Elasticity measurement method, elasticity image-based matching method, and ultrasound imaging system

Abstract

An elasticity measurement method, a matching method based on an elasticity image and an ultrasonic imaging system, the elasticity measurement method comprising: acquiring at least two frames of shear wave elasticity images of a target tissue based on shear wave elasticity imaging; selecting at least one first shear wave elasticity image from the at least two frames of shear wave elasticity images; determining a first target region in the at least one first shear wave elasticity image, and obtaining a first elasticity measurement result according to an elasticity measurement value of the first target region; and determining a second target region in at least one second shear wave elasticity image from the at least two frames of shear wave elasticity images other than the first shear wave elasticity image based on the first target region, and obtaining a second elasticity measurement result according to an elasticity measurement value of the second target region. The present application can automatically measure multiple frames of shear wave elasticity images without the user determining the target region frame by frame, thereby simplifying the operation process.

Description

[0001] Divisional application information This invention patent application is a divisional application of the invention patent application filed on November 30, 2020, with application number 202011379952.0, and entitled "Elasticity Measurement Method, Matching Method Based on Elastic Image and Ultrasonic Imaging System". Technical Field

[0002] This application relates to the field of ultrasound imaging technology, and more specifically to an elasticity measurement method, an elasticity image-based matching method, and an ultrasound imaging system. Background Technology

[0003] Ultrasound elastography has become a hot topic in clinical research in recent years. It mainly reflects the elasticity or hardness of tissues and is increasingly used in the auxiliary detection of tissue cancer lesions, the differentiation of benign and malignant lesions, and the evaluation of prognosis and recovery.

[0004] Ultrasonic elastography primarily reflects the stiffness or softness of tissues by imaging elastic parameters within a region of interest. Over the past two decades, numerous different elastography methods have emerged, such as quasi-static elastography based on strain induced by probe pressure, shear wave elastography or elastic measurement based on shear waves generated by acoustic radiation, and transient elastography based on shear waves generated by external vibrations.

[0005] Shear wave elastography, in particular, uses an ultrasound probe to excite a focused ultrasound beam, generating acoustic radiation force that creates a shear wave source within the tissue, producing transversely propagating shear waves. By identifying and detecting the shear waves generated within the tissue and their propagation parameters, and imaging these parameters, the stiffness differences of the tissue can be quantitatively and visually obtained. Because the shear wave excitation originates from the acoustic radiation force generated by the focused ultrasound beam, it no longer depends on the pressure applied by the operator. Therefore, compared to conventional elastography, shear wave elastography offers improvements in stability and repeatability. Furthermore, the quantitative measurement results of shear waves allow for more objective diagnosis by physicians, making it a widely used elastography method among doctors today.

[0006] Typically, after performing shear wave elastography, doctors use shear wave elastography measurement tools to measure the target region on a single frame of the image, thus obtaining the elasticity measurement result for that region. However, current measurement tools can only measure a single frame of the shear wave elastography image. If multiple frames of shear wave elastography images are to be measured, the target region needs to be plotted multiple times, which is time-consuming and laborious. Summary of the Invention

[0007] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. This summary section is not intended to limit the key features and essential technical features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0008] One embodiment of the present invention provides an elasticity measurement method, the method comprising: Acquire at least two frames of shear wave elastic images of the target tissue based on shear wave elastic imaging; At least one first shear wave elastic image is selected from the at least two shear wave elastic images; A first target region is determined in the first frame of the first shear wave elastic image, and a first elastic measurement result is obtained based on the elastic measurement value of the first target region; Acquire at least two frames of B-mode ultrasound images of the target tissue, wherein the at least two frames of B-mode ultrasound images include a first B-mode ultrasound image corresponding to the first shear wave elastic image and a second B-mode ultrasound image corresponding to the second shear wave elastic image; A fourth target region in the second B-mode ultrasound image is determined based on a third target region in the first B-mode ultrasound image, wherein the third target region corresponds to the same location as the first target region; Based on the location of the fourth target region, a second target region is determined in at least one frame of the second shear wave elastic image (excluding the first shear wave elastic image) among the at least two frames of shear wave elastic images, wherein the second target region corresponds to the same location as the fourth target region. The second elasticity measurement result is obtained based on the elasticity measurement value of the second target area.

[0009] A second aspect of the present invention provides an elasticity measurement method, the method comprising: Acquire at least two frames of elasticity images of the target tissue; Select at least one first elastic image from the at least two elastic images; A first target region is determined in the first elastic image of at least one frame, and a first elasticity measurement result is obtained based on the elasticity measurement value of the first target region; Acquire at least two frames of B-mode ultrasound images of the target tissue, wherein the at least two frames of B-mode ultrasound images include a first B-mode ultrasound image corresponding to the first elastic image and a second B-mode ultrasound image corresponding to the second elastic image; A fourth target region in the second B-mode ultrasound image is determined based on a third target region in the first B-mode ultrasound image, wherein the third target region corresponds to the same location as the first target region; Based on the location of the fourth target region, a second target region is determined in at least one second elastic image (excluding the first elastic image) among the at least two elastic images, wherein the second target region corresponds to the same location as the fourth target region; The second elasticity measurement result is obtained based on the elasticity measurement value of the second target area.

[0010] In one embodiment, the elastic image includes a strain elastic image or a shear wave elastic image.

[0011] A third aspect of this invention provides a matching method based on elastic images, the method comprising: Acquire at least two frames of elasticity images of the target tissue; Select at least one first elastic image from the at least two elastic images; Determine the first target region in the at least one frame of the first elastic image; Acquire at least two frames of B-mode ultrasound images of the target tissue, wherein the at least two frames of B-mode ultrasound images include a first B-mode ultrasound image corresponding to the first elastic image and a second B-mode ultrasound image corresponding to the second elastic image; A fourth target region in the second B-mode ultrasound image is determined based on a third target region in the first B-mode ultrasound image, wherein the third target region corresponds to the same location as the first target region; Based on the location of the fourth target region, a second target region is determined in at least one second elastic image (excluding the first elastic image) among the at least two elastic images, wherein the second target region corresponds to the same location as the fourth target region; The second elasticity measurement result is obtained based on the elasticity measurement value of the second target area.

[0012] A fourth aspect of the present invention provides an ultrasound imaging system, the ultrasound imaging system including an ultrasound probe, a processor, a memory and a display, wherein the memory stores a computer program executed by the processor, and the computer program, when executed by the processor, performs the steps of the method of the foregoing embodiments of the present invention.

[0013] After determining the first target region in the first shear wave elastic image, the elastic measurement method and ultrasonic imaging system of this invention automatically determine the second target region in at least one frame of the second shear wave elastic image based on the first target region, eliminating the need for the user to determine the target region frame by frame, thus simplifying the operation process. Attached Figure Description

[0014] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of the invention in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of the invention and form part of the specification. They are used together with the embodiments of the invention to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0015] Figure 1 A structural block diagram of an ultrasound imaging system according to an embodiment of the present invention is shown; Figure 2 A schematic flowchart of an elasticity measurement method according to an embodiment of the present invention is shown; Figure 3A and Figure 3B A schematic diagram showing a first target region and a second target region having the same shape, size, and position according to an embodiment of the present invention is shown; Figure 4 A schematic diagram illustrating the movement of a third target region to obtain a fourth target region according to an embodiment of the present invention is shown. Figure 5 This diagram illustrates how a fourth target region is obtained based on the position of matching pixels according to an embodiment of the present invention. Figure 6A and Figure 6B A schematic diagram illustrating the identification of a fourth target region around a target measurement location according to an embodiment of the present invention is shown. Figure 7A and Figure 7B This diagram illustrates the determination of a fourth target region based on its similarity to a third target region according to an embodiment of the present invention. Figure 8 A schematic diagram of a display interface according to an embodiment of the present invention is shown; Figure 9 A schematic flowchart of an elasticity measurement method according to an embodiment of the present invention is shown; Figure 10 A schematic flowchart illustrating a matching method based on elastic images according to an embodiment of the present invention is shown. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this application more apparent, exemplary embodiments according to this application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely a part of the embodiments of this application, and not all of the embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein. Based on the embodiments of the present invention described in this application, all other embodiments obtained by those skilled in the art without inventive effort should fall within the protection scope of this application.

[0017] The following description provides numerous specific details to offer a more thorough understanding of this application. However, it will be apparent to those skilled in the art that this application can be practiced without one or more of these details. In other instances, certain technical features well-known in the art have not been described to avoid confusion with this application.

[0018] It should be understood that this application can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. Rather, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of this application to those skilled in the art.

[0019] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising” and / or “including,” when used in this specification, identify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0020] To fully understand this application, a detailed structure will be presented in the following description to illustrate the technical solution proposed in this application. Optional embodiments of this application are described in detail below; however, in addition to these detailed descriptions, this application may have other implementation methods.

[0021] Below, first refer to Figure 1 An ultrasound imaging system according to an embodiment of the present invention is described. Figure 1 A schematic structural block diagram of an ultrasound imaging system 100 according to an embodiment of the present invention is shown.

[0022] like Figure 1 As shown, the ultrasound imaging system 100 includes an ultrasound probe 110, a transmitting circuit 112, a receiving circuit 114, a processor 116, and a display 118. Further, the ultrasound imaging system may also include a transmit / receive selection switch 120 and a beamforming circuit 122, with the transmitting circuit 112 and the receiving circuit 114 connected to the ultrasound probe 110 via the transmit / receive selection switch 120.

[0023] The ultrasonic probe 110 includes multiple transducer elements. These elements can be arranged in a row to form a linear array, or in a two-dimensional matrix to form a planar array. They can also form a convex array. The transducers are used to emit ultrasonic waves based on excitation electrical signals, or to convert received ultrasonic waves into electrical signals. Therefore, each element can be used to achieve the mutual conversion between electrical pulse signals and ultrasonic waves, thereby enabling the emission of ultrasonic waves to the target area of ​​the object being tested, and also to receive ultrasonic wave echoes reflected back from the tissue. During ultrasonic testing, the transmission and reception sequences can be used to control which transducer elements are used to emit ultrasonic waves and which are used to receive ultrasonic waves, or to control the transducer elements to be used in time-slotted manner for emitting ultrasonic waves or receiving ultrasonic wave echoes. Transducer elements participating in ultrasonic wave emission can be simultaneously excited by electrical signals, thus emitting ultrasonic waves simultaneously; or, transducer elements participating in ultrasonic beam emission can be excited by several electrical signals with a certain time interval, thus continuously emitting ultrasonic waves with a certain time interval.

[0024] In one embodiment, the transducer in the ultrasound probe 110 is also used to apply an acoustic radiation force pulse to the target area of ​​the object under test to generate a shear wave. Specifically, during shear wave elastography, the transducer in the ultrasound probe applies an acoustic radiation force pulse to the target area of ​​the object under test to generate a shear wave; the transmitting circuit 112 sends the delayed-focused transmitting pulse to the ultrasound probe 110 through the transmit / receive selection switch 120, and the ultrasound probe 110, excited by the transmitting pulse, transmits an ultrasonic beam to the tissue of the target area of ​​the object under test to track the shear wave; after a certain delay, the ultrasound probe 110 receives the ultrasonic echo reflecting back from the tissue of the target area, carrying tissue information, and converts this ultrasonic echo back into an electrical signal. The receiving circuit 114 receives the electrical signal generated by the ultrasound probe 110, obtains the ultrasound echo signal, and sends these ultrasound echo signals to the beamforming circuit 122. The beamforming circuit 122 performs focusing delay, weighting, and channel summation on the ultrasound echo data, and then sends it to the processor 116. The processor 116 performs elastic imaging processing on the ultrasound echo signal, calculates the elastic parameters used to generate the elastic image, and generates the corresponding shear wave elastic image based on the elastic parameters. The processor 116 can also perform conventional B-mode ultrasound image processing on the ultrasound echo signal to generate a B-mode ultrasound image. The shear wave elastic image or B-mode ultrasound image obtained by the processor 116 can be displayed on the display 118 or stored in the memory 124.

[0025] Optionally, the processor 116 can be implemented as software, hardware, firmware, or any combination thereof, and can use one or more application-specific integrated circuits (ASICs), one or more general-purpose integrated circuits, one or more microprocessors, one or more programmable logic devices, or any combination of the foregoing circuits and / or devices, or other suitable circuits or devices. Furthermore, the processor 116 can control other components in the ultrasound imaging system 100 to perform the corresponding steps of the methods in the various embodiments of this specification.

[0026] The display 118 is connected to the processor 116. The display 118 can be a touch screen, an LCD screen, etc.; or, the display 118 can be an independent display such as an LCD screen or a television, separate from the ultrasound imaging system 100; or, the display 118 can be the screen of an electronic device such as a smartphone or tablet, etc. The number of displays 118 can be one or more. For example, the display 118 may include a main screen and a touch screen, with the main screen primarily used to display ultrasound images and the touch screen primarily used for human-computer interaction.

[0027] The display 118 can display the ultrasound images obtained by the processor 116. Furthermore, while displaying the ultrasound images, the display 118 can also provide a graphical user interface for human-machine interaction. One or more controlled objects can be set on the graphical interface, allowing the user to input operation commands using a human-machine interaction device to control these controlled objects and perform corresponding control operations. For example, icons can be displayed on the graphical interface, and the human-machine interaction device can be used to operate these icons to perform specific functions, such as drawing a region of interest bounding box on the ultrasound image.

[0028] Optionally, the ultrasound imaging system 100 may also include other human-machine interface devices besides the display 118, which are connected to the processor 116. For example, the processor 116 may be connected to the human-machine interface device via an external input / output port, which may be a wireless communication module, a wired communication module, or a combination of both. The external input / output port may also be based on USB, bus protocols such as CAN, and / or wired network protocols.

[0029] The human-computer interaction device may include an input device for detecting user input information. This input information may be, for example, control commands for the timing of ultrasound transmission / reception, operational input commands for drawing points, lines, or boxes on an ultrasound image, or other types of commands. The input device may include one or a combination of several of the following: a keyboard, mouse, scroll wheel, trackball, mobile input device (such as a mobile device with a touchscreen, a mobile phone, etc.), a multi-function knob, etc. The human-computer interaction device may also include an output device such as a printer.

[0030] The ultrasound imaging system 100 may also include a memory 124 for storing instructions executed by the processor, storing received ultrasound echoes, storing ultrasound images, etc. The memory may be a flash memory card, solid-state memory, hard disk, etc. It may be volatile and / or non-volatile memory, removable memory and / or non-removable memory, etc.

[0031] It should be understood that Figure 1 The components included in the ultrasound imaging system 100 shown are merely illustrative and may include more or fewer components. This application is not limiting in this regard.

[0032] The elasticity measurement method, elasticity image-based matching method, and ultrasound imaging system provided in this application are applicable to both humans and various animals; the target tissue can be human target tissue or target tissue of various animals.

[0033] Below, we will refer to Figure 2 A method for measuring elasticity according to an embodiment of the present invention is described. Figure 2 This is a schematic flowchart of an elasticity measurement method 200 according to an embodiment of the present invention.

[0034] like Figure 2 As shown, the elasticity measurement method 200 of this embodiment includes the following steps: In step S210, at least two frames of shear wave elastic images of the target tissue obtained based on shear wave elastic imaging are acquired. In step S220, at least one first shear wave elastic image is selected from the at least two shear wave elastic images; In step S230, a first target region in the first shear wave elastic image of at least one frame is determined, and a first elasticity measurement result is obtained based on the elasticity measurement value of the first target region. In step S240, based on the first target region, a second target region is determined in at least one second shear wave elastic image other than the first shear wave elastic image among the at least two frames of shear wave elastic images, and a second elasticity measurement result is obtained based on the elasticity measurement value of the second target region.

[0035] The elasticity measurement method 200 according to an embodiment of the present invention eliminates the need for the user to repeatedly draw the target region. After determining the first target region in the first shear wave elasticity image, it automatically determines the second target region in at least two other frames of the second shear wave elasticity image based on the first target region. This allows for the measurement of the target region on multiple frames of shear wave elasticity images to obtain multiple elasticity measurement results, avoiding image waste and eliminating the need for the user to repeatedly select the target region, thus simplifying the operation process. The stability of the elasticity measurement results can be observed based on multiple elasticity measurement results, and statistical values ​​can be obtained by combining the elasticity measurement results from multiple frames of shear wave elasticity images, improving the accuracy of shear wave elasticity measurement.

[0036] In step S210, acquiring at least two frames of shear wave elastic images of the target tissue based on shear wave elastography can be achieved by freezing the images after real-time shear wave elastography, thereby obtaining at least two frames of shear wave elastography images. Specifically, the real-time shear wave elastography process includes: controlling an ultrasound probe to generate shear waves propagating within the target tissue, emitting ultrasound waves into the target tissue to track the shear waves propagating within the target tissue, receiving the ultrasound echoes to obtain ultrasound echo signals, and obtaining at least two frames of shear wave elastography images of the target tissue based on the ultrasound echo signals.

[0037] Alternatively, acquiring at least two shear wave elastic images of the target tissue obtained based on shear wave elastography can also be reading at least two shear wave elastic images of the target tissue obtained based on shear wave elastography that have already been stored, such as a video image composed of multiple consecutive shear wave elastic images.

[0038] In one embodiment, in addition to at least two shear wave elastography images, at least two B-mode ultrasound images of the target tissue obtained based on shear wave elastography can also be acquired. The at least two B-mode ultrasound images correspond one-to-one with the at least two shear wave elastography images. Specifically, the at least two B-mode ultrasound images include a first B-mode ultrasound image corresponding to the first shear wave elastography image and a second B-mode ultrasound image corresponding to the second shear wave elastography image.

[0039] For example, in shear wave elastography, the region of interest (ROI) is first determined based on a B-mode ultrasound image. Specifically, a transmitting circuit sends an appropriately delayed electrical signal to the transducer in the ultrasound probe. The transducer converts the electrical signal into ultrasound waves, which are then transmitted to the target tissue of the object being measured. The transducer in the ultrasound probe receives the ultrasound echo returned from the target region and converts it back into an electrical signal to obtain an ultrasound echo signal. After signal amplification, analog-to-digital conversion, and other processing, the signal is transmitted to a beamforming circuit for beamforming. The beamformed ultrasound echo signal is then sent to a processor, which performs logarithmic compression, dynamic range adjustment, and digital scan transformation on the ultrasound echo signal to form a B-mode ultrasound image that reflects the morphology and structure of the target tissue. The processor can output this B-mode ultrasound image to a display for display, facilitating the determination of the ROI within the B-mode ultrasound image for generating the shear wave elastography image.

[0040] In one approach, the user can manually select a region of interest (ROI) bounding box on a B-mode ultrasound image, and the processor determines the location of the ROI based on the detected user input. Alternatively, the location of the ROI can be automatically determined on the B-mode ultrasound image based on relevant machine learning algorithms, i.e., the ROI bounding box is automatically generated. In other examples, the ROI can be obtained through semi-automatic detection. For instance, the location of the ROI on the B-mode ultrasound image can be automatically detected based on machine learning algorithms, and an editable ROI bounding box can be displayed on the B-mode ultrasound image, allowing the user to adjust its height, width, and position using a mouse, touchscreen, or other means to determine the specific location of the ROI.

[0041] Subsequently, the display transmits the coordinates of the identified region of interest (ROI) to the processor. The processor determines the location of the ROI within the tissue based on these coordinates, thus performing shear wave elastography. Specifically, a series of ultrasonic pulses are emitted from an ultrasound probe towards the ROI to generate shear wave propagation based on acoustic radiation force. The transmitting circuit then excites the ultrasound probe to emit ultrasound waves tracking the shear wave towards the identified ROI and receives the echo signals. The processor calculates elasticity measurements of the ROI based on the echo signals, such as at least one of shear wave velocity, Young's modulus, or shear modulus. A shear wave elastography image is then generated based on the distribution of these elasticity measurements. Different colors, grayscale values, or fill methods can be used to identify tissues with different hardness properties within the shear wave elastography image. For example, pseudo-color mapping can be performed on elasticity measurements at multiple locations within the ROI and superimposed onto the ROI frame of a B-mode ultrasound image to form a shear wave elastography image of the ROI.

[0042] For example, elasticity measurements can be calculated as follows: The displacement at a point along the shear wave propagation path is calculated based on the received ultrasonic echo signal. When the displacement at that point is maximum, the shear wave is considered to have reached that point. The propagation path or trajectory of the shear wave can be located by the arrival time at each point, allowing for the plotting of the shear wave trajectory. The slope at each point along the shear wave propagation path can be obtained from the trajectory, and this slope represents the shear wave velocity. Based on the relationship between the shear wave velocity and Young's modulus and shear modulus, other elasticity measurements, such as Young's modulus and shear modulus, can be further calculated after obtaining the shear wave velocity.

[0043] In step S220, the user can select at least one first shear wave elastic image from at least two shear wave elastic images. Specifically, the processor can receive a selection instruction for the first shear wave elastic image and select it from the at least two shear wave elastic images according to the received instruction. Alternatively, the processor can automatically select at least one first shear wave elastic image from the at least two shear wave elastic images based on preset criteria. For example, the first shear wave elastic image may include the first frame, the last frame, a frame that meets the preset requirements, or any frame from the at least two shear wave elastic images. After determining the first shear wave elastic image, the display can show the first shear wave elastic image on the display interface to facilitate the determination of the first target area for shear wave elasticity measurement.

[0044] In step S230, the first target region can be user-specified or automatically determined by the processor. The first target region can be a lesion region or other feature regions. When the user specifies the first target region, the user can determine the first target region in the first shear wave elastic image using an input device such as a mouse or touchscreen. The processor receives the determination instruction for the first target region and determines the first target region in at least one frame of the first shear wave elastic image based on the received instruction. The method for determining the first target region in the first shear wave elastic image can be to use a tracing method to outline the lesion region or other feature regions in the first shear wave elastic image, forming a closed contour line to define the target region, or to draw a conventional ellipse or circular frame to define the first target region. This embodiment of the invention does not limit the shape, size, or position of the first target region. When the processor automatically determines the target area, it can determine the target area based on the elasticity measurement of each pixel in the first shear wave elastic image; the processor can also perform image recognition based on the first B-mode ultrasound image corresponding to the first shear wave elastic image to identify the lesion area or other feature area therein, and take the area corresponding to the identified lesion area or other feature area in the first shear wave elastic image as the first target area.

[0045] Once the first target region is determined, the first elasticity measurement result can be obtained based on the elasticity measurements within that region. As mentioned above, the shear wave elasticity image is generated based on elasticity measurements, with each pixel corresponding to a specific elasticity measurement, such as Young's modulus, shear modulus, or shear wave velocity. After determining the first target region, the elasticity measurements corresponding to all pixels within that region can be obtained, and statistical results such as the average, minimum, maximum, quartile, or standard deviation of all elasticity measurements can be calculated to serve as the first elasticity measurement result.

[0046] In step S240, based on the first target region, a second target region is determined in at least one frame of the second shear wave elastic image other than the first shear wave elastic image, and a second elasticity measurement result is obtained based on the elasticity measurement value of the second target region. The second target region is determined based on the first target region and corresponds to the same or similar location in the tissue. The user only needs to determine the first target region in the first shear wave elastic image to determine at least one second target region, thereby obtaining at least two elasticity measurement results, without needing to select target regions frame by frame. The method for obtaining the second elasticity measurement result based on the elasticity measurement value of the second target region is similar to the method for obtaining the first elasticity measurement result based on the elasticity measurement value of the first target region; that is, the elasticity measurement value of each pixel within the second target region is obtained, and the statistical value of all elasticity measurements is calculated as the second elasticity measurement result.

[0047] There are various methods for determining a second target region based on a first target region. In one embodiment, for continuous shear wave elastic images, a region with the same shape, size, and location as the first target region can be directly determined in the second shear wave elastic image as the second target region. For example, referring to... Figure 3A , Figure 3B ,in Figure 3A The image shows a first target region in a first shear wave elastic image and a corresponding third target region in a first B-mode ultrasound image. Figure 3B The diagram illustrates a second target region in a second shear wave elastography image and a corresponding fourth target region in a second B-mode ultrasound image. The first and second target regions have the same shape, size, and location. When the lesion region or other feature region exhibits almost no displacement or only very slight displacement in multiple shear wave elastography images, measurements can be performed on multiple shear wave elastography images (excluding the first shear wave elastography image) using a measurement frame of the same shape, size, and location. This allows for automated measurement of multiple shear wave elastography images with minimal computational effort.

[0048] In another embodiment, since the shear wave elasticity image corresponds to a B-mode ultrasound image, and the B-mode ultrasound image reflects the morphological structure of the target tissue, the target region for elasticity measurement can be determined based on the B-mode ultrasound image. Specifically, a fourth target region in a second B-mode ultrasound image corresponding to the second shear wave elasticity image can be determined based on a third target region in a first B-mode ultrasound image corresponding to the first shear wave elasticity image, and a second target region in the second shear wave elasticity image can be determined based on the position of the fourth target region. The third target region corresponds to the same position as the first target region, and the fourth target region corresponds to the same position as the second target region.

[0049] As one implementation method, refer to Figure 4 A target tracking method can be used to determine a fourth target region in a second B-mode ultrasound image based on a third target region in a first B-mode ultrasound image. Specifically, the first B-mode ultrasound image within the third target region is extracted as the target image; the positional change of the target image between the first and second B-mode ultrasound images is tracked; and the position of the third target region is moved according to this positional change to obtain the position of the fourth target region. Exemplarily, the positional change includes at least one of translation and rotation, and translation can be in any direction. Any suitable target tracking method can be used to track the positional change of the target image, such as feature recognition, machine learning, or block matching methods.

[0050] According to reference Figure 3A , Figure 3B and Figure 4 The second target region determined by the described method has the same shape and size as the first target region. However, during shear wave elastography, the shape and size of the lesion region or other feature regions may change. Since multiple frames of shear wave elastography images are acquired continuously, even if the shape and size of the lesion region or other feature regions may change slightly, the changes are usually within a certain range. Therefore, the new target region boundary can be determined by tracking the displacement of pixels at the boundary of the third target region, allowing the fourth target region to have different shapes, sizes, and positions from the third target region. This enables automatic measurement of multiple frames of shear wave elastography images even when there are subtle changes in the lesion region or other feature regions.

[0051] Specifically, firstly, pixels at the boundary of the third target region are extracted as target pixels, and matching pixels that match the target pixels are searched in the second B-mode ultrasound image. Then, the location of the boundary of the fourth target region is determined based on the position of the matching pixels in the second B-mode ultrasound image, thus obtaining the fourth target region. The methods for searching for matching pixels that match the target pixels can include feature recognition, machine learning, or block matching methods, etc. Figure 5 As shown, the fourth and third target regions thus determined can have different shapes and sizes, and correspondingly, the second and first target regions can also have different shapes and sizes.

[0052] In another embodiment, an automatic tracing method can be used to determine the fourth target region in the second B-mode ultrasound image based on the third target region. Specifically, when determining the first target region, a determination instruction for the target measurement position can be received based on the first B-mode ultrasound image. The target measurement position is determined according to the determination instruction, and the region around the target measurement position that meets the preset requirements is identified as the third target region. Based on the correspondence between the first B-mode ultrasound image and the first shear wave elastography image and the position of the third target region, the first target region in the first shear wave elastography image can be obtained. Since the displacement of the lesion region or other feature region in the continuously acquired multiple frames of shear wave elastography images is generally small, the target measurement position selected in the first B-mode ultrasound image can be directly used as the target measurement position in at least one other frame of the second B-mode ultrasound image, and the region around the target measurement position that meets the preset requirements is identified in the second B-mode ultrasound image as the fourth target region. For example, the user can select the target measurement position at the center of the third target region, so that even if the target region is displaced in multiple frames of shear wave elastography images, the target measurement position can still be located inside the target region.

[0053] For example, refer to Figure 6A , Figure 6B ,in Figure 6A This shows the target measurement location selected by the user in the first B-mode ultrasound image. The user can draw a box containing the lesion area, such that the center of the box (i.e., Figure 6AThe cross (in the image) is located inside the lesion area, and the position of the cross is used as the target measurement location. The processor automatically traces around the target measurement location to obtain the lesion area, which is then used as the third target area. Based on the correspondence between the first shear wave elastography image and the first B-mode ultrasound image, the first target area in the first shear wave elastography image can be determined. The first target area and the third target area have the same position, size, and shape. The first shear wave elastography image and the first B-mode ultrasound image can be displayed side by side on the display interface, with the outline of the first target area displayed in the first shear wave elastography image and the outline of the third target area displayed in the first B-mode ultrasound image, respectively, to facilitate the user's viewing of the tissue structure and elasticity characteristics of the target area.

[0054] Figure 6B The fourth target region, identified in the second B-mode ultrasound image, and the second target region, identified in the second shear wave elastic image, are shown. Figure 6B The shape and location of the lesion area in the image have changed to some extent, but the target measurement location remains within the lesion area. The processor can perform image recognition around the target measurement location to automatically trace the lesion area and use it as the fourth target area. After determining the fourth target area, the second target area in the second shear wave elastography image can be determined based on the correspondence between the second B-mode ultrasound image and the second shear wave elastography image.

[0055] In reference Figure 6A and Figure 6B In the described example, the target measurement location is located inside the first target region and the second target region. In other examples, the target measurement location may also be outside the first target region, for example, it may surround the first target region. For the second shear wave elastic image, the processor can perform image recognition inside the target measurement location to obtain the second target region.

[0056] Image recognition can identify lesion areas or other feature areas in B-mode ultrasound images. However, a B-mode ultrasound image may contain multiple lesion areas or other feature areas simultaneously. Therefore, in one embodiment, at least two regions to be measured can be identified in a second B-mode ultrasound image. These at least two regions to be measured are compared with a third target region in a first B-mode ultrasound image to obtain the similarity between the third target region and each region to be measured. A fourth target region is then selected from the regions to be measured based on the similarity. For example, the region to be measured with the highest similarity to the third target region can be selected as the fourth target region. This allows for repeated measurements of the same target region.

[0057] Alternatively, a similar approach can be used when selecting the first target region, whereby the processor automatically identifies multiple regions to be tested in the first B-mode ultrasound image, and the user selects a third target region from among these regions. (See reference...) Figure 7A , Figure 7B ,in Figure 7A Multiple regions to be tested identified in the first B-mode ultrasound image are shown, as well as a third target region selected among the multiple regions to be tested. Figure 7B The fourth target region is shown, selected based on its similarity to the third target region.

[0058] By executing steps S210 to S240, a first elasticity measurement result is obtained based on the elasticity measurement value of the first target region, and a second elasticity measurement result is obtained based on the elasticity measurement value of the second target region. After obtaining the first and second elasticity measurement results, at least one of the first and second elasticity measurement results can be displayed. For example, the first and second elasticity measurement results can be directly displayed using tables or images, or statistical values ​​of the first and second elasticity measurement results can be displayed, such as the variance after the average.

[0059] In one embodiment, refer to Figure 8 The trend chart can display at least two of the first and second elasticity measurement results. The horizontal axis of the trend chart represents the imaging time of each frame of the shear wave elasticity image, and the vertical axis represents the elasticity measurement result obtained from measuring each frame of the shear wave elasticity image. Figure 8 The trend chart uses Young's modulus as the elasticity measurement result, but it can also be shear modulus, shear wave velocity, etc. The trend chart reflects the changing trend of the elasticity measurement results of the same target region in multiple frames of shear wave elasticity images, thus reflecting the stability of shear wave elasticity measurement.

[0060] In one embodiment, the trend chart can also be used for human-computer interaction. The user can select a target location on the trend chart. The processor receives the selection instruction for the target location on the trend chart and controls the display to show either a first elasticity measurement result or a second elasticity measurement result corresponding to the target location. That is, if the target location corresponds to a first shear wave elasticity image, the first elasticity measurement result is displayed; if the target location corresponds to a second shear wave elasticity image, the second elasticity measurement result is displayed. (Continue referring to...) Figure 8If a selection instruction for the thirteenth frame of all sixteen shear wave elastic images is received through a trend chart, the average value (Mean), maximum value (Max), minimum value (Min), and variance (SD) of the elasticity measurement corresponding to each pixel in the target area of ​​the thirteenth frame shear wave elastic image will be displayed numerically on one side of the trend chart, thus comprehensively reflecting the relevant information about the elasticity measurement in the target area.

[0061] In one embodiment, upon receiving a selection instruction for a target location on a trend chart, a first shear wave elasticity image or a second shear wave elasticity image corresponding to the target location may also be displayed. That is, if the target location corresponds to the first shear wave elasticity image, the first shear wave elasticity image is displayed; if the target location corresponds to the second shear wave elasticity image, the second shear wave elasticity image is displayed. (Continue referring to...) Figure 8 In addition to displaying shear wave elastic images, it can also display corresponding B-mode ultrasound images. It can also display the location of the target area in both shear wave elastic images and B-mode ultrasound images, such as displaying the outline of the target area.

[0062] In another embodiment, displaying at least one of the first elasticity measurement result and the second elasticity measurement result includes: receiving a selection instruction for a target shear wave elastic image in the first shear wave elastic image and the second shear wave elastic image; and displaying the first elasticity measurement result or the second elasticity measurement result corresponding to the target shear wave elastic image. For example, a user can select and browse at least two obtained shear wave elastic images, and display the corresponding elasticity measurement result when displaying each frame of the shear wave elastic image.

[0063] Based on the above description, after determining the first target region in the first shear wave elastic image, the elastic measurement method 200 of this embodiment of the invention automatically determines the second target region in at least one frame of the second shear wave elastic image based on the first target region, without requiring the user to determine the target region frame by frame, thus simplifying the operation process.

[0064] This invention also provides an ultrasound imaging system, which includes an ultrasound probe, a processor, a memory, and a display. The memory stores a computer program executed by the processor, which, when run by the processor, performs the steps of the elasticity measurement method 200. (See also...) Figure 1 The ultrasound imaging system 100 may include a reference Figure 1The ultrasonic imaging system 100 described herein includes some or all of the following components: ultrasonic probe 110, transmitting circuit 112, receiving circuit 114, processor 116, display 118, transmit / receive selection switch 120, beamforming circuit 122, and memory 124. The descriptions of each component can be found above. The following description focuses on the main functions of the ultrasonic imaging system 100, omitting details already described above.

[0065] Specifically, the processor 116 is used to acquire at least two frames of shear wave elastic images of the target tissue of the object under test; select at least one first shear wave elastic image from the at least two frames of shear wave elastic images; determine a first target region in the at least one first shear wave elastic image, and obtain a first elasticity measurement result based on the elasticity measurement value of the first target region; based on the first target region, determine a second target region in at least one second shear wave elastic image other than the first shear wave elastic image from the at least two frames of shear wave elastic images, and obtain a second elasticity measurement result based on the elasticity measurement value of the second target region.

[0066] Other specific details of the ultrasonic imaging system in this embodiment of the invention can be found in the above description of the elasticity measurement method 200, and will not be repeated here.

[0067] Based on the above description, after determining the first target region in the first shear wave elastic image, the ultrasonic imaging system of this embodiment automatically determines the second target region in at least one frame of the second shear wave elastic image based on the first target region, without requiring the user to determine the target region frame by frame, thus simplifying the operation process.

[0068] Below, we will refer to Figure 9 Describes an elasticity measurement method according to another embodiment of this application. Figure 9 This is a schematic flowchart of an elasticity measurement method 900 according to an embodiment of the present invention. Figure 9 As shown, the elasticity measurement method 900 includes the following steps: In step S910, at least two frames of elasticity images of the target tissue are acquired; In step S920, at least one first elastic image is selected from the at least two elastic images; In step S930, a first target region in the at least one frame of the first elastic image is determined, and a first elastic measurement result is obtained based on the elastic measurement value of the first target region. In step S940, based on the first target region, a second target region is determined in at least one frame of the second elastic image other than the first elastic image in the elastic image, and a second elasticity measurement result is obtained based on the elasticity measurement value of the second target region.

[0069] The elasticity measurement method 900 according to an embodiment of the present invention is generally similar to the elasticity measurement method 200 described above. The main difference is that the elastic image obtained in step S910 is not limited to a shear wave elastic image. For example, the elastic image can be either a shear wave elastic image as described above or a strain elastic image. The implementation of the shear wave elastic image can be understood with reference to the foregoing description. For the strain elastic image, it is achieved through pressure elastic imaging. Specifically, the imaging method mainly involves applying pressure to the target tissue using an ultrasonic probe, acquiring two frames of ultrasonic echo information before and after the target tissue is compressed, and then calculating the displacement of the corresponding position before and after compression using the ultrasonic echo information. This is the spatial position change information of the target tissue at two different times. By calculating the axial gradient of the displacement, the strain value of each point in the target tissue region is obtained. The strain value of each point in the target tissue region is then represented in image form, i.e., the strain elastic image. The strain elastic image can intuitively reflect the difference in softness or elasticity between different tissues. Under the same external force compression, the greater the strain, the softer the tissue; the smaller the strain, the harder the tissue.

[0070] Therefore, the elastic measurement method 900 according to embodiments of the present invention can not only automatically measure multiple frames of shear wave elastic images, but also automatically measure multiple frames of strain elastic images. Apart from this, the elastic measurement method 900 is generally similar to the elastic measurement method 200; for details, please refer to the relevant descriptions above. For the sake of brevity, the same details will not be repeated here.

[0071] This invention also provides an ultrasound imaging system, which includes an ultrasound probe, a processor, a memory, and a display. The memory stores a computer program executed by the processor, which, when run by the processor, performs the steps of the elasticity measurement method 900. (See also...) Figure 1 The ultrasound imaging system 100 may include a reference Figure 1 The ultrasonic imaging system 100 described herein includes some or all of the following components: ultrasonic probe 110, transmitting circuit 112, receiving circuit 114, processor 116, display 118, transmit / receive selection switch 120, beamforming circuit 122, and memory 124. The descriptions of each component can be found above. The following description focuses on the main functions of the ultrasonic imaging system 100, omitting details already described above.

[0072] Specifically, the processor 116 is configured to acquire at least two frames of elastic images of the target tissue, the elastic images including shear wave elastic images or strain elastic images; select at least one first elastic image from the at least two elastic images; determine a first target region in the at least one first elastic image, and obtain a first elastic measurement result based on the elastic measurement value of the first target region; and, based on the first target region, determine a second target region in at least one second elastic image other than the first elastic image from the at least two elastic images, and obtain a second elastic measurement result based on the elastic measurement value of the second target region.

[0073] Based on the above description, after the elasticity measurement method 900 and the ultrasonic imaging system according to the embodiments of the present invention determine the first target region in the first elasticity image, the second target region is automatically determined in at least one frame of the second elasticity image based on the first target region, without requiring the user to determine the target region frame by frame, thus simplifying the operation process.

[0074] Below, we will refer to Figure 10 A matching method based on elastic images according to another embodiment of the present invention is described. Figure 10 This is a schematic flowchart of a matching method 1000 based on elastic images according to an embodiment of the present invention. Figure 10 As shown, the elastic image-based matching method 1000 includes the following steps: In step S1010, at least two frames of elasticity images of the target tissue are acquired; In step S1020, at least one first elastic image is selected from the at least two elastic images; In step S1030, a first target region in the at least one frame of the first elastic image is determined; In step S1040, based on the first target region, a second target region is determined in at least one frame of the second elastic image other than the first elastic image.

[0075] According to an embodiment of the present invention, the elastic image-based matching method 1000 automatically determines the second target region in at least two other frames of the second elastic image after determining the first target region in the first elastic image, without requiring the user to select the target region multiple times, thereby simplifying the operation process.

[0076] In step S1010, the at least two elastic images can be strain elastic images or shear wave elastic images. Obtaining at least two elastic images can be achieved by freezing the images after real-time shear wave elastic imaging or strain elastic imaging, thereby obtaining at least two elastic images of the target tissue. Alternatively, obtaining at least two shear wave elastic images can also be achieved by reading at least two stored elastic images of the target tissue obtained based on shear wave elastic imaging or strain elastic imaging.

[0077] In one embodiment, in addition to at least two elastic images, at least two B-mode ultrasound images of the target tissue can also be acquired based on shear wave elastography or strain elastography, wherein the at least two B-mode ultrasound images correspond one-to-one with the at least two elastic images. Specifically, the at least two B-mode ultrasound images include a first B-mode ultrasound image corresponding to the first elastic image and a second B-mode ultrasound image corresponding to the second elastic image.

[0078] In step S1020, the user can select at least one first elastic image from at least two elastic images. The processor receives a selection instruction for the first elastic image and selects the first elastic image from the at least two elastic images according to the received selection instruction. Alternatively, the processor can automatically select at least one first elastic image from at least two elastic images according to a preset standard.

[0079] In step S1030, the first target region can be user-specified or automatically determined by the processor. The first target region can be a lesion region or other feature regions. When the user specifies the first target region, the processor receives a determination instruction for the first target region and determines the first target region in at least one frame of the first elastic image according to the received determination instruction. When the processor automatically determines the target region, the processor can determine the target region based on the elasticity measurement values ​​of each pixel in the first elastic image, or it can determine the first target region based on the first B-mode ultrasound image corresponding to the first elastic image.

[0080] In step S1040, based on the first target region, a second target region is determined in at least one frame of the second elastic image, excluding the first elastic image. The determined second target region can then be displayed in the second elastic image for user reference or for measurement or analysis of the second elastic image based on the second target region, without requiring the user to select the target region frame by frame.

[0081] In one embodiment, for consecutive elastic images, a region with the same shape, size, and position as the first target region can be directly determined in the second elastic image as the second target region. When the lesion region or other feature region has almost no displacement or only very slight displacement in multiple frames of elastic images, the second target region can be drawn in multiple frames of second elastic images other than the first elastic image using a measurement frame with the same shape, size, and position, thereby achieving automatic determination of the target region in multiple frames of elastic images with only a small amount of computation.

[0082] In another embodiment, since the elasticity image corresponds to the B-mode ultrasound image, and the B-mode ultrasound image reflects the morphological structure of the target tissue, the target region can be determined based on the B-mode ultrasound image. Specifically, a fourth target region in the second B-mode ultrasound image corresponding to the second elasticity image can be determined based on the third target region in the first B-mode ultrasound image corresponding to the first elasticity image, and a second target region in the second elasticity image can be determined based on the position of the fourth target region. The third target region corresponds to the first target region at the same position, and the fourth target region corresponds to the second target region at the same position.

[0083] One approach is to use a target tracking method to determine a fourth target region in a second B-mode ultrasound image based on a third target region in a first B-mode ultrasound image. Specifically, the first B-mode ultrasound image within the third target region is extracted as the target image; the positional change of the target image between the first and second B-mode ultrasound images is tracked; and the position of the third target region is moved according to this positional change to obtain the position of the fourth target region.

[0084] In another embodiment, since the shape and size of the lesion region or other feature regions may change during elastography, the boundary of a new target region can be determined by tracking the displacement of pixels at the boundary of the third target region. This allows the fourth target region to have different shapes, sizes, and positions from the third target region, thereby enabling automatic measurement of multiple frames of elastography images even when there are subtle changes in the lesion region or other feature regions. Specifically, firstly, pixels at the boundary of the third target region are extracted as target pixels, and matching pixels that match the target pixels are searched in the second B-mode ultrasound image. Then, the location of the boundary of the fourth target region is determined based on the position of the matching pixels in the second B-mode ultrasound image, thus obtaining the fourth target region.

[0085] In another embodiment, an automatic tracing method can be used to determine the fourth target region in the second B-mode ultrasound image based on the third target region. Specifically, when determining the first target region, a target location determination instruction can be received based on the first B-mode ultrasound image. The target location is determined according to the target location determination instruction, and the region around the target location that meets preset requirements is identified as the third target region. Based on the correspondence between the first B-mode ultrasound image and the first elastic image and the position of the third target region, the first target region in the first elastic image can be obtained. Since the displacement of the lesion region or other feature region in multiple consecutively acquired elastic images is generally small, the target location selected in the first B-mode ultrasound image can be directly used as the target location in at least one other frame of the second B-mode ultrasound image, and the region around the target location that meets the preset requirements is identified in the second B-mode ultrasound image as the fourth target region. After determining the fourth target region, the second target region in the second elastic image can be determined based on the correspondence between the second B-mode ultrasound image and the second elastic image.

[0086] In another embodiment, at least two regions to be tested can be identified in the second B-mode ultrasound image. These two identified regions are then compared with a third target region in the first B-mode ultrasound image to obtain the similarity between the third target region and each region to be tested. A fourth target region is then selected from the regions to be tested based on the similarity. Optionally, when selecting the first target region, the processor can automatically identify multiple regions to be tested in the first B-mode ultrasound image, and the user can select the third target region from among these multiple regions.

[0087] Based on the above description, after determining a first target region in a first elastic image, the elastic image-based matching method 1000 according to an embodiment of the present invention automatically determines a second target region in at least one frame of a second elastic image based on the first target region, without requiring the user to determine the target region frame by frame. The determined first and second target regions can be displayed in the first and second elastic images in the form of a region of interest box or other suitable form for user reference; or, after determining the first and second target regions, the first and second elastic images can be measured or analyzed based on the first and second target regions. In addition, the elastic image-based matching method 1000 has many similarities to the elasticity measurement methods 200 and 900, which can be referred to in the relevant descriptions above. For brevity, the same details will not be repeated here.

[0088] This invention also provides an ultrasound imaging system, which includes an ultrasound probe, a processor, a memory, and a display. The memory stores a computer program executed by the processor. When the computer program is run by the processor, it performs the steps of a matching method 1000 based on elastic images. (See also...) Figure 1 The ultrasound imaging system 100 may include a reference Figure 1 The ultrasonic imaging system 100 described herein includes some or all of the following components: ultrasonic probe 110, transmitting circuit 112, receiving circuit 114, processor 116, display 118, transmit / receive selection switch 120, beamforming circuit 122, and memory 124. The descriptions of each component can be found above. The following description focuses on the main functions of the ultrasonic imaging system 100, omitting details already described above.

[0089] Specifically, the processor 116 is configured to: acquire at least two frames of elastic images of the target tissue; select at least one first elastic image from the at least two frames of elastic images; determine a first target region in the at least one first elastic image; and, based on the first target region, determine a second target region in at least one second elastic image other than the first elastic image from the at least two frames of elastic images. The elastic images include shear wave elastic images or strain elastic images.

[0090] Based on the above description, after the elastic image-based matching method 1000 and the ultrasound imaging system of the present invention determine the first target region in the first elastic image, the second target region is automatically determined in at least one frame of the second elastic image based on the first target region, without requiring the user to determine the target region frame by frame, thus simplifying the operation process.

[0091] Furthermore, according to embodiments of the present invention, a computer storage medium is also provided, on which program instructions are stored. When executed by a computer or processor, these program instructions are used to perform corresponding steps of the elasticity measurement method 200, elasticity measurement method 900, or elasticity image-based matching method 1000 of the present invention. The storage medium may, for example, include a memory card of a smartphone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disc read-only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.

[0092] Furthermore, according to embodiments of the present invention, a computer program is also provided, which can be stored on a cloud or local storage medium. When this computer program is run by a computer or processor, it is used to perform the corresponding steps of the elasticity measurement method of the embodiments of the present invention.

[0093] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of this application. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of this application. All such changes and modifications are intended to be included within the scope of this application as claimed in the appended claims.

[0094] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0095] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0096] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0097] Similarly, it should be understood that, in order to streamline this application and aid in understanding one or more of the various inventive aspects, features of this application may sometimes be grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of this application. However, this approach should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with features fewer than all features of a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0098] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or elements of any method or apparatus so disclosed may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0099] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0100] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some modules according to embodiments of the present invention. This application can also be implemented as an apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such an implementation of this application can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0101] It should be noted that the above embodiments are illustrative of this application and not limiting of it, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0102] The above description is merely a specific embodiment or illustration of the embodiments of this application. The scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. The scope of protection of this application shall be determined by the scope of the claims.

Claims

1. A method for measuring elasticity, characterized in that, The method includes: Acquire at least two frames of shear wave elastic images of the target tissue based on shear wave elastic imaging; At least one first shear wave elastic image is selected from the at least two shear wave elastic images; A first target region is determined in the first frame of the first shear wave elastic image, and a first elastic measurement result is obtained based on the elastic measurement value of the first target region; Acquire at least two frames of B-mode ultrasound images of the target tissue, the at least two frames of B-mode ultrasound images including a first B-mode ultrasound image corresponding to the first shear wave elastic image and a second B-mode ultrasound image corresponding to the second shear wave elastic image; A fourth target region in the second B-mode ultrasound image is determined based on a third target region in the first B-mode ultrasound image, wherein the third target region corresponds to the same location as the first target region; Based on the location of the fourth target region, a second target region is determined in at least one frame of the second shear wave elastic image (excluding the first shear wave elastic image) among the at least two frames of shear wave elastic images, wherein the second target region corresponds to the same location as the fourth target region. The second elasticity measurement result is obtained based on the elasticity measurement value of the second target area.

2. The method according to claim 1, characterized in that, The acquisition of at least two frames of shear wave elastic images of the target tissue based on shear wave elastic imaging includes: A shear wave propagating within the target tissue is generated; ultrasound waves are emitted towards the target tissue to track the propagating shear wave; the ultrasound echoes are received to obtain an ultrasound echo signal; and at least two frames of shear wave elasticity images of the target tissue are obtained based on the ultrasound echo signal; or, Read at least two frames of shear wave elastic images of the target tissue obtained from shear wave elastic imaging that have been stored.

3. The method according to claim 1, characterized in that, Selecting at least one first shear wave elastic image from the at least two shear wave elastic images includes: Receive a selection instruction for the first shear wave elastic image, and select the first shear wave elastic image from the at least two frames of shear wave elastic images according to the received selection instruction.

4. The method according to claim 1, characterized in that, Determining the first target region in the at least one frame of the first shear wave elastic image includes: Receive a determination instruction for the first target region, and determine the first target region in the at least one frame of the first shear wave elastic image according to the received determination instruction.

5. The method according to claim 1, characterized in that, Determining the fourth target region in the second B-mode ultrasound image based on the third target region in the first B-mode ultrasound image includes: Extract the first B-mode ultrasound image within the third target region as the target image; Track the positional changes of the target image between the first B-mode ultrasound image and the second B-mode ultrasound image; The position of the third target area is moved according to the position change to obtain the position of the fourth target area.

6. The method according to claim 5, characterized in that, The positional changes include translation and / or rotation.

7. The method according to claim 1, characterized in that, Determining the fourth target region in the second B-mode ultrasound image based on the third target region in the first B-mode ultrasound image includes: Extract the pixels at the boundary of the third target region as target pixels; Search for matching pixels in the second B-mode ultrasound image that match the target pixel; The location of the boundary of the fourth target region is determined based on the position of the matching pixel in the second B-mode ultrasound image, so as to obtain the fourth target region.

8. The method according to claim 1, characterized in that, Determining the fourth target region in the second B-mode ultrasound image based on the third target region in the first B-mode ultrasound image includes: Based on the first B-mode ultrasound image, a command to determine the target measurement location is received, and the target measurement location is determined according to the command to determine the target measurement location. The third target region is a region around the target measurement location that meets preset requirements. In the second B-mode ultrasound image, a region around the target measurement location that meets the preset requirements is identified as the fourth target region.

9. The method according to claim 1, characterized in that, Determining the fourth target region in the second B-mode ultrasound image based on the third target region in the first B-mode ultrasound image includes: At least two regions to be tested are identified in the second B-mode ultrasound image; The at least two regions to be tested are compared with the third target region to obtain the similarity between the third target region and each of the regions to be tested; Based on the similarity, the fourth target region is selected in the region to be tested.

10. The method according to claim 1, characterized in that, Also includes: Display at least one of the first elasticity measurement result and the second elasticity measurement result, and / or display the statistical values ​​of the first elasticity measurement result and the second elasticity measurement result.

11. The method according to claim 10, characterized in that, The display of at least one of the first elasticity measurement result and the second elasticity measurement result includes: At least two of the first elasticity measurement results and the second elasticity measurement results are displayed in the form of a trend chart.

12. The method according to claim 11, characterized in that, Also includes: Receive a selection instruction for the target location of the trend chart; Display the first elasticity measurement result or the second elasticity measurement result corresponding to the target location.

13. The method according to claim 12, characterized in that, Also includes: Display the first shear wave elastic image or the second shear wave elastic image corresponding to the target location.

14. The method according to claim 11, characterized in that, The display of at least one of the first elasticity measurement result and the second elasticity measurement result includes: Receive a selection instruction for a target shear wave elastic image in the first shear wave elastic image and the second shear wave elastic image; Display the first elasticity measurement result or the second elasticity measurement result corresponding to the elastic image of the target shear wave.

15. A method for measuring elasticity, characterized in that, The method includes: Acquire at least two frames of elasticity images of the target tissue; Select at least one first elastic image from the at least two elastic images; A first target region is determined in the first elastic image of at least one frame, and a first elasticity measurement result is obtained based on the elasticity measurement value of the first target region; Acquire at least two frames of B-mode ultrasound images of the target tissue, wherein the at least two frames of B-mode ultrasound images include a first B-mode ultrasound image corresponding to the first elastic image and a second B-mode ultrasound image corresponding to the second elastic image; A fourth target region in the second B-mode ultrasound image is determined based on a third target region in the first B-mode ultrasound image, wherein the third target region corresponds to the same location as the first target region; Based on the location of the fourth target region, a second target region is determined in at least one second elastic image (excluding the first elastic image) among the at least two elastic images, wherein the second target region corresponds to the same location as the fourth target region; The second elasticity measurement result is obtained based on the elasticity measurement value of the second target area.

16. The method according to claim 15, characterized in that, The elastic image includes a strain elastic image or a shear wave elastic image.

17. A matching method based on elastic images, characterized in that, The method includes: Acquire at least two frames of elasticity images of the target tissue; Select at least one first elastic image from the at least two elastic images; Determine the first target region in the at least one frame of the first elastic image; Acquire at least two frames of B-mode ultrasound images of the target tissue, wherein the at least two frames of B-mode ultrasound images include a first B-mode ultrasound image corresponding to the first elastic image and a second B-mode ultrasound image corresponding to the second elastic image; A fourth target region in the second B-mode ultrasound image is determined based on a third target region in the first B-mode ultrasound image, wherein the third target region corresponds to the same location as the first target region; Based on the location of the fourth target region, a second target region is determined in at least one second elastic image (excluding the first elastic image) among the at least two elastic images, wherein the second target region corresponds to the same location as the fourth target region; The second elasticity measurement result is obtained based on the elasticity measurement value of the second target area.

18. The method according to claim 17, characterized in that, The elastic image includes a strain elastic image or a shear wave elastic image.

19. An ultrasound imaging system, characterized in that, The ultrasound imaging system includes an ultrasound probe, a processor, a memory, and a display. The memory stores a computer program that is run by the processor, and the computer program, when run by the processor, performs the steps of the method according to any one of claims 1-18.

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