parallel processors, or both. Multiple processors may be included or combined in a single device or in multiple devices.

[0028] The term "processor" as used herein encompasses an electronic component capable of executing a program or machine-executable instructions. References to a computing device with a "processor" should be interpreted to include more than one processor or processing core, such as in a multi-core processor. A processor may also refer to a collection of processors within a single computer system or distributed among multiple computer systems, such as a cloud-based or other multi-site application. The term computing device should also be interpreted to include a collection or network of computing devices, each of which includes one or more processors. Modules have software instructions for performing various functions using one or more processors, which may be within the same computing device or distributed across multiple computing devices.

[0029] Display 140 may be, for example, a monitor such as a computer monitor, a television, a liquid crystal display (LCD), a light emitting diode (LED) display, a flat panel display, a solid state display, or a cathode ray tube (liquid) display, or an electronic whiteboard. Display 140 may also provide a graphical user interface (GUI) 145 for displaying and receiving information to and from a user.

[0030] The user interface 150 may include a user and / or network interface for providing a user with information and data output by the controller 120 and / or memory 130 and / or receiving information and data input by a user. That is, the user interface 150 allows a user to operate the imaging device as described herein and to schedule, control, or otherwise manipulate aspects of the imaging system 100 of the present teachings. In particular, the user interface 150 allows the controller 120 to indicate the effect of the user's control or manipulation. The user interface 150 may include one or more of a port, a disk drive, a wireless antenna, or other type of receiver circuitry. The user interface 150 may further connect one or more interface devices, such as, for example, a mouse, a keyboard, a mouse, a trackball, a joystick, a microphone, a video camera, a touchpad, a touch screen, voice or gesture recognition captured by a microphone or video camera, etc.

[0031] In particular, the controller 120, memory 130, display 140, GUI 145, and user interface 150 may be located remotely (e.g., in another location in the building or another building) from the imaging device 110 operated by the sonographer. The controller 120, memory 130, display 140, GUI 145, and user interface 150 may be located, for example, where the radiologist / clinician is located. However, in particular, additional controllers, memories, displays, GUIs, and user interfaces may be located closer to the sonographer and useful for accomplishing various functions of the imaging device 110 required to complete a CEUS scan as contemplated by the present teachings.

[0032] Figure 2A is a flow chart of a method 202 of acquiring images using the CEUS imaging system of Figure 1 to provide a frame of images to a clinician for review, according to a representative embodiment. Various aspects and details of the method are common to those described in connection with the representative embodiment of Figure 1. These common aspects and details may not be repeated to avoid obscuring the currently described representative embodiment.

[0033] Referring to FIG. 2A, an initial plane for imaging the liver is selected at 204 and CEUS images are acquired at the initial plane at 206. That is, at 204, the sonographer begins the CEUS scan at an initial location, such as a lesion on the liver. When the imaging device 110 performs the scan, it images a two-dimensional image plane (sometimes called a slice), which is the initial plane, and it is at the initial plane that the CEUS images are acquired. The initial plane is located in a portion of the body selected for imaging, which for illustrative purposes may be the target lesion area in the center of the ultrasound image. The CEUS images are acquired by placing the probe in the appropriate position / orientation and then acquiring incoming frames over a full examination period of 3-6 minutes. As used herein and described more fully below, images at or not too far from the desired image plane at which the sonographer is attempting to acquire image data are referred to as in-plane (IP) images, which include the entire area of ​​the lesion being examined and are desired for further review to aid in diagnosis or treatment. In particular, these desired in-plane frames may be referred to herein as optimized frames because they at least provide the radiologist / clinician with the frames that are most useful for diagnosing and treating the patient and do not include OOP frames that are less useful for diagnosing and treating the patient, and if provided to the radiologist / clinician, may burden the radiologist / clinician with reviewing a relatively large number of non-optimal frames from the CEUS procedure.

[0034] However, as described more fully below, relative motion between the patient and the imaging device can cause the imaging device 110 to capture an image in another image plane that is not the same as the desired initial plane. For example, when the sonographer is attempting to capture an image at a selected location (e.g., a target lesion area), patient movement (e.g., caused by breathing) or unintentional movement of the imaging device 110 by the sonographer will cause the imaging device 110 to move relative to the selected location. This causes the imaging device 110 to capture an ultrasound image from another plane that is different from the initial plane. In contrast, images captured at another plane that is too far from the initial plane based on certain factors that will be described more fully below in the desired IP image are referred to herein as OOP images and are undesirable. According to various aspects of the present teachings described in connection with the following exemplary embodiments, OOP images are provided that are deemed too far from the initial plane and are not included in the images provided for review by a radiologist or similarly trained clinician. In one measure, in OOP, a significant portion (e.g., 70% to 100%) of the target area of ​​the lesion is lost in the current image frame.

[0035] After completion of 206, the method 202 proceeds to perform a visual cineloop quality check at 208. For example, a sonographer can review the images acquired at 206 to check the quality of the images collected (e.g., at the 3-6 minute portion of the procedure, as alluded to above).

[0036] At 210, the sonographer determines whether the acquired image data is sufficient for a complete review and analysis of the condition of the anatomy being imaged. If the sonographer determines that sufficient image data is acquired, the method 202 proceeds to 212 where the collected data is stored and / or transmitted to another location for storage and review.

[0037] If the sonographer determines that more image data is needed, the method 202 proceeds to 214, where a second contrast agent may be needed for the current or next plane of the liver where the appearance of perfusion was not evident during the first injection period. The method 202 then returns to 206, and the procedure is repeated at 210 until the sonographer determines that the image data acquired is sufficient for a complete review and analysis of the condition of the anatomy being imaged. The method 202 then proceeds to 212, where the collected data is stored, or transmitted to another location for storage and review, or both. As will be described more fully below, OOP images that are not useful for the desired imaging procedure are removed and not stored at 212. Rather, the image data stored at 212 includes only images that are below a threshold set for OOP images.

[0038] Figure 2B is a flow chart of a method 220 of reviewing all cinematic loops (cineloops) acquired in the manner of Figure 2A by a radiologist or other trained clinician, according to a representative embodiment. Various aspects and details of the method are common to those described in connection with the representative embodiments of Figures 1 and 2A. These common aspects and details may not be repeated to avoid obscuring the currently described representative embodiment.

[0039] At 222, the entire imaging procedure, including the entire cine loop and notes from the sonographer, is loaded for review by the radiologist / clinician. By way of example, the imaging procedure loaded at 222 may be initially stored on a suitable memory device and transported to another location where the sonographer is located. Alternatively, the entire imaging procedure acquired at 212 may be transmitted (e.g., by wired or wireless communication link) and loaded at 222 for review by the radiologist / clinician. As will be appreciated, and as will become more clear as this description continues, the present teachings allow only IP images to be stored and transmitted at 222 for loading. Beneficially, in comparison to known systems that include OOP and IP image data for loading for review by the radiologist / clinician, only IP images are stored or transmitted at 222 for loading. This, of course, reduces memory requirements for the stored image data, or bandwidth requirements for the transmitted image data, or both. Thus, and among other advantages, the present teachings reduce memory requirements, or bandwidth requirements, or both for the collection of image data to be reviewed by the radiologist / clinician.

[0040] At 224, the image data loaded at 222 is reviewed by the radiologist / clinician and measurements are taken by the radiologist / clinician from the IP images. Beneficially, at 222, since only the IP images are stored or transmitted for loading, the radiologist / clinician does not have to review less than the desired images (OOP images) at 224. In contrast, image review of known CEUS imaging systems is difficult due to the CEUS loop length (up to 5 minutes of imaging from contrast injection). Thus, the review burden in time as well as mental effort by the radiologist / clinician is reduced by the systems and methods of the present teachings as compared to known systems and methods.

[0041] At 226, a structured report (SR) or a free text report (FTR) is generated and at 228, the method 220 of reviewing CEUS image data is completed.

[0042] 3 is a flow chart of a method 300 for removing out-of-plane frames according to a representative embodiment. Modules containing instructions, when executed by a processor, cause the processor to perform the method 300. Various aspects and details of the method are common to those described in connection with the representative embodiment of FIGS. 1-2B. These common aspects and details may not be repeated to avoid obscuring the currently described representative embodiment.

[0043] At 302, the method 300 begins with determining OOP frames of a CEUS imaging procedure. As will be described more fully below, the determination of OOP frames may be performed according to a variety of methods. As alluded to above and described more fully below, the instructions comprise modules stored in a tangible non-transitory computer readable medium that, when executed by a processor, cause the processor to automatically identify OOP images due to patient or imaging device motion. As mentioned above and described more fully below, OOP images are undesirable artifacts for diagnostic and therapeutic purposes. At 302, these OOP images are identified for removal during data acquisition by a sonographer.

[0044] At 304, the method continues with automatic removal of OOP frames from the CEUS imaging data based on criteria to provide an optimized set of frames of IP images. Again, the instructions stored in memory 130 comprise modules executed by the processor to remove OOP frames.

[0045] As mentioned above, this removal of OOP images is performed while the sonographer is performing the CEUS procedure, beneficially reducing memory requirements for storing the imaging procedure's data, or bandwidth requirements for transmitting the imaging procedure's data, or both. As described more fully below, the criteria by which an image is determined to be removed from the CEUS procedure as being an OOP procedure may be based on a comparison of normalized cross-correlation coefficients (NCCC) between adjacent frames, or based on a comparison of time intensity curve (TIC) data from a TIC curve with TIC data of frames collected during the CEUS procedure. Regardless of the type of criteria selected, for example, a comparison with a threshold value determines whether a particular frame should be discarded as being an OOP frame, and therefore whether the particular frame should be saved as an IP frame for further review by a radiologist or other clinician. Thus, 304 results in a reduction in the memory requirements of the imaging system 100, or bandwidth requirements for transmission of image data by or within the imaging system 100, or both.

[0046] At 306, the method 300 completes with display of the optimized set of frames for review by a radiologist or other clinician. Illustratively, these optimized sets of frames may be shown on the display 140 and further manipulated by the radiologist or other clinician via the GUI 145 of the imaging system 100.

[0047] Figure 4 is a graph of CEUS intensity versus time (also called a TIC curve) for an ideal wash-in and wash-out cycle. Various aspects and details of Figure 4 are common to those described in connection with the exemplary embodiments of Figures 1-3. These common aspects and details may not be repeated to avoid obscuring the currently described exemplary embodiment.

[0048] In accordance with the present teachings, removal of OOP frames eliminates unwanted frames and redundancies within the entire cine loop, leaving only IP frames for review by the sonographer or other clinician. Beneficially, the remaining IP frames / short cine loops correspond to significant events such as liver phase difference resulting in median half-time 406 between onset and peak time, which frequently occurs at 60 and 120 seconds after onset, peak time 404 when the target lesion shows strongest enhancement in the CEUS image, and onset 402 when microbubbles in the contrast agent reach the target lesion.

[0049] Figure 5 is a graph of a CEUS intensity versus time curve (TIC curve) and a fitted TIC curve based on data collected by the CEUS imaging system of Figure 1, according to a representative embodiment. Various aspects and details of Figure 5 are common to those described in connection with the representative embodiments of Figures 1-4. These common aspects and details may not be repeated to avoid obscuring the currently described representative embodiment.

[0050] Referring to FIG. 5, the raw data of curve 500 is the CEUS intensity at various time points obtained from a CEUS scan of the liver. Illustratively, these data are collected by a sonographer who has either manually or automatically identified a suspicious lesion to be targeted. Depending on the contrast ratio between the lesion and the background, the suspicious lesion can be determined in one of several ways, such as a pre-contrast B-mode image with a high mechanical index (MI) (e.g., MI=1.3), or from selected frames within the CEUS loop with either its side-by-side B-mode or CEUS images.

[0051] In particular, the raw data of curve 500 is from a relatively smaller region of interest (ROI) around the target lesion based on the entire motion compensated CEUS loop. The fitted curve 502 is a fitted curve based on the raw data of curve 500. The fitted curve 502 is created using a mathematical model specific to the anatomical portion being scanned. Illustratively, the model selected to determine the fitted curve 502 is a delayed normal model that determines the mean transit time (MTT) of contrast across the liver, MTT=μ+1 / λ where μ is the mean of the lag normal distribution, and λ is the preclet number, which is the ratio between the diffusion time and the convection time, divided by 2 to estimate both the diffusion and convection contributions of microbubbles moving through a blood vessel. Further details of determining MTT values ​​for use in connection with the present teachings can be found in Alireza Akhbardeh et al., "A Multi-Model Framework to Estimate Perfusion Parameters using Contrast-Enhanced Ultrasound Imaging," Med. Phys. 46(2), February 2019, pp. 590-600, the entire disclosure of which is specifically incorporated herein by reference (a copy of which is attached).

[0052] As will be appreciated, when applied to other anatomical elements of the body, other mathematical models are used that are found to better track CEUS contrast intensity versus time for the particular anatomical element being studied. By way of example and not limitation, other mathematical models include a log-normal model for the breast and heart, a gamma variate mathematical model for the carotid artery, a local density random walk (LDRW) mathematical model, and an early transit time (FTP) model for the carotid artery. These mathematical models are modules stored in memory 130 that, when executed by the processor, include instructions that obtain raw CEUS intensity data from the imaging device and calculate a curve 502 that is fitted to these data.

[0053] As will become clearer as the description continues, using the systems and methods of the present teachings, the mean value of the data points and the standard deviation from the mean are determined for each data point. The mean value and standard deviation are compared to a threshold value to determine data points classified as in-plane data points, and these data points are not removed from the frame of data provided to the radiologist / clinician. In contrast, data points that are greater than the threshold value are removed from the data set. As an example, data point 504, which is relatively close to the fitted curve 502, is determined by the systems and methods of the present teachings to be an in-plane data point. However, data sets 506, 508, 510 are likely to exceed the threshold value and are likely to be data points from another plane that are erroneously captured due to the relative motion of the body and the imaging device 110, as described above. Thus, these data sets are determined by the systems and methods of the present teachings to be OOP data points and are not stored image data for the CEUS procedure, are not transmitted to the radiologist / clinician, or both. As mentioned above, and as described more fully below, the module for automatically identifying and removing OOP frames and loops is instructions stored in memory 130 that are executed by the processor to perform this identification and removal of OOP frames and loops.

[0054] FIG. 6A is a flow chart of a method 600 for determining whether a frame is an in-plane frame or an out-of-plane frame using changes in a TIC curve, according to a representative embodiment. Various aspects and details of FIG. 6A are common to those described in connection with the representative embodiments of FIGS. 1-5. These common aspects and details may not be repeated to avoid obscuring the currently described representative embodiment. Additionally, as described above, the method 600 is a module that includes instructions stored in the memory 130. When executed by a processor, the instructions cause the processor to perform the method 600.

[0055] At 602, known motion compensation techniques are applied to the entire cineloop, and thereby to a relatively large region including the suspect lesion or the entire image, if desired.

[0056] At 604, a TIC curve is generated around the target lesion for a smaller ROI based on the entire motion compensation CEUS loop. By way of example, curve 500 is a TIC curve generated for a smaller ROI around the target lesion of the liver. After generating the TIC curve, the method includes applying a mathematical model appropriate to the organ element being scanned by CEUS. Continuing with the example of FIG. 5, in this part of the method, a fitted curve 502 for the liver is generated using the delayed normal model described above.

[0057] Next, at 604 of method 600, a difference curve is generated using a difference function (diff(n)) for each time data point. According to an exemplary embodiment, the fitted difference for each CEUS intensity and time data point n is calculated as diff(n)=abs(OTIC(n)-FTIC(n)), where OTIC is the original time data point and FTIC is the fitted CEUS time data point n.

[0058] At 606, the method continues by calculating the standard deviation (std) of the difference curves for each CEUS and time data point. According to an exemplary embodiment, a frame is considered OOP when the OTIC curve value (n) at each time point is outside a predefined range. As shown in FIG. 6A, for illustrative purposes only, the range can be expressed as (FTIC value (n)-2*std to FTIC value (n)+2*std).

[0059] At 608, the method 600 continues to compare each OTIC data point to the threshold to see if the OTIC data point is within range. According to an exemplary embodiment, if the value of an OTIC data point is outside the predetermined range, the frame associated with this data point is considered to be an OOP frame. By way of example only, as mentioned above, the data sets 506, 508, 510 are out of range. As alluded to above, the predetermined range refers to OTIC data points that are within the examination plane (i.e., the initial plane) of the ROI where the imaging device 110 is located at a particular time during the procedure. These data points are retained (stored and / or transmitted). In contrast, the out-of-range data points are likely to be data points collected during a particular time of the procedure, but are in a different image plane than the initial plane due to the relative motion between the imaging device 110 and the patient's body where the CEUS scan is being performed.

[0060] By way of example, a threshold for determining whether an OITC data point is in range or out of range can be determined using (FTIC value(n)-2*std to FTIC value(n)+2*std). Data points within the range are kept (stored and / or sent to the radiologist / clinician) at 610, while data points beyond the predefined range are OOP frame data points and are removed / discarded at 612. In particular, both the fitted value and the OITC value are used to determine a difference function (diff(n)), the standard deviation being useful for identifying IP or OOP frames.

[0061] FIG. 6B is a flow chart of a method 620 for selecting a representative CEUS frame or short loop at or near a feature point of a TIC curve, according to a representative embodiment. Various aspects and details of FIG. 6B are common to those described in connection with the representative embodiments of FIGS. 1-6A. These common aspects and details may not be repeated to avoid obscuring the currently described representative embodiment. Furthermore, as described above, the method 620 is a module that includes instructions stored in the memory 130. When executed by a processor, the instructions cause the processor to perform the method 620. According to a representative embodiment, a TIC curve is determined at 622, as described above.

[0062] At 624, the method 620 includes, but is not limited to, determining feature points on the TIC curve to be analyzed, such as the start of the TIC curve (e.g., 402), the median or maximum wash-in slope of the wash-in curve (e.g., 404), the peak time of the TIC curve (e.g., 406), the median or minimum wash-out slope of the wash-out curve (e.g., 408), a time point of about 60 seconds based on the American College of Radiology CEUS Liver Imaging, Reporting and Data System (CEUS-LI-RADS), and a time point during the LP or about 120 seconds when considering the ACR CEUS-LI-RAD.

[0063] At 626, a representative short loop or frame is selected at or near the feature point from 624. By selecting a short cine loop or frame from the entire cine loop, data from important portions of the CEUS scan can be more easily isolated for review by the radiologist / clinician. Also, because the image data is reduced, less memory or bandwidth is required to store the data, or to transmit the data, or both.

[0064] At 628, a determination is made whether the selected short loop is an IP loop or an OOP loop. In particular, the method for determining whether the loop contains IP or OOP data is substantially the same as that used to determine whether a single frame contains IP or OOP data. As will be appreciated, since each loop contains multiple frames, the above-described method for determining an IP or OOP loop includes repeating the method for each frame of the loop. According to one representative embodiment, the determination of whether each frame of the loop is IP or OOP is made individually. The IP frames of the loop are stored and the OOP frames of the loop are discarded. Thus, when the short loop is determined to be IP at 628, the method proceeds to 630. Otherwise, the method proceeds to 632.

[0065] 7 is a flow chart of a method 700 for determining whether a frame is an in-plane frame or an out-of-plane frame using changes in NCCC values, according to a representative embodiment. Various aspects and details of FIG. 6B are common to those described in connection with the representative embodiments of FIGS. 1-6A. These common aspects and details may not be repeated to avoid obscuring the currently described representative embodiment. Additionally, as discussed above, the method 700 is a module that includes instructions stored in memory 130. When executed by a processor, the instructions cause the processor to perform the method 700.

[0066] At 702, known motion compensation methods are applied to the entire cineloop, and thereby to a relatively large region including the suspect lesion or the entire image, if necessary.

[0067] At 704, normalized cross-correlation coefficient (NCCC) values ​​are calculated for two adjacent frames of the target lesion region based on the entire motion-compensated CEUS loop, in particular, adjacent frames are frames that are consecutive in time and frame number (e.g., frames (n-1), n, (n+1)).

[0068] According to one representative embodiment, the NCCC value (γ(u,v)) is determined by calculating the cross-correlation in the spatial or frequency domain depending on the size of the image, calculating a local sum by pre-calculating a running sum, and using the local sum to normalize the cross-correlation to obtain the correlation coefficient. This is It can be represented as TIFF2024008910000001.tif2595, where f is the image, TIFF2024008910000002.tif86 is the average of the time, TIFF2024008910000003.tif1111 is the average of f(x,y) in the region under the template.

[0069] In the above equation, f and t are functions in two spatial dimensions (x, y), and the actual values ​​of f(x, y) and t(x, y) are used to determine the NCCC value at (x, y).

[0070] At 706, the method continues with comparing the NCC value calculated at 704 to a predefined threshold. According to a representative embodiment, the NCCC value is calculated for any two adjacent frames of a region of interest (ROI), such as a region of a target lesion area, based on the entire motion compensated CEUS loop. Then, out-of-plane frames are determined based on a threshold comparison and are removed when the NCCC value is outside the threshold range, or frames of a short loop that are selected. By way of example, according to a representative embodiment, the decision of whether a frame is OOP is based on a predefined NCCC value (e.g., 0.75). When the NCCC value is below this threshold, the frame is considered OOP and discarded. All other frames are considered IP and are stored / shared with the clinician reviewing the scan.

[0071] If the NCCC value is sufficiently large at 706, the data point is considered to be in-plane and the data points of these frames are stored and / or transmitted to the radiologist / clinician at 708. If the NCCC value is below a predefined threshold, the frame associated with this data point is considered to be an OOP frame and is discarded at 710.

[0072] As will be appreciated by those skilled in the art having the benefit of this disclosure, the devices, systems, and methods of the present teachings provide for the transmission of echo image data from an ultrasound device. For example, compared to known methods and systems, various aspects of a protocol, including the initiation, duration, and termination of steps in the protocol, can be facilitated during the generation of the protocol, or during the implementation of the protocol, or both. Furthermore, errors that may arise from human interaction with the imaging system can be reduced, thereby reducing the need to repeat a procedure and reducing the time required to complete an imaging procedure. Notably, these advantages are exemplary, and other advances in the field of medical imaging will be apparent to those skilled in the art having the benefit of this disclosure.

[0073] Although the methods, systems, and components for implementing imaging protocols have been described with reference to several exemplary embodiments, it is understood that the words used are not words of limitation, but words of description and illustration. Changes may be made within the scope of the appended claims, as currently stated and amended, without departing from the scope and spirit of the protocol implementation of the present teachings. The foregoing description of the disclosed embodiments is provided to enable those skilled in the art to practice the concepts described in this disclosure. Thus, the subject matter disclosed above should be considered as illustrative and not limiting, and the appended claims are intended to encompass all such modifications, enhancements, and other embodiments that fall within the true spirit and scope of the present disclosure. Thus, to the maximum extent permitted by law, the scope of the present disclosure should be determined by the broadest permissible interpretation of the following claims and their equivalents, and should not be limited or restricted by the foregoing detailed description.

Claims

1. A system for providing ultrasound images, An ultrasound probe adapted to provide the aforementioned ultrasound image, It is a processor, The steps include generating an intensity-versus-time curve for the ultrasound image, The steps include determining the out-of-plane frame of the ultrasound image based on the intensity-time curve, The steps include removing the out-of-plane frames from the ultrasound image based on criteria that provide an optimized set of frames, and A processor configured to perform the following actions: A display configured to communicate with the processor and display an optimized set of frames A system that has

2. In order to determine the out-of-plane frame, the processor further: The step of comparing the intensity-to-time curve (TIC) between the aforementioned ultrasound images. The system according to claim 1, configured to perform the following:

3. In order to compare the TIC between the ultrasound images, the processor further: The steps include: fitting the original TIC curve to determine other TIC curves, The steps include obtaining the difference function between the other TIC curve and the original TIC curve, Steps to determine the mean and standard deviation, The steps include determining whether the difference function in the selected frame is outside a predetermined range, and The system according to claim 2, configured to perform the following:

4. The display is configured to display a time-series set of ultrasound image sources in their entirety, and the system further, A user interface configured to allow selection of the optimized set of frames. The system according to claim 1, having the following features.

5. A computer program product, which, when executed by a processor, the processor, The steps include generating an intensity-versus-time curve for the ultrasound image, The steps include determining the out-of-plane frame of the contrast-enhanced ultrasound image (CEUS) based on the intensity-vs-time curve, Steps include removing the out-of-plane frames from the ultrasound image based on criteria for providing an optimized set of frames, The steps include displaying the optimized set of frames and A computer program product that contains instructions to execute something.

6. When executed by the processor to determine the out-of-plane frame, the instruction further to the processor: Steps to compare intensity-time curves (TIC) A computer program product according to claim 5, which causes to execute.

7. When executed by the processor to compare the TIC between the ultrasound images, the instruction further commands the processor: The steps include: fitting the original TIC curve to determine other TIC curves, The steps include obtaining the difference function between the other TIC curve and the original TIC curve, Steps to determine the mean and standard deviation, The steps include determining whether the difference function in the selected frame is outside a predetermined range, and A computer program product according to claim 6, which causes the execution of the following.

8. When executed by the processor to compare the TIC, the instruction is given to the processor: Steps include displaying the entire set of source ultrasound images in chronological order, A step that allows the user interface to select the set of frames to be optimized, A computer program product according to claim 7, which causes to execute

9. A method for providing an ultrasound image, wherein the method is: The steps include generating an intensity-versus-time curve for the ultrasound image, The steps include determining the out-of-plane frame of the ultrasound image based on the intensity-time curve, Steps include removing the out-of-plane frames from the ultrasound image based on criteria for providing an optimized set of frames, The steps include displaying the optimized set of frames and A method having

10. A step of comparing intensity-to-time curves (TIC). The method according to claim 9, further comprising the above.

11. A step of fitting the curve of the original TIC curve to determine other TIC curves, The steps include obtaining the difference function between the other TIC curve and the original TIC curve, Steps to determine the mean and standard deviation, The steps include determining whether the difference function in the selected frame is outside a predetermined range, and The method according to claim 10, further comprising:

12. A step of displaying the entire set of source ultrasound images that are arranged in a time series, A step that enables the selection of an optimized set of frames in the user interface, and The method according to any one of claims 9 to 11, further comprising the above.

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