WO2022141257A1 - 一种应变弹性成像方法、装置以及存储介质 - Google Patents

一种应变弹性成像方法、装置以及存储介质 Download PDF

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WO2022141257A1
WO2022141257A1 PCT/CN2020/141641 CN2020141641W WO2022141257A1 WO 2022141257 A1 WO2022141257 A1 WO 2022141257A1 CN 2020141641 W CN2020141641 W CN 2020141641W WO 2022141257 A1 WO2022141257 A1 WO 2022141257A1
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strain
region
target tissue
ultrasonic
interest
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PCT/CN2020/141641
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English (en)
French (fr)
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周迪
李双双
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深圳迈瑞生物医疗电子股份有限公司
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Priority to PCT/CN2020/141641 priority Critical patent/WO2022141257A1/zh
Priority to CN202080103721.9A priority patent/CN116096298A/zh
Publication of WO2022141257A1 publication Critical patent/WO2022141257A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings

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  • the present application relates to the technical field of ultrasonic imaging, and more particularly to a strain elastography imaging method, device and storage medium.
  • Strain elastography has been widely used in clinical research and diagnosis in recent years. Strain elastography uses the probe to press the tissue, and calculates the displacement and strain of the tissue in real time to reflect the elasticity-related parameters of the tissue in the imaging area and image it. It can qualitatively reflect the degree of softness and hardness of the lesion relative to the surrounding tissue, and it is usually used in the clinical practice of thyroid, breast, musculoskeletal and other aspects. Judging the degree of tissue softness and hardness can effectively assist in the diagnosis and evaluation of cancer lesions, benign and malignant tumors, and postoperative recovery.
  • Strain elasticity images generally use different colors to represent different tissue hardness or strain values.
  • strain elasticity algorithms use the average strain of the entire imaging area as a benchmark to color map and convert the imaging area.
  • target tissues such as thyroid and breast
  • the strain values of these tissue areas are often very different from the target tissue. , appearing as extremely soft or extremely hard in the strain image, resulting in a shift in the mean strain value of the entire imaging area, and using the mean strain value for color mapping, the normal target tissue in the strain image will appear to be too hard or soft, reducing the image reliability, which seriously affects the image quality.
  • a strain elastography method includes: controlling an ultrasonic probe to transmit ultrasonic waves to a tissue to be measured of a target object, receiving echoes of the ultrasonic waves, and acquiring ultrasonic echoes based on the echoes of the ultrasonic waves data; generate an ultrasound image based on the ultrasound echo data, and acquire a region of interest in the ultrasound image and a target tissue region in the region of interest; calculate the target tissue region based on the ultrasound echo data Strain and the strain of the region of interest; image feature mapping is performed on the strain of the region of interest based on the strain of the target tissue region to generate and display a strain elastic image of the region of interest.
  • a strain elastography method includes: controlling an ultrasonic probe to transmit a first ultrasonic wave to a tissue to be measured of a target object, receiving an echo of the first ultrasonic wave, and based on the first ultrasonic wave obtain first ultrasound echo data; generate an ultrasound image based on the first ultrasound echo data, and obtain a region of interest in the ultrasound image and a target tissue region in the region of interest; control the ultrasound probe At least transmit a second ultrasonic wave to the sub-tissue corresponding to the target tissue region in the tissue to be tested, receive the echo of the second ultrasonic wave, and obtain second ultrasonic echo data based on the echo of the second ultrasonic wave; The second ultrasonic echo data calculates the strain of the target tissue region and the strain of the region of interest; image feature mapping is performed on the strain of the region of interest based on the strain of the target tissue region to generate and display the strain of the region of interest. Strain elasticity image of the region of interest described.
  • a strain elastography method comprising: providing a method for selecting a strain elastography mode; and controlling an ultrasonic probe to emit ultrasonic waves to a tissue to be measured of a target object based on the selection of the strain elastography mode , receive the echo of the ultrasonic wave, obtain ultrasonic echo data based on the echo of the ultrasonic wave; generate an ultrasonic image based on the ultrasonic echo data, and acquire the target tissue area in the ultrasonic image; based on the ultrasonic echo
  • the wave data calculates the strain of the target tissue area; a strain elasticity image of the target tissue area is generated and displayed based on the strain of the target tissue area.
  • a strain elastography method comprising: providing a selection method of an ultrasonic imaging mode and a selection method of a strain elastography mode; and controlling an ultrasonic probe to a target object based on the selection of the ultrasonic imaging mode
  • the tissue to be tested transmits ultrasonic waves, receives the echoes of the ultrasonic waves, and obtains ultrasonic echo data based on the echoes of the ultrasonic waves; generates an ultrasonic image based on the ultrasonic echo data, and acquires the target tissue area in the ultrasonic image.
  • a strain elastography device in yet another aspect of the present application, includes an ultrasonic probe, a transmitting circuit, a receiving circuit and a processor, wherein: the transmitting circuit is used to excite the ultrasonic probe to the tissue to be measured of the target object transmitting ultrasonic waves; the receiving circuit is used to control the ultrasonic probe to receive ultrasonic echoes returned from the tissue to be tested to obtain ultrasonic echo signals; the processor is used to generate ultrasonic image data according to the ultrasonic echo signals ; The processor is further configured to execute the above strain elastography method.
  • a storage medium is provided, and a computer program is stored on the storage medium, and the computer program executes the above strain elastography method when running.
  • the strain elasticity imaging method, device, and storage medium generate a strain elasticity image of the target tissue region or a region of interest including the target tissue region based on the strain value of the target tissue region, which can reduce or even avoid other tissue or The strain value of the region affects the strain image of the target tissue, thereby improving the quality and reliability of strain elastography.
  • FIG. 1 shows a schematic diagram of a strain elasticity image obtained by an existing strain elasticity imaging method.
  • FIG. 2 is a schematic diagram illustrating the occurrence of deviation in the strain elasticity image obtained by the existing strain elasticity imaging method.
  • FIG. 3 shows a schematic block diagram of an exemplary ultrasound imaging apparatus for implementing the strain elastography method according to an embodiment of the present application.
  • FIG. 4 shows a schematic flowchart of a strain elastography method according to an embodiment of the present application.
  • 5A and 5B are schematic diagrams illustrating an example of identifying a segmentation target region in a strain elastography method according to an embodiment of the present application.
  • FIG. 6 is a schematic diagram illustrating another example of identifying a segmented target region in a strain elastography method according to an embodiment of the present application.
  • FIGS. 7A , 7B and 7C are schematic diagrams illustrating still another example of identifying a segmented target region in a strain elastography method according to an embodiment of the present application.
  • FIG. 8 shows a schematic diagram of an example of a color mapping scheme in a strain elastography method according to an embodiment of the present application.
  • FIG. 9 shows a schematic diagram of another example of a color mapping scheme in a strain elastography method according to an embodiment of the present application.
  • FIG. 10 shows a schematic diagram of an example of a display scheme in a strain elastography method according to an embodiment of the present application.
  • FIG. 11 shows a schematic flowchart of a strain elastography method according to another embodiment of the present application.
  • FIG. 12 shows a schematic flowchart of a strain elastography method according to still another embodiment of the present application.
  • FIGS. 13A and 13B illustrate exemplary schematic diagrams of a display scheme in a strain elastography method according to still another embodiment of the present application.
  • FIG. 14 shows a schematic flowchart of a strain elastography method according to yet another embodiment of the present application.
  • FIG. 15 shows a schematic block diagram of a strain elastography apparatus according to an embodiment of the present application.
  • Fig. 1 shows a schematic diagram of a strain elasticity image obtained by an existing strain elasticity imaging method. As shown in Fig. 1, taking the average strain value in the imaging region R1 (also called the region of interest) as a benchmark, the The imaging region R1 is color-mapped and converted to obtain a strain elasticity image.
  • Color 1, color 2, and color 3 in the strain elasticity image represent hard, normal, and soft tissues, respectively (color 1, color 2, and color 3 may correspond to red, green, and blue, respectively, but because of the The drawing is required to be a grayscale image, so the color cannot be shown in Figure 1, but the color can be set and seen in practical applications).
  • the tissue is shown as color 2, the tissue with a strain value greater than the average value is shown as color 3, and the tissue less than the average value is shown as color 1, and the depth of the color represents the degree of softness or hardness of the tissue.
  • FIG. 2 shows a schematic diagram of the occurrence of deviation in the strain elasticity image obtained by the existing strain elasticity imaging method.
  • tissue structure image on the left side of Figure 2 in addition to target tissues such as thyroid and breast, there are blood vessels, dark areas and some other tissues in the imaging area R2.
  • the strain values of these tissue areas are often very different from those of the target tissue.
  • Strain images appear to be extremely soft or extremely hard, causing a shift in the mean strain across the imaged area.
  • the strain elasticity image on the right side of Figure 2 is obtained by color mapping with this mean strain value. It can be seen that the normal target tissue in the strain elasticity image will be hard or soft, which reduces the reliability of the image and seriously affects the image quality.
  • the present application provides a strain elastography solution.
  • strain elastography color mapping is not performed based on the average strain of the entire imaging region (region of interest), but the strain value in the target tissue region is used.
  • Generating strain elastic images for benchmarks can avoid the problems shown in Figure 2 and improve the reliability of the strain elastic images. The following description will be made with reference to FIGS. 3 to 15 .
  • FIG. 3 shows a schematic structural block diagram of an exemplary ultrasonic imaging apparatus 10 for implementing the strain elastography method according to the embodiment of the present application.
  • the ultrasound imaging apparatus 10 may include an ultrasound probe 100 , a transmit/receive selection switch 101 , a transmit/receive sequence controller 102 , a processor 103 , a display 104 and a memory 105 .
  • the transmit/receive sequence controller 102 can excite the ultrasonic probe 100 to transmit ultrasonic waves to a target object (target object), and can also control the ultrasonic probe 100 to receive ultrasonic echoes returned from the target object, thereby obtaining ultrasonic echo signals/data.
  • the processor 103 processes the ultrasound echo signals/data to obtain tissue-related parameters and ultrasound images of the target object.
  • the ultrasound images obtained by the processor 103 may be stored in the memory 105 , and these ultrasound images may be displayed on the display 104 .
  • the display 104 of the aforementioned ultrasound imaging device 10 may be a touch display screen, a liquid crystal display screen, or the like, or may be an independent display device such as a liquid crystal display, a TV, or the like independent of the ultrasound imaging device 10 , or It is a display screen on electronic devices such as mobile phones and tablet computers.
  • the memory 105 of the aforementioned ultrasonic imaging device 10 may be a flash memory card, a solid-state memory, a hard disk, or the like.
  • Embodiments of the present application further provide a computer-readable storage medium, where the computer-readable storage medium stores a plurality of program instructions, and after the plurality of program instructions are called and executed by the processor 103, the strains in the various embodiments of the present application can be executed. Some or all or any combination of steps in an elastography method.
  • the computer-readable storage medium may be the memory 105, which may be a non-volatile storage medium such as a flash memory card, a solid-state memory, and a hard disk.
  • the processor 103 of the aforementioned ultrasound imaging apparatus 10 may be implemented by software, hardware, firmware, or a combination thereof, and may use a circuit, a single or multiple application specific integrated circuits (ASIC), a single or General-purpose integrated circuits, single or multiple microprocessors, single or multiple programmable logic devices, or a combination of the foregoing circuits or devices, or other suitable circuits or devices, thereby enabling the processor 103 to perform various embodiments Corresponding steps in the strain elastography method.
  • ASIC application specific integrated circuits
  • microprocessors single or multiple programmable logic devices
  • a combination of the foregoing circuits or devices or other suitable circuits or devices
  • FIG. 4 shows a schematic flowchart of a strain elastography method 400 according to an embodiment of the present application. As shown in FIG. 4, the strain elastography method 400 includes the following steps:
  • step S410 the ultrasonic probe is controlled to transmit ultrasonic waves to the tissue to be tested of the target object, the echoes of the ultrasonic waves are received, and ultrasonic echo data is acquired based on the echoes of the ultrasonic waves.
  • step S420 an ultrasound image is generated based on the ultrasound echo data, and a region of interest in the ultrasound image and a target tissue region in the region of interest are acquired.
  • step S430 the strain of the target tissue region and the strain of the region of interest are calculated based on the ultrasound echo data.
  • step S440 image feature mapping is performed on the strain of the region of interest based on the strain of the target tissue region to generate and display a strain elasticity image of the region of interest.
  • the purpose of controlling the ultrasound probe to emit ultrasound to the tissue to be measured (ie, the tissue for strain elastography) of the target object is to acquire ultrasound images (such as tissue structure images, etc.).
  • ultrasound images such as tissue structure images, etc.
  • a region of interest for performing strain elasticity imaging can be acquired, and a target tissue region in the region of interest can be acquired.
  • the target tissue area is different based on the different tissues to be tested. For example, when the aforementioned tissue to be tested is thyroid, the target tissue region is the region where the thyroid tissue is located; when the aforementioned tissue to be tested is the breast, the target tissue region is the region where the breast tissue is located, and so on.
  • the region of interest includes not only the target tissue region, but also some non-target tissue regions (such as the aforementioned blood vessels, dark areas, and some other tissues), the target tissue region in the region of interest can be acquired for acquiring
  • the strain value of the target tissue region is subjected to image feature mapping (such as color mapping, etc.) to obtain a strain elasticity image with higher reliability.
  • acquiring the target tissue region in the region of interest in the ultrasound image may include: automatically identifying and segmenting the target tissue region in the ultrasound image corresponding to the tissue to be tested . 5A, 5B and 6 are described below.
  • FIGS. 5A and 5B are schematic diagrams illustrating an example of identifying a segmentation target region in a strain elastography method according to an embodiment of the present application.
  • an image segmentation method based on edge detection is shown to identify and segment target tissue regions in an ultrasound image.
  • the discontinuity in the ultrasound image due to gray level or structural mutation is the edge.
  • Edge detection algorithms such as differential operators detect such discontinuities, thereby realizing the identification and segmentation of target tissue and other tissue regions within the region of interest.
  • the segmentation results are shown in Figure 5B.
  • the region T1 is the segmented target tissue region.
  • FIG. 6 is a schematic diagram illustrating another example of identifying a segmented target region in a strain elastography method according to an embodiment of the present application.
  • a machine learning-based method is shown to identify and segment target tissue regions in an ultrasound image.
  • machine learning methods include but are not limited to pattern recognition, deep learning, etc., to identify and segment the target tissue area in the ultrasound image.
  • the segmentation result is shown in Figure 6, and the area T2 is the segmented target tissue area.
  • acquiring the target tissue region in the region of interest in the ultrasound image may include: semi-automatically identifying and segmenting the target tissue corresponding to the tissue to be tested in the ultrasound image area.
  • semi-automatic can be understood as a combination of automatic and user manual methods, which is also easy to achieve accurate identification and segmentation results.
  • semi-automatically identifying and segmenting the target tissue region corresponding to the tissue to be tested in the ultrasound image may include: displaying the ultrasound image, and acquiring a reference region selected by the user in the ultrasound image. ; Calculate and extract the features of the reference region; identify and segment the target tissue region corresponding to the tissue to be measured in the ultrasound image according to the principle of feature consistency or feature similarity. 7A, 7B and 7C are described below.
  • FIG. 7A , 7B and 7C are schematic diagrams illustrating still another example of identifying a segmented target region in a strain elastography method according to an embodiment of the present application.
  • the user can first manually select or trace any target tissue in the ultrasound image, and the selection methods can include but are not limited to clicking, tracing, circle frame, box, etc., wherein Fig. 7A shows What is shown is a target tissue T3 obtained by the user clicking on the selection circle, and FIG. 7B shows a target tissue T4 obtained by manually tracing the user.
  • the system can automatically calculate and extract the relevant features (including but not limited to grayscale, texture, variance, etc.) of the region selected by the user in Figure 7A (or Figure 7B ), and automatically identify and segment the corresponding features according to the principle of consistency or proximity of the features.
  • the tissue area selected by the user with the same or close characteristics is used as the target tissue area.
  • the T5 area in Figure 7C is the target tissue area identified and segmented. It can be seen that the user-selected area T3 is included in the target tissue area. Inside.
  • acquiring the target tissue region in the region of interest in the ultrasound image may include: displaying the ultrasound image, and acquiring selected and selected user selected and selected ultrasound images in the ultrasound image The target tissue area corresponding to the tissue to be tested.
  • the user manually determines the target tissue region corresponding to the tissue to be tested, and the target tissue region can be obtained based on user input.
  • strain within the target tissue region can be calculated (such as based on radio frequency (RF) data or quadrature modulation (IQ) data within the target tissue region); furthermore, since strain elastography is performed on the region of interest , so that strains in regions other than the target tissue region in the region of interest can also be obtained.
  • the strain generated by the tissue may be generated by the pressure of the probe, or may be generated by the motion of the tissue itself, for example, the strain generated by the motion of small organs such as musculoskeletal, thyroid, uterus, and blood vessels.
  • image feature mapping (such as color mapping) is performed on the strain in the region of interest to obtain a strain elastic image of the region of interest.
  • performing image feature mapping on the strain of the region of interest based on the strain of the target tissue region may include: generating a strain reference value based on the strain of the target tissue region, and using the strain reference Image feature mapping is performed on the strain of the region of interest as the reference value.
  • the strain reference value may be the mean value of the strain of the target tissue area, or may be any other value that can reflect the strain characteristics of the target tissue area.
  • the image feature mapping performed on the strain of the region of interest based on the strain reference value may be color mapping, or other mappings capable of reflecting different strain values in the image.
  • performing image feature mapping on the strain of the region of interest based on the strain reference value may include: determining a strain range according to the strain reference value, two of the strain ranges The boundary values are respectively smaller than and larger than the strain reference value; the strain of the region of interest is mapped to a gray value according to the strain range in a linear mapping relationship; and the gray value is converted into a corresponding color.
  • the position where the strain in the region of interest is in the strain range can be mapped to a gray value within a preset range; the position where the strain in the region of interest exceeds the strain range can be mapped to the gray value of the preset range. Boundary value. It will be described below with reference to FIG. 8 .
  • FIG. 8 shows a schematic diagram of an example of a color mapping scheme in a strain elastography method according to an embodiment of the present application.
  • a certain strain range smaller than and greater than the strain mean value is selected, and the position of the strain in the region of interest within the strain range is linearly related , which is mapped to a grayscale value of 0-255, and the strain value beyond this range is mapped to 0 or 255.
  • the grayscale value is converted to the corresponding color displayed in the strain image.
  • the mapping relationship is shown in Figure 8.
  • performing image feature mapping on the strain of the region of interest based on the strain reference value may include: determining a strain range according to the strain reference value, two of the strain ranges The boundary values are respectively smaller than and larger than the strain reference value; the strain of the region of interest is mapped to a gray value according to the strain range in a nonlinear mapping relationship; and the gray value is converted into a corresponding color.
  • the position where the strain in the region of interest is in the strain range can be mapped to a gray value within a preset range; the position where the strain in the region of interest exceeds the strain range can be mapped to the gray value of the preset range. Boundary value. It will be described below with reference to FIG. 9 .
  • FIG. 9 shows a schematic diagram of another example of a color mapping scheme in a strain elastography method according to an embodiment of the present application.
  • a certain strain range smaller than and larger than the average strain value is selected, and the position where the strain in the region of interest is within the strain range is calculated as a nonlinear
  • the relationship is mapped to a grayscale value of 0-255, and the strain value beyond this range is mapped to 0 or 255.
  • the grayscale value is converted to the corresponding color displayed in the strain image.
  • the mapping relationship is shown in Figure 9.
  • FIG. 10 shows a schematic diagram of an example of a display scheme in a strain elastography method according to an embodiment of the present application.
  • FIG. 10 after identifying and segmenting the target tissue region T in the region of interest R, according to the identification result, calculate the mean strain value of the target tissue region T, and use the strain mean value as the benchmark to carry out the entire region of interest R. Color mapping and strain imaging resulted in the strain elastic image M of the region of interest shown on the right side of Figure 10.
  • the strain elastic image M of the region of interest R is mapped based on the average strain in the target tissue region T, the strain values of other tissues or regions in the region of interest can be reduced or even avoided. It affects the display of the target tissue strain image, thereby improving the quality and reliability of strain elastography.
  • the strain elasticity imaging method 400 generates a strain elasticity image of the region of interest including the target tissue region based on the strain value of the target tissue region, which can reduce or even avoid other tissues in the region of interest
  • the strain value of the or region has an impact on the target tissue strain image, thereby improving the quality and reliability of strain elastography.
  • the strain elastography method 1100 may include the following steps:
  • step S1110 the ultrasonic probe is controlled to transmit the first ultrasonic wave to the tissue to be tested of the target object, receive the echo of the first ultrasonic wave, and obtain first ultrasonic echo data based on the echo of the first ultrasonic wave.
  • step S1120 an ultrasound image is generated based on the first ultrasound echo data, and a region of interest in the ultrasound image and a target tissue region in the region of interest are acquired.
  • step S1130 the ultrasonic probe is controlled to transmit the second ultrasonic wave to at least the sub-tissue corresponding to the target tissue region in the tissue to be tested, receive the echo of the second ultrasonic wave, and obtain the first ultrasonic wave based on the echo of the second ultrasonic wave. 2. Ultrasonic echo data.
  • step S1140 the strain of the target tissue region and the strain of the region of interest are calculated based on the second ultrasound echo data.
  • step S1150 image feature mapping is performed on the strain of the region of interest based on the strain of the target tissue region to generate and display a strain elasticity image of the region of interest.
  • the strain elastography method 1100 according to the embodiment of the present application is generally similar to the strain elastography method 400 according to the embodiment of the present application described above.
  • the strain elastography method 1100 and the strain elastography method 400 will not be repeated here. are similar in detail, only the differences are described.
  • the difference between the two is that in the strain elastography method 400 according to the embodiment of the present application, the data source for generating the ultrasound image and the data source for calculating the strain are the same data source, while in the strain elastography method according to the embodiment of the present application, the data source for generating the ultrasonic image and the data source for calculating the strain are the same data source.
  • the data source for generating the ultrasound image in 1100 and the data source for calculating the strain are not the same data source.
  • the ultrasonic probe is controlled to transmit ultrasonic waves twice and acquire corresponding echo data: one is to transmit ultrasonic waves for the tissue to be measured of the target object, and the ultrasonic waves are generated according to the corresponding echo signals.
  • the ultrasound image of the tissue to be tested of the target object and obtain the region of interest and the target tissue region; one is to transmit ultrasonic waves to the sub-tissue corresponding to the target tissue region in the tissue to be tested, and obtain the target tissue region and the target tissue region according to the corresponding echo signals. Strain in the region of interest.
  • the data source for generating the ultrasonic image and the data source for calculating the strain are not the same data source, so two imaging modes, the ultrasonic imaging mode and the strain elastography mode, can be provided, wherein the ultrasonic imaging mode corresponds to The aforementioned first ultrasonic wave emission and its subsequent operations (corresponding to steps S1110 to S1120 ), and the strain elastography mode corresponds to the aforementioned second ultrasonic wave emission and its subsequent operations (corresponding to steps S1130 to S1150 ).
  • a selection mode of the strain elastography mode may be provided (to the user), and based on the (user's) selection of the strain elastography mode, the selection of the strain elastography mode may be triggered. Strain elastography is performed on the sub-tissue corresponding to the target tissue region.
  • a method for selecting an ultrasound imaging mode may be provided (to the user), and based on the (user's) selection of the ultrasound imaging mode, ultrasound imaging of the tissue to be tested is triggered; Then, after step S1120 is completed, the ultrasonic imaging mode can be switched to the strain elastography mode, and subsequent steps S1130 to S1150 are performed.
  • the selection method of the strain elastography mode may be provided (to the user), and the trigger based on the selection of the strain elastography mode (by the user) can be triggered. Strain elastography is performed on the tissue to be tested.
  • the strain elastography method 1100 can also obtain the same effect as the strain elastography method 400 , that is, the strain of the region of interest including the target tissue region is generated based on the strain value of the target tissue region
  • the elastic image can reduce or even avoid the influence of the strain value of other tissues or regions in the region of interest on the strain image of the target tissue, thereby improving the quality and reliability of strain elastography.
  • the strain elastography method 400 uses the same data source to simplify the operation process of the entire method, while the strain elastography method 1100 uses different data sources to obtain more accurate strain calculation results, thereby obtaining a more accurate strain elasticity image.
  • FIG. 12 shows a schematic flowchart of a strain elastography method 1200 according to still another embodiment of the present application. As shown in FIG. 12, the strain elastography method 1200 may include the following steps:
  • step S1210 a selection manner of the strain elastography mode is provided.
  • step S1220 based on the selection of the strain elastography mode, the ultrasonic probe is controlled to transmit ultrasonic waves to the tissue under test of the target object, receive the echoes of the ultrasonic waves, and acquire ultrasonic echo data based on the echoes of the ultrasonic waves.
  • step S1230 an ultrasound image is generated based on the ultrasound echo data, and a target tissue region in the ultrasound image is acquired.
  • step S1240 the strain of the target tissue region is calculated based on the ultrasound echo data.
  • step S1250 a strain elasticity image of the target tissue region is generated and displayed based on the strain of the target tissue region.
  • the strain elastography method 1200 according to the embodiment of the present application is substantially similar to the strain elastography method 400 according to the embodiment of the present application described above.
  • the strain elastography method 1200 and the strain elastography method 400 will not be repeated here. are similar in detail, only the differences are described.
  • the strain elasticity imaging method 400 acquires the region of interest in the ultrasound image and the target tissue region in the region of interest, and then generates the strain elasticity image of the region of interest according to the strain of the target tissue region;
  • the imaging method 1200 is to directly acquire the target tissue region in the ultrasound image, and then generate a strain elasticity image of the target tissue region according to the strain of the target tissue region; in addition, similar to the strain elasticity imaging method 1100 described above, the strain elasticity imaging method 1200
  • a strain elastography mode can also be provided for the user to choose to perform strain elastography in this mode.
  • the strain elasticity image of the target tissue area is generated according to the strain of the target tissue area, which can reduce or even avoid the influence of the strain values of other non-target tissue areas on the target tissue strain image, Thereby improving the quality and reliability of strain elastography; in addition, since strain elastography is not performed directly on areas other than the target tissue area, the amount of calculation can be further reduced, and the doctor can directly focus on the elasticity of the target tissue area, making it more targeted. powerful.
  • FIGS. 13A and 13B illustrate exemplary schematic diagrams of a display scheme in a strain elastography method according to still another embodiment of the present application.
  • Figure 13A after identifying and segmenting the target tissue area, according to the identification result, calculate the strain mean value of the target tissue area, and use the strain mean value as the benchmark, only perform color mapping and strain imaging on the target tissue area, and other areas. The strain image is not displayed, as shown in Figure 13A.
  • the mean strain value of the target tissue area is calculated, and based on the mean strain value, only color mapping and strain imaging are performed on the target tissue area, and other areas are It is directly displayed as the color corresponding to normal tissue (center of softness and hardness), as shown in Figure 13B.
  • FIG. 14 shows a schematic flowchart of a strain elastography method 1400 according to yet another embodiment of the present application. As shown in FIG. 14, strain elastography method 1400 may include the following steps:
  • step S1410 a selection mode of the ultrasound imaging mode and a selection mode of the strain elastography mode are provided.
  • step S1420 based on the selection of the ultrasonic imaging mode, the ultrasonic probe is controlled to transmit ultrasonic waves to the tissue under test of the target object, receive the echoes of the ultrasonic waves, and acquire ultrasonic echo data based on the echoes of the ultrasonic waves.
  • step S1430 an ultrasound image is generated based on the ultrasound echo data, and a target tissue region in the ultrasound image is acquired.
  • step S1440 the ultrasonic imaging mode is switched to the strain elastography mode based on the selection of the strain elastography mode, and the ultrasonic probe is controlled at least to the sub-tissue corresponding to the target tissue region in the tissue to be measured A second ultrasonic wave is emitted, an echo of the second ultrasonic wave is received, and second ultrasonic echo data is acquired based on the echo of the second ultrasonic wave.
  • step S1450 the strain of the target tissue region is calculated based on the second ultrasound echo data.
  • step S1460 a strain elasticity image of the target tissue region is generated and displayed based on the strain of the target tissue region.
  • the strain elastography method 1400 according to the embodiment of the present application is substantially similar to the strain elastography method 1200 according to the embodiment of the present application described above.
  • the strain elastography method 1400 and the strain elastography method 1200 will not be repeated here. are similar in detail, only the differences are described.
  • the difference between the two is that in the strain elastography method 1200 according to the embodiment of the present application, the data source for generating the ultrasonic image and the data source for calculating the strain are the same data source, while in the strain elastography method according to the embodiment of the present application, the data source for generating the ultrasonic image and the data source for calculating the strain are the same data source.
  • the data source for generating the ultrasound image in 1400 and the data source for calculating the strain are not the same data source. This is similar to the difference between the strain elastography method 1100 and the strain elastography method 400 described above, and will not be repeated here.
  • the strain elasticity imaging methods 1200 and 1400 generate a strain elasticity image of the target tissue area according to the strain of the target tissue area, which can reduce or even avoid the strain values of other non-target tissue areas affecting the target tissue strain
  • the quality and reliability of strain elastography is improved; in addition, since strain elastography is not directly performed on areas other than the target tissue area, the amount of calculation can be further reduced, and the doctor can directly focus on the elasticity of the target tissue area , more targeted.
  • the strain elastography method 1200 uses the same data source to simplify the operation process of the entire method, while the strain elastography method 1400 uses different data sources to obtain more accurate strain calculation results, thereby obtaining a more accurate strain elasticity image.
  • the strain elastography method according to the embodiment of the present application is exemplarily described above.
  • the following describes a strain elastography device provided according to another aspect of the present application with reference to FIG. 15 , which can be used to implement the aforementioned strain elastography method according to the embodiments of the present application.
  • Those skilled in the art can understand the structure and operation of each component of the strain elastography device according to the embodiment of the present application in combination with the foregoing description, which is not repeated here for brevity.
  • FIG. 15 shows a schematic block diagram of a strain elastography apparatus 1500 according to an embodiment of the present application.
  • the strain elastography apparatus 1500 may include an ultrasound probe 1510 , a transmitting circuit 1520 , a receiving circuit 1530 and a processor 1540 .
  • the transmitting circuit 1520 is used to excite the ultrasonic probe 1510 to transmit ultrasonic waves to the tissue to be measured of the target object;
  • the receiving circuit 1530 is used to control the ultrasonic probe 1510 to receive the ultrasonic echoes returned from the tissue to be measured to obtain ultrasonic echo signals;
  • the processor 1540 is configured to generate ultrasound image data according to the ultrasound echo signal, and is further configured to execute the aforementioned strain elastography method according to the embodiment of the present application.
  • a storage medium is also provided, and program instructions are stored on the storage medium, and when the program instructions are run by a computer or a processor, the program instructions are used to execute the corresponding steps of the strain elastography method of the embodiments of the present application .
  • the storage medium may include, for example, a memory card for a smartphone, a storage unit for a tablet computer, a hard disk for a personal computer, a read only memory (ROM), an erasable programmable read only memory (EPROM), a portable compact disk read only memory (CD). - ROM), USB memory, or any combination of the above storage media.
  • a computer-readable storage medium can be any combination of one or more computer-readable storage media.
  • a computer program is also provided, and the computer program can be stored in the cloud or on a local storage medium.
  • the computer program is run by a computer or a processor, it is used to execute the corresponding steps of the strain elastography method of the embodiments of the present application.
  • the strain elasticity imaging method, device, and storage medium generate the strain elasticity image of the target tissue region or the region of interest including the target tissue region based on the strain value of the target tissue region, which can reduce the Even the strain values of other tissues or regions are prevented from affecting the strain image of the target tissue, thereby improving the quality and reliability of strain elastography.
  • Various component embodiments of the present application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof.
  • a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all functions of some modules according to the embodiments of the present application.
  • DSP digital signal processor
  • the present application can also be implemented as a program of apparatus (eg, computer programs and computer program products) for performing part or all of the methods described herein.
  • Such a program implementing the present application may be stored on a computer-readable medium, or may be in the form of one or more signals. Such signals may be downloaded from Internet sites, or provided on carrier signals, or in any other form.

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Abstract

一种应变弹性成像方法（400）、装置（10）以及存储介质。该方法（400）包括：控制超声探头（100）向目标对象的待测组织发射超声波，接收超声波的回波，基于超声波的回波获取超声回波数据（S410）；基于超声回波数据生成超声图像，并获取超声图像中的感兴趣区域和感兴趣区域中的目标组织区域（S420）；基于超声回波数据计算目标组织区域的应变和感兴趣区域的应变（S430）；基于目标组织区域的应变对感兴趣区域的应变进行图像特征映射以生成并显示感兴趣区域的应变弹性图像（S440）。该方法（400）以目标组织区域的应变值为基准生成应变弹性图像，能够提高应变弹性成像的质量和可信度。

Description

一种应变弹性成像方法、装置以及存储介质
说明书
技术领域
本申请涉及超声成像技术领域，更具体地涉及一种应变弹性成像方法、装置以及存储介质。
背景技术
应变弹性成像技术近年来已经被广泛的被应用到临床研究和诊断中。应变弹性成像通过探头按压组织，并实时计算组织的位移及应变来反映成像区域内组织的弹性相关参数并成像。它可以定性地反映病灶相对于周围组织的软硬程度，目前通常被应用于甲状腺、乳腺、肌骨等方面的临床上。对于组织软硬程度的判断可以有效辅助对于癌症病变、肿瘤良恶性及术后恢复等进行的诊断和评价。
应变弹性图像一般通过不同的颜色来代表组织不同的硬度或者应变值，目前应变弹性算法是通过整个成像区域的应变均值作为基准，对成像区域进行颜色映射和转换的。但是目前在对甲状腺、乳腺等组织进行应变弹性成像时，成像区域内除了甲状腺、乳腺等目标组织，还存在血管、暗区以及一些其他组织，这些组织区域的应变值往往和目标组织差异很大，在应变图像中显示为极软或极硬，从而导致整个成像区域的应变均值产生偏移，以此应变均值进行颜色映射，应变图像中正常目标组织会表现为偏硬或者偏软，降低图像可信度，严重影响图像质量。
发明内容
本申请一方面，提供了一种应变弹性成像方法，该方法包括：控制超声探头向目标对象的待测组织发射超声波，接收所述超声波的回波，基于所述超声波的回波获取超声回波数据；基于所述超声回波数据生成超声图像，并获取所述超声图像中的感兴趣区域和所述感兴趣区域中的目标组织区域；基于所述超声回波数据计算所述目标组织区域的应变和所述感兴趣 区域的应变；基于所述目标组织区域的应变对所述感兴趣区域的应变进行图像特征映射以生成并显示所述感兴趣区域的应变弹性图像。
本申请另一方面，提供了一种应变弹性成像方法，该方法包括：控制超声探头向目标对象的待测组织发射第一超声波，接收所述第一超声波的回波，基于所述第一超声波的回波获取第一超声回波数据；基于所述第一超声回波数据生成超声图像，并获取所述超声图像中的感兴趣区域和所述感兴趣区域中的目标组织区域；控制超声探头至少向所述待测组织中所述目标组织区域对应的子组织发射第二超声波，接收所述第二超声波的回波，基于所述第二超声波的回波获取第二超声回波数据；基于所述第二超声回波数据计算所述目标组织区域的应变和所述感兴趣区域的应变；基于所述目标组织区域的应变对所述感兴趣区域的应变进行图像特征映射以生成并显示所述感兴趣区域的应变弹性图像。
本申请再一方面，提供了一种应变弹性成像方法，该方法包括：提供应变弹性成像模式的选择方式；基于对所述应变弹性成像模式的选择控制超声探头向目标对象的待测组织发射超声波，接收所述超声波的回波，基于所述超声波的回波获取超声回波数据；基于所述超声回波数据生成超声图像，并获取所述超声图像中的目标组织区域；基于所述超声回波数据计算所述目标组织区域的应变；基于所述目标组织区域的应变生成并显示所述目标组织区域的应变弹性图像。
本申请又一方面，提供了一种应变弹性成像方法，该方法包括：提供超声成像模式的选择方式和应变弹性成像模式的选择方式；基于对所述超声成像模式的选择控制超声探头向目标对象的待测组织发射超声波，接收所述超声波的回波，基于所述超声波的回波获取超声回波数据；基于所述超声回波数据生成超声图像，并获取所述超声图像中的目标组织区域；基于对所述应变弹性成像模式的选择将所述超声成像模式切换至所述应变弹性成像模式，并控制超声探头至少向所述待测组织中所述目标组织区域对应的子组织发射第二超声波，接收所述第二超声波的回波，基于所述第二超声波的回波获取第二超声回波数据；基于所述第二超声回波数据计算所述目标组织区域的应变；基于所述目标组织区域的应变生成并显示所述目标组织区域的应变弹性图像。
本申请再一方面，提供了一种应变弹性成像装置，该装置包括超声探头、发射电路、接收电路和处理器，其中：所述发射电路用于激励所述超声探头向目标对象的待测组织发射超声波；所述接收电路用于控制所述超声探头接收自所述待测组织返回的超声回波，以获取超声回波信号；所述处理器用于根据所述超声回波信号生成超声图像数据；所述处理器还用于执行上述应变弹性成像方法。
本申请又一方面，提供了一种存储介质，所述存储介质上存储有计算机程序，所述计算机程序在运行时执行上述应变弹性成像方法。
根据本申请实施例的应变弹性成像方法、装置以及存储介质以目标组织区域的应变值为基准生成目标组织区域或包含目标组织区域的感兴趣区域的应变弹性图像，能够减小甚至避免其他组织或区域的应变值对目标组织应变图像产生影响，从而提高应变弹性成像的质量和可信度。
附图说明
图1示出现有应变弹性成像方法得到的应变弹性图像的示意图。
图2示出现有应变弹性成像方法得到的应变弹性图像中出现偏差的示意图。
图3示出用于实现根据本申请实施例的应变弹性成像方法的示例性超声成像装置的示意性框图。
图4示出根据本申请一个实施例的应变弹性成像方法的示意性流程图。
图5A和图5B示出根据本申请一个实施例的应变弹性成像方法中识别分割目标区域的一个示例的示意图。
图6示出根据本申请一个实施例的应变弹性成像方法中识别分割目标区域的另一个示例的示意图。
图7A、图7B和图7C示出根据本申请一个实施例的应变弹性成像方法中识别分割目标区域的再一个示例的示意图。
图8示出根据本申请一个实施例的应变弹性成像方法中颜色映射方案的一个示例的示意图。
图9示出根据本申请一个实施例的应变弹性成像方法中颜色映射方案的另一个示例的示意图。
图10示出根据本申请一个实施例的应变弹性成像方法中的显示方案的一个示例的示意图。
图11示出根据本申请另一个实施例的应变弹性成像方法的示意性流程图。
图12示出根据本申请再一个实施例的应变弹性成像方法的示意性流程图。
图13A和图13B示出根据本申请再一个实施例的应变弹性成像方法中的显示方案的示例性示意图。
图14示出根据本申请又一个实施例的应变弹性成像方法的示意性流程图。
图15示出根据本申请实施例的应变弹性成像装置的示意性框图。
具体实施方式
为了使得本申请的目的、技术方案和优点更为明显，下面将参照附图详细描述根据本申请的示例实施例。显然，所描述的实施例仅仅是本申请的一部分实施例，而不是本申请的全部实施例，应理解，本申请不受这里描述的示例实施例的限制。基于本申请中描述的本申请实施例，本领域技术人员在没有付出创造性劳动的情况下所得到的所有其他实施例都应落入本申请的保护范围之内。
在下文的描述中，给出了大量具体的细节以便提供对本申请更为彻底的理解。然而，对于本领域技术人员而言显而易见的是，本申请可以无需一个或多个这些细节而得以实施。在其他的例子中，为了避免与本申请发生混淆，对于本领域公知的一些技术特征未进行描述。
应当理解的是，本申请能够以不同形式实施，而不应当解释为局限于这里提出的实施例。相反地，提供这些实施例将使公开彻底和完全，并且将本申请的范围完全地传递给本领域技术人员。
在此使用的术语的目的仅在于描述具体实施例并且不作为本申请的限制。在此使用时，单数形式的“一”、“一个”和“所述/该”也意图包括复数形式，除非上下文清楚指出另外的方式。还应明白术语“组成”和/或“包括”，当在该说明书中使用时，确定所述特征、整数、步骤、操作、 元件和/或部件的存在，但不排除一个或更多其他的特征、整数、步骤、操作、元件、部件和/或组的存在或添加。在此使用时，术语“和/或”包括相关所列项目的任何及所有组合。
为了彻底理解本申请，将在下列的描述中提出详细的步骤以及详细的结构，以便阐释本申请提出的技术方案。本申请的较佳实施例详细描述如下，然而除了这些详细描述外，本申请还可以具有其他实施方式。
应变弹性图像一般通过不同的颜色来代表组织不同的硬度或者应变值，现有的应变弹性成像方法是通过整个成像区域的应变均值作为基准，对成像区域进行颜色映射和转换的。现在结合图1来描述，图1示出现有应变弹性成像方法得到的应变弹性图像的示意图，如图1所示，以成像区域R1(也称为感兴趣区域)内的应变均值作为基准，对成像区域R1进行颜色映射和转换得到应变弹性图像。应变弹性图像中颜色1、颜色2和颜色3分别代表硬度偏硬、正常和偏软的组织(颜色1、颜色2和颜色3可分别对应于红色、绿色和蓝色，但由于专利申请文件中附图要求是灰度图，因此在图1中无法示出颜色，但实际应用中是可以设置并看到颜色的)，图中以成像区域应变均值为基准，应变值与均值相同或接近的组织表现为颜色2，应变值大于均值的组织表现为颜色3，小于均值的组织表现为颜色1，颜色的深浅代表组织偏软或偏硬的程度。
但是，目前在对甲状腺、乳腺等组织进行应变弹性成像时，成像区域内除了甲状腺、乳腺等目标组织，还存在血管、暗区以及一些其他组织。现在结合图2来描述，图2示出现有应变弹性成像方法得到的应变弹性图像中出现偏差的示意图。如图2左侧的组织结构图像所示，成像区域R2内除了甲状腺、乳腺等目标组织，还存在血管、暗区以及一些其他组织，这些组织区域的应变值往往和目标组织差异很大，在应变图像中显示为极软或极硬，从而导致整个成像区域的应变均值产生偏移。以此应变均值进行颜色映射得到图2右侧的应变弹性图像，可以看出，该应变弹性图像中正常目标组织会表现为偏硬或者偏软，降低图像可信度，严重影响图像质量。
基于此，本申请提供一种应变弹性成像方案，其在进行应变弹性成像时，不以整个成像区域(感兴趣区域)的应变均值为基准进行颜色映射， 而是以目标组织区域中的应变值为基准生成应变弹性图像，可以避免出现图2中所示的问题，提高应变弹性图像的可信度。下面结合图3到图15来描述。
图3示出用于实现本申请实施例的应变弹性成像方法的示例性超声成像装置10的结构框图示意图。如图3所示，该超声成像装置10可以包括超声探头100、发射/接收选择开关101、发射/接收序列控制器102、处理器103、显示器104和存储器105。发射/接收序列控制器102可以激励超声探头100向目标对象(目标对象)发射超声波，还可以控制超声探头100接收从目标对象返回的超声回波，从而获得超声回波信号/数据。处理器103对该超声回波信号/数据进行处理，以获得目标对象的组织相关参数和超声图像。处理器103获得的超声图像可以存储于存储器105中，这些超声图像可以在显示器104上显示。
本申请实施例中，前述的超声成像装置10的显示器104可为触摸显示屏、液晶显示屏等，也可以是独立于超声成像装置10之外的液晶显示器、电视机等独立显示装置，也可为手机、平板电脑等电子装置上的显示屏。
本申请实施例中，前述的超声成像装置10的存储器105可为闪存卡、固态存储器、硬盘等。
本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质存储有多条程序指令，该多条程序指令被处理器103调用执行后，可执行本申请各个实施例中的应变弹性成像方法中的部分步骤或全部步骤或其中步骤的任意组合。
一个实施例中，该计算机可读存储介质可为存储器105，其可以是闪存卡、固态存储器、硬盘等非易失性存储介质。
本申请实施例中，前述的超声成像装置10的处理器103可以通过软件、硬件、固件或者其组合实现，可以使用电路、单个或多个专用集成电路(application specific integrated circuits，ASIC)、单个或多个通用集成电路、单个或多个微处理器、单个或多个可编程逻辑器件、或者前述电路或器件的组合、或者其他适合的电路或器件，从而使得该处理器103可以执行各个实施例中的应变弹性成像方法的相应步骤。
图4示出了根据本申请一个实施例的应变弹性成像方法400的示意性 流程图。如图4所示，应变弹性成像方法400包括如下步骤：
在步骤S410，控制超声探头向目标对象的待测组织发射超声波，接收所述超声波的回波，基于所述超声波的回波获取超声回波数据。
在步骤S420，基于所述超声回波数据生成超声图像，并获取所述超声图像中的感兴趣区域和所述感兴趣区域中的目标组织区域。
在步骤S430，基于所述超声回波数据计算所述目标组织区域的应变和所述感兴趣区域的应变。
在步骤S440，基于所述目标组织区域的应变对所述感兴趣区域的应变进行图像特征映射以生成并显示所述感兴趣区域的应变弹性图像。
在本申请的实施例中，控制超声探头向目标对象的待测组织(即进行应变弹性成像的组织)发射超声波是为了获取超声图像(诸如组织结构图像等等)。根据该超声图像可以获取用于进行应变弹性成像的感兴趣区域(类似于前文所述的成像区域，一般可以由用户来选定)，并获取该感兴趣区域中的目标组织区域。其中，该目标组织区域基于所述待测组织的不同而不同。例如，当前述的待测组织为甲状腺时，该目标组织区域即甲状腺组织所在区域；当前述的待测组织为乳腺时，该目标组织区域即乳腺组织所在区域，诸如此类。由于感兴趣区域中除了包括目标组织区域，还可能包含一些非目标组织区域(诸如前述的血管、暗区以及一些其他组织)，因此，可以获取感兴趣区域中的目标组织区域，以用于获取目标组织区域的应变值进行图像特征映射(诸如颜色映射等等)而得到可信度更高的应变弹性图像。
在本申请的一个实施例中，获取所述超声图像中的感兴趣区域中的目标组织区域，可以包括：自动识别并分割出所述超声图像中与所述待测组织相对应的目标组织区域。下面结合图5A、图5B和图6来描述。
图5A和图5B示出根据本申请一个实施例的应变弹性成像方法中识别分割目标区域的一个示例的示意图。在图5A到图5B中，示出了基于边缘检测的图像分割方法对超声图像中目标组织区域进行识别和分割。如图5A所示，超声图像中由于灰度级或结构突变产生的不连续性就是边缘，利用目标组织和其他组织区域在超声图像中灰度或结构的不连续性，可以通过包括但不限于微分算子等边缘检测算法检测这种不连续性，从而实现对感兴趣区域 内目标组织和其他组织区域的识别和分割，分割结果如图5B所示。在图5B中，区域T1即为分割出的目标组织区域。
图6示出根据本申请一个实施例的应变弹性成像方法中识别分割目标区域的另一个示例的示意图。在图6中，示出了基于机器学习的方法对超声图像中目标组织区域进行识别和分割。其中，机器学习的方法包括但不限于模式识别、深度学习等，对超声图像中目标组织区域进行识别和分割，分割结果如图6所示，区域T2即为分割出的目标组织区域。
在本申请的另一个实施例中，获取所述超声图像中的感兴趣区域中的目标组织区域，可以包括：半自动识别并分割出所述超声图像中与所述待测组织相对应的目标组织区域。其中，半自动可以理解为结合自动和用户手动方式，这样的方式也易于实现准确的识别分割结果。示例性地，半自动识别并分割出所述超声图像中与所述待测组织相对应的目标组织区域，可以包括：显示所述超声图像，并获取用户在所述超声图像中选定的参考区域；计算并提取所述参考区域的特征；根据特征一致原则或特征相近原则识别并分割出所述超声图像中与所述待测组织相对应的目标组织区域。下面结合图7A、图7B和图7C来描述。
图7A、图7B和图7C示出根据本申请一个实施例的应变弹性成像方法中识别分割目标区域的再一个示例的示意图。如图7A和图7B所示，用户可以首先在超声图像中手动选择或描迹任意一处目标组织，选择方式可以包括但不限于点击、描迹、圆框、方框等，其中图7A示出的是用户点击选择圆框得到的一处目标组织T3，图7B示出的是用户手动描迹得到的一处目标组织T4。接着，系统可以自动计算并提取图7A(或图7B)中用户选定区域的相关特征(包括但不限于灰度、纹理、方差等)，根据特征一致或接近的原则，自动识别分割出与用户选定区域特征一致或接近的组织区域，作为目标组织区域，如图7C所示，图7C中的T5区域即为识别分割出的目标组织区域，可以看到用户选定区域T3包括在其内。
在本申请的再一个实施例中，获取所述超声图像中的感兴趣区域中的目标组织区域，可以包括：显示所述超声图像，并获取用户在所述超声图像中的选定的与所述待测组织相对应的目标组织区域。在该实施例中，完全由用户手动确定与所述待测组织相对应的目标组织区域，可以实现基于 用户输入获取目标组织区域。
在获取目标组织区域后，可计算目标组织区域内的应变(诸如基于目标组织区域内的射频(RF)数据或正交调制(IQ)数据)；此外，由于要对感兴趣区域进行应变弹性成像，因而还可获取感兴趣区域中目标组织区域以外区域的应变。在本申请的实施例中，组织产生的应变可以是探头按压产生的，也可以是组织自身运动产生的，例如肌骨、甲状腺、子宫、血管等小器官自身运动产生应变。接着，基于目标组织区域内的应变，对感兴趣区域内的应变进行图像特征映射(诸如颜色映射)，以得到感兴趣区域的应变弹性图像。
在本申请的实施例中，基于所述目标组织区域的应变对所述感兴趣区域的应变进行图像特征映射，可以包括：基于所述目标组织区域的应变生成应变参考值，以所述应变参考值为基准对所述感兴趣区域的应变进行图像特征映射。示例性地，该应变参考值可以为目标组织区域的应变的均值，也可以为任何其他能够反映目标组织区域应变的特征的值。示例性地，以所述应变参考值为基准对所述感兴趣区域的应变进行的图像特征映射可以是颜色映射，或者其他能够在图像中体现不同应变值的映射。
在本申请的一个实施例中，以所述应变参考值为基准对所述感兴趣区域的应变进行图像特征映射，可以包括：根据所述应变参考值确定应变范围，所述应变范围的两个边界值分别小于和大于所述应变参考值；根据所述应变范围以线性映射关系将所述感兴趣区域的应变映射为灰度值；将所述灰度值转化为相应的颜色。示例性地，可以将感兴趣区域内应变处于所述应变范围的位置映射成预设范围内的灰度值；将感兴趣区域内应变超出所述应变范围的位置映射成所述预设范围的边界值。下面结合图8来描述。
图8示出根据本申请一个实施例的应变弹性成像方法中颜色映射方案的一个示例的示意图。如图8所示，计算得到目标组织区域(目标区域)的应变均值后，选定小于和大于该应变均值的一定应变范围，将感兴趣区域内应变处于所述应变范围的位置以线性的关系，映射成为0-255的灰度值，超出该范围的应变值均映射为0或255，最后再将灰度值转化为应变图像中显示的相应颜色，映射关系如图8所示。
在本申请的一个实施例中，以所述应变参考值为基准对所述感兴趣区 域的应变进行图像特征映射，可以包括：根据所述应变参考值确定应变范围，所述应变范围的两个边界值分别小于和大于所述应变参考值；根据所述应变范围以非线性映射关系将所述感兴趣区域的应变映射为灰度值；将所述灰度值转化为相应的颜色。示例性地，可以将感兴趣区域内应变处于所述应变范围的位置映射成预设范围内的灰度值；将感兴趣区域内应变超出所述应变范围的位置映射成所述预设范围的边界值。下面结合图9来描述。
图9示出根据本申请一个实施例的应变弹性成像方法中颜色映射方案的另一个示例的示意图。如图9所示，计算得到目标组织区域(目标区域)的应变均值后，选定小于和大于该应变均值的一定应变范围，将感兴趣区域内应变处于所述应变范围的位置以非线性的关系，映射成为0-255的灰度值，超出该范围的应变值均映射为0或255，最后再将灰度值转化为应变图像中显示的相应颜色，映射关系如图9所示。
在本申请的实施例中，在将感兴趣区域内每一处的应变值映射为灰度值和相应的颜色后，可生成感兴趣区域的应变弹性图像并进行显示。下面结合图10来描述。图10示出根据本申请一个实施例的应变弹性成像方法中的显示方案的一个示例的示意图。如图10所示，对感兴趣区域R内的目标组织区域T识别和分割后，根据识别结果，计算目标组织区域T的应变均值，并以此应变均值为基准，对整个感兴趣区域R进行颜色映射和应变成像，得到图10右侧所示的感兴趣区域的应变弹性图像M。如图10所示，由于感兴趣区域R的应变弹性图像M是以目标组织区域T内的应变均值为基准而映射得到的，因而能够减小甚至避免感兴趣区域内其他组织或区域的应变值对目标组织应变图像的显示产生影响，从而提高应变弹性成像的质量和可信度。
基于上面的描述，根据本申请实施例的应变弹性成像方法400以目标组织区域的应变值为基准生成包含目标组织区域的感兴趣区域的应变弹性图像，能够减小甚至避免感兴趣区域内其他组织或区域的应变值对目标组织应变图像产生影响，从而提高应变弹性成像的质量和可信度。
下面结合图11描述根据本申请另一个应变弹性成像方法1100的示意性流程图。如图11所示，应变弹性成像方法1100可以包括如下步骤：
在步骤S1110，控制超声探头向目标对象的待测组织发射第一超声波， 接收所述第一超声波的回波，基于所述第一超声波的回波获取第一超声回波数据。
在步骤S1120，基于所述第一超声回波数据生成超声图像，并获取所述超声图像中的感兴趣区域和所述感兴趣区域中的目标组织区域。
在步骤S1130，控制超声探头至少向所述待测组织中所述目标组织区域对应的子组织发射第二超声波，接收所述第二超声波的回波，基于所述第二超声波的回波获取第二超声回波数据。
在步骤S1140，基于所述第二超声回波数据计算所述目标组织区域的应变和所述感兴趣区域的应变。
在步骤S1150，基于所述目标组织区域的应变对所述感兴趣区域的应变进行图像特征映射以生成并显示所述感兴趣区域的应变弹性图像。
根据本申请实施例的应变弹性成像方法1100与前文所述的根据本申请实施例的应变弹性成像方法400大体上类似，为了简洁，此处不再赘述应变弹性成像方法1100与应变弹性成像方法400中相似的细节，仅描述两者的不同之处。两者的不同之处在于，在根据本申请实施例的应变弹性成像方法400中生成超声图像的数据源和计算应变的数据源是同一数据源，而在根据本申请实施例的应变弹性成像方法1100中生成超声图像的数据源和计算应变的数据源不是同一数据源。
因此，在根据本申请实施例的应变弹性成像方法1100中，控制超声探头两次发射超声波并获取相应的回波数据：一次是针对目标对象的待测组织发射超声波，根据相应的回波信号生成目标对象的待测组织的超声图像，并获取其中的感兴趣区域和目标组织区域；一次是针对待测组织中目标组织区域对应的子组织发射超声波，根据相应的回波信号获取目标组织区域和感兴趣区域的应变。
在本申请的实施例中，生成超声图像的数据源和计算应变的数据源不是同一数据源，因而可以提供两种成像模式——超声成像模式和应变弹性成像模式，其中，超声成像模式对应于前述第一次发射超声波及其后续操作(对应于步骤S1110到步骤S1120)，应变弹性成像模式对应于前述第二次发射超声波及其后续操作(对应于步骤S1130到步骤S1150)。因此，在一个实施例中，在步骤S1130之前，可以(向用户)提供应变弹性成像模式的选择方式， 并基于(用户)对所述应变弹性成像模式的选择触发对所述待测组织中所述目标组织区域对应的子组织进行应变弹性成像。类似地，在一个实施例中，在步骤S1110之前，可以(向用户)提供超声成像模式的选择方式，基于(用户)对所述超声成像模式的选择触发对所述待测组织进行超声成像；然后，再完成步骤S1120后，可以将所述超声成像模式切换至所述应变弹性成像模式，再执行后续的步骤S1130到步骤S1150。
基于这样的思路，在前述的应变弹性成像方法400中，也可以在步骤S410之前，(向用户)提供应变弹性成像模式的选择方式，并基于(用户)对所述应变弹性成像模式的选择触发对所述待测组织进行应变弹性成像。
基于上面的描述，根据本申请实施例的应变弹性成像方法1100也可以得到与应变弹性成像方法400相同的效果，即以目标组织区域的应变值为基准生成包含目标组织区域的感兴趣区域的应变弹性图像，能够减小甚至避免感兴趣区域内其他组织或区域的应变值对目标组织应变图像产生影响，从而提高应变弹性成像的质量和可信度。此外，应变弹性成像方法400使用同一数据源可以简化整个方法的操作流程，而应变弹性成像方法1100使用不同数据源可能获得更为精准的应变计算结果，从而得到更准确的应变弹性图像。
图12示出了根据本申请再一个实施例的应变弹性成像方法1200的示意性流程图。如图12所示，应变弹性成像方法1200可以包括如下步骤：
在步骤S1210，提供应变弹性成像模式的选择方式。
在步骤S1220，基于对所述应变弹性成像模式的选择控制超声探头向目标对象的待测组织发射超声波，接收所述超声波的回波，基于所述超声波的回波获取超声回波数据。
在步骤S1230，基于所述超声回波数据生成超声图像，并获取所述超声图像中的目标组织区域。
在步骤S1240，基于所述超声回波数据计算所述目标组织区域的应变。
在步骤S1250，基于所述目标组织区域的应变生成并显示所述目标组织区域的应变弹性图像。
根据本申请实施例的应变弹性成像方法1200与前文所述的根据本申请实施例的应变弹性成像方法400大体上类似，为了简洁，此处不再赘述 应变弹性成像方法1200与应变弹性成像方法400中相似的细节，仅描述两者的不同之处。两者的不同之处在于，应变弹性成像方法400是获取超声图像中感兴趣区域以及感兴趣区域中的目标组织区域，再根据目标组织区域的应变生成感兴趣区域的应变弹性图像；而应变弹性成像方法1200是直接获取超声图像中的目标组织区域，再根据目标组织区域的应变生成目标组织区域的应变弹性图像；此外，与前文所述应变弹性成像方法1100中类似的，应变弹性成像方法1200也可以提供应变弹性成像模式，以供用户选择在该模式下进行应变弹性成像。
在根据本申请实施例的应变弹性成像方法1200中，根据目标组织区域的应变生成目标组织区域的应变弹性图像，能够减小甚至避免其他非目标组织区域的应变值对目标组织应变图像产生影响，从而提高应变弹性成像的质量和可信度；此外，由于直接不对目标组织区域以外的区域进行应变弹性成像，因而可以进一步减少计算量，且使得医生直接关注目标组织区域的弹性情况，针对性更强。
图13A和图13B示出根据本申请再一个实施例的应变弹性成像方法中的显示方案的示例性示意图。如图13A所示，在对目标组织区域识别和分割后，根据识别结果，计算目标组织区域的应变均值，并以此应变均值为基准，只对目标组织区域进行颜色映射和应变成像，其他区域不显示应变图像，如图13A所示的。如图13B所示，在对目标组织区域识别和分割后，根据识别结果，计算目标组织区域的应变均值，并以此应变均值为基准，只对目标组织区域进行颜色映射和应变成像，其他区域直接显示为正常组织(软硬程度居中)对应的颜色，如图13B所示的。
图14示出根据本申请又一个实施例的应变弹性成像方法1400的示意性流程图。如图14所示，应变弹性成像方法1400可以包括如下步骤：
在步骤S1410，提供超声成像模式的选择方式和应变弹性成像模式的选择方式。
在步骤S1420，基于对所述超声成像模式的选择控制超声探头向目标对象的待测组织发射超声波，接收所述超声波的回波，基于所述超声波的回波获取超声回波数据。
在步骤S1430，基于所述超声回波数据生成超声图像，并获取所述超 声图像中的目标组织区域。
在步骤S1440，基于对所述应变弹性成像模式的选择将所述超声成像模式切换至所述应变弹性成像模式，并控制超声探头至少向所述待测组织中所述目标组织区域对应的子组织发射第二超声波，接收所述第二超声波的回波，基于所述第二超声波的回波获取第二超声回波数据。
在步骤S1450，基于所述第二超声回波数据计算所述目标组织区域的应变。
在步骤S1460，基于所述目标组织区域的应变生成并显示所述目标组织区域的应变弹性图像。
根据本申请实施例的应变弹性成像方法1400与前文所述的根据本申请实施例的应变弹性成像方法1200大体上类似，为了简洁，此处不再赘述应变弹性成像方法1400与应变弹性成像方法1200中相似的细节，仅描述两者的不同之处。两者的不同之处在于，在根据本申请实施例的应变弹性成像方法1200中生成超声图像的数据源和计算应变的数据源是同一数据源，而在根据本申请实施例的应变弹性成像方法1400中生成超声图像的数据源和计算应变的数据源不是同一数据源。这与前文所述的应变弹性成像方法1100与应变弹性成像方法400这两者之间的区别是类似的，此处不再赘述。
基于上面的描述，根据本申请实施例的应变弹性成像方法1200和1400根据目标组织区域的应变生成目标组织区域的应变弹性图像，能够减小甚至避免其他非目标组织区域的应变值对目标组织应变图像产生影响，从而提高应变弹性成像的质量和可信度；此外，由于直接不对目标组织区域以外的区域进行应变弹性成像，因而可以进一步减少计算量，且使得医生直接关注目标组织区域的弹性情况，针对性更强。此外，应变弹性成像方法1200使用同一数据源可以简化整个方法的操作流程，而应变弹性成像方法1400使用不同数据源可能获得更为精准的应变计算结果，从而得到更准确的应变弹性图像。
以上示例性地描述了根据本申请实施例的应变弹性成像方法。下面结合图15描述根据本申请另一方面提供的应变弹性成像装置，其可以用于实现前文所述的根据本申请实施例的应变弹性成像方法。本领域技术人员可以结合前文所述理解根据本申请实施例的应变弹性成像装置各部件的结构 和操作，为了简洁，此处不再赘述。
图15示出了根据本申请一个实施例的应变弹性成像装置1500的示意性框图。如图15所示，应变弹性成像装置1500可以包括超声探头1510、发射电路1520、接收电路1530和处理器1540。其中，发射电路1520用于激励超声探头1510向目标对象的待测组织发射超声波；接收电路1530用于控制超声探头1510接收自所述待测组织返回的超声回波，以获取超声回波信号；处理器1540用于根据所述超声回波信号生成超声图像数据，还用于执行前文所述的根据本申请实施例的应变弹性成像方法。
此外，根据本申请实施例，还提供了一种存储介质，在存储介质上存储了程序指令，在程序指令被计算机或处理器运行时用于执行本申请实施例的应变弹性成像方法的相应步骤。存储介质例如可以包括智能电话的存储卡、平板电脑的存储部件、个人计算机的硬盘、只读存储器(ROM)、可擦除可编程只读存储器(EPROM)、便携式紧致盘只读存储器(CD-ROM)、USB存储器、或者上述存储介质的任意组合。计算机可读存储介质可以是一个或多个计算机可读存储介质的任意组合。
此外，根据本申请实施例，还提供了一种计算机程序，该计算机程序可以存储在云端或本地的存储介质上。在该计算机程序被计算机或处理器运行时用于执行本申请实施例的应变弹性成像方法的相应步骤。
基于上面的描述，根据本申请实施例的应变弹性成像方法、装置以及存储介质以目标组织区域的应变值为基准生成目标组织区域或包含目标组织区域的感兴趣区域的应变弹性图像，能够减小甚至避免其他组织或区域的应变值对目标组织应变图像产生影响，从而提高应变弹性成像的质量和可信度。
尽管这里已经参考附图描述了示例实施例，应理解上述示例实施例仅仅是示例性的，并且不意图将本申请的范围限制于此。本领域普通技术人员可以在其中进行各种改变和修改，而不偏离本申请的范围和精神。所有这些改变和修改意在被包括在所附权利要求所要求的本申请的范围之内。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使 用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其他的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个装置，或一些特征可以忽略，或不执行。
在此处所提供的说明书中，说明了大量具体细节。然而，能够理解，本申请的实施例可以在没有这些具体细节的情况下实践。在一些实例中，并未详细示出公知的方法、结构和技术，以便不模糊对本说明书的理解。
类似地，应当理解，为了精简本申请并帮助理解各个发明方面中的一个或多个，在对本申请的示例性实施例的描述中，本申请的各个特征有时被一起分组到单个实施例、图、或者对其的描述中。然而，并不应将该本申请的方法解释成反映如下意图：即所要求保护的本申请要求比在每个权利要求中所明确记载的特征更多的特征。更确切地说，如相应的权利要求书所反映的那样，其发明点在于可以用少于某个公开的单个实施例的所有特征的特征来解决相应的技术问题。因此，遵循具体实施方式的权利要求书由此明确地并入该具体实施方式，其中每个权利要求本身都作为本申请的单独实施例。
本领域的技术人员可以理解，除了特征之间相互排斥之外，可以采用任何组合对本说明书(包括伴随的权利要求、摘要和附图)中公开的所有特征以及如此公开的任何方法或者装置的所有过程或单元进行组合。除非另外明确陈述，本说明书(包括伴随的权利要求、摘要和附图)中公开的每个特征可以由提供相同、等同或相似目的的替代特征来代替。
此外，本领域的技术人员能够理解，尽管在此的一些实施例包括其他实施例中所包括的某些特征而不是其他特征，但是不同实施例的特征的组合意味着处于本申请的范围之内并且形成不同的实施例。例如，在权利要求书中，所要求保护的实施例的任意之一都可以以任意的组合方式来使用。
本申请的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员 应当理解，可以在实践中使用微处理器或者数字信号处理器(DSP)来实现根据本申请实施例的一些模块的一些或者全部功能。本申请还可以实现为用于执行这里所描述的方法的一部分或者全部的装置程序(例如，计算机程序和计算机程序产品)。这样的实现本申请的程序可以存储在计算机可读介质上，或者可以具有一个或者多个信号的形式。这样的信号可以从因特网网站上下载得到，或者在载体信号上提供，或者以任何其他形式提供。
应该注意的是上述实施例对本申请进行说明而不是对本申请进行限制，并且本领域技术人员在不脱离所附权利要求的范围的情况下可设计出替换实施例。在权利要求中，不应将位于括号之间的任何参考符号构造成对权利要求的限制。本申请可以借助于包括有若干不同元件的硬件以及借助于适当编程的计算机来实现。在列举了若干装置的单元权利要求中，这些装置中的若干个可以是通过同一个硬件项来具体体现。单词第一、第二、以及第三等的使用不表示任何顺序。可将这些单词解释为名称。
以上，仅为本申请的具体实施方式或对具体实施方式的说明，本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。本申请的保护范围应以权利要求的保护范围为准。

Claims (19)

  1. 一种应变弹性成像方法，其特征在于，所述方法包括：
    控制超声探头向目标对象的待测组织发射超声波，接收所述超声波的回波，基于所述超声波的回波获取超声回波数据；
    基于所述超声回波数据生成超声图像，并获取所述超声图像中的感兴趣区域和所述感兴趣区域中的目标组织区域；
    基于所述超声回波数据计算所述目标组织区域的应变和所述感兴趣区域的应变；
    基于所述目标组织区域的应变对所述感兴趣区域的应变进行图像特征映射以生成并显示所述感兴趣区域的应变弹性图像。
  2. 一种应变弹性成像方法，其特征在于，所述方法包括：
    控制超声探头向目标对象的待测组织发射第一超声波，接收所述第一超声波的回波，基于所述第一超声波的回波获取第一超声回波数据；
    基于所述第一超声回波数据生成超声图像，并获取所述超声图像中的感兴趣区域和所述感兴趣区域中的目标组织区域；
    控制超声探头至少向所述待测组织中所述目标组织区域对应的子组织发射第二超声波，接收所述第二超声波的回波，基于所述第二超声波的回波获取第二超声回波数据；
    基于所述第二超声回波数据计算所述目标组织区域的应变和所述感兴趣区域的应变；
    基于所述目标组织区域的应变对所述感兴趣区域的应变进行图像特征映射以生成并显示所述感兴趣区域的应变弹性图像。
  3. 根据权利要求1或2所述的方法，其特征在于，所述基于所述目标组织区域的应变对所述感兴趣区域的应变进行图像特征映射，包括：
    基于所述目标组织区域的应变生成应变参考值，以所述应变参考值为基准对所述感兴趣区域的应变进行图像特征映射。
  4. 根据权利要求3所述的方法，其特征在于，所述基于所述目标组织区域的应变生成应变参考值，包括：
    计算所述目标组织区域的应变的均值，以作为应变参考值。
  5. 根据权利要求3所述的方法，其特征在于，所述图像特征映射包 括颜色映射。
  6. 根据权利要求5所述的方法，其特征在于，所述以所述应变参考值为基准对所述感兴趣区域的应变进行图像特征映射，包括：
    根据所述应变参考值确定应变范围，所述应变范围的两个边界值分别小于和大于所述应变参考值；
    根据所述应变范围以线性或非线性的映射关系将所述感兴趣区域的应变映射为灰度值；
    将所述灰度值转化为相应的颜色。
  7. 根据权利要求6所述的方法，其特征在于，所述将所述感兴趣区域的应变或所述目标组织区域的应变映射为灰度值，包括：
    将所述感兴趣区域内应变处于所述应变范围的位置映射成预设范围内的灰度值；
    将所述感兴趣区域内应变超出所述应变范围的位置映射成所述预设范围的边界值。
  8. 根据权利要求1或2所述的方法，其特征在于，所述获取所述超声图像中的感兴趣区域，包括：
    显示所述超声图像，并获取用户在所述超声图像中的选定的感兴趣区域。
  9. 根据权利要求1或2所述的方法，其特征在于，所述获取所述超声图像中的感兴趣区域中的目标组织区域，包括：
    显示所述超声图像，并获取用户在所述超声图像中的选定的与所述待测组织相对应的目标组织区域；或者
    自动或半自动识别并分割出所述超声图像中与所述待测组织相对应的目标组织区域。
  10. 根据权利要求9所述的方法，其特征在于，所述自动识别并分割出所述超声图像中与所述待测组织相对应的目标组织区域是基于边缘检测算法或机器学习来实现的。
  11. 根据权利要求9所述的方法，其特征在于，所述半自动识别并分割出所述超声图像中与所述待测组织相对应的目标组织区域，包括：
    显示所述超声图像，并获取用户在所述超声图像中选定的参考区域；
    计算并提取所述参考区域的特征；
    根据特征一致原则或特征相近原则识别并分割出所述超声图像中与所述待测组织相对应的目标组织区域。
  12. 根据权利要求1所述的方法，其特征在于，所述控制超声探头向目标对象的待测组织发射超声波之前，所述方法还包括：
    提供应变弹性成像模式的选择方式；
    基于对所述应变弹性成像模式的选择触发对所述待测组织进行应变弹性成像。
  13. 根据权利要求2所述的方法，其特征在于，所述控制超声探头至少向所述待测组织中所述目标组织区域对应的子组织发射第二超声波之前，所述方法还包括：
    提供应变弹性成像模式的选择方式；
    基于对所述应变弹性成像模式的选择触发对所述待测组织中所述目标组织区域对应的子组织进行应变弹性成像。
  14. 根据权利要求13所述的方法，其特征在于，所述控制超声探头向目标对象的待测组织发射第一超声波之前，所述方法还包括：
    提供超声成像模式的选择方式；
    基于对所述超声成像模式的选择触发对所述待测组织进行超声成像；
    所述基于对所述应变弹性成像模式的选择触发对所述待测组织中所述目标组织区域对应的子组织进行应变弹性成像包括：
    将所述超声成像模式切换至所述应变弹性成像模式。
  15. 一种应变弹性成像方法，其特征在于，所述方法包括：
    提供应变弹性成像模式的选择方式；
    基于对所述应变弹性成像模式的选择控制超声探头向目标对象的待测组织发射超声波，接收所述超声波的回波，基于所述超声波的回波获取超声回波数据；
    基于所述超声回波数据生成超声图像，并获取所述超声图像中的目标组织区域；
    基于所述超声回波数据计算所述目标组织区域的应变；
    基于所述目标组织区域的应变生成并显示所述目标组织区域的应变 弹性图像。
  16. 一种应变弹性成像方法，其特征在于，所述方法包括：
    提供超声成像模式的选择方式和应变弹性成像模式的选择方式；
    基于对所述超声成像模式的选择控制超声探头向目标对象的待测组织发射超声波，接收所述超声波的回波，基于所述超声波的回波获取超声回波数据；
    基于所述超声回波数据生成超声图像，并获取所述超声图像中的目标组织区域；
    基于对所述应变弹性成像模式的选择将所述超声成像模式切换至所述应变弹性成像模式，并控制超声探头至少向所述待测组织中所述目标组织区域对应的子组织发射第二超声波，接收所述第二超声波的回波，基于所述第二超声波的回波获取第二超声回波数据；
    基于所述第二超声回波数据计算所述目标组织区域的应变；
    基于所述目标组织区域的应变生成并显示所述目标组织区域的应变弹性图像。
  17. 根据权利要求15或16所述的方法，其特征在于，所述基于所述目标组织区域的应变生成所述目标组织区域的应变弹性图像，包括：
    基于所述目标组织区域的应变进行图像特征映射以生成所述目标组织区域的应变弹性图像。
  18. 一种应变弹性成像装置，其特征在于，所述装置包括超声探头、发射电路、接收电路和处理器，其中：
    所述发射电路用于激励所述超声探头向目标对象的待测组织发射超声波；
    所述接收电路用于控制所述超声探头接收自所述待测组织返回的超声回波，以获取超声回波信号；
    所述处理器用于根据所述超声回波信号生成超声图像数据；
    所述处理器还用于执行权利要求1-17中的任一项所述的应变弹性成像方法。
  19. 一种存储介质，其特征在于，所述存储介质上存储有计算机程序，所述计算机程序在运行时执行如权利要求1-17中的任一项所述的应变弹 性成像方法。
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