Elastic image imaging method, device and ultrasonic imaging equipment

Abstract

This application discloses a dynamic processing method of elastic data applied to elastography, which comprehensively processes at least three frames of target tissue image data, first obtains a number of reference frames according to the multi-frame image data, and determines the pre-compression image and the image after compression, and calculate the strain value for generating the elastic image based on the determined image data before compression and the image data after compression. This application uses dynamic comprehensive processing of multi-frame target tissue image data, so that the obtained relative strain of the target tissue region is as close to the ideal value as possible, improves the quality of elastic data, and improves the output rate of high-quality elastic images. At the same time, the influence of user manipulation can also be reduced. According to the method above, an elastic imaging device and an ultrasonic imaging device are also provided.

Description

technical field

[0001] The present application relates to a medical device, in particular to an elastic image imaging method and its device, and an ultrasonic imaging device. Background technique

[0002] Medical ultrasound elastography mainly refers to a series of imaging and signal processing techniques aimed at displaying tissue elasticity differences. There are currently several categories including pressure elastography, acoustic radiation force imaging (Acoustic Radiation Force Imaging, ARFI), shear wave elastography (Shear Wave Elastography, SWE) and so on. Among them, pressure elastography has the longest development time and the most mature technology. Pressure elastography, as an important auxiliary method for B-mode sonographic detection in cancer detection, especially in the discrimination of benign and malignant breast cancer, has been rapidly applied in clinic.

[0003] Pressure elastography mainly uses a hand-held ultrasonic probe to apply pressure to the ta...

Examples

Embodiment 1

[0053] The inventive idea of ​​this embodiment is to fix the pre-compression image data frame first, and then filter out the compressed data frame with the best matching effect with the pre-compression data frame in several adjacent frames through certain criteria, and then use these two frames to calculate elastic data. Based on this concept, in this embodiment, the reference frame determination module 32 is as Figure 4 As shown, it includes a pre-compression image determination unit 321 , an extraction unit 323 , a quality score calculation unit 324 and a post-compression image determination unit 325 . The pre-compression image determination unit 321 is used to determine a certain frame from the M frames of images as the pre-compression image, and the remaining frames are used as candidate images; Extract some data from the selected image to form a respective data matrix, wherein the number of nodes in the data matrix is ​​less than the number of nodes in the node matrix; ...

Embodiment 2

[0068] The inventive concept of this embodiment is to calculate several sets of elastic data for several frames within a certain range, and the methods for obtaining several sets of elastic data include but are not limited to the calculation of two adjacent frames, the calculation of two frames with fixed intervals, etc., and then All elastic data are composited to obtain one frame of composite elastic data.

[0069] Based on this concept, in this embodiment, N is equal to 2, and the reference frame determination module 32 selects two frames of images at least one frame apart from the M frame images as the pre-compression image and the compressed image respectively, then the calculation module 34 is as follows: Figure 6 As shown, it includes: a second strain value calculation unit 342 and a third strain value calculation unit 343 . The second strain value calculation unit 342 is used to take the image before compression, the image after compression and several frames of image...

Embodiment 3

[0077] When N is equal to 3, in a specific embodiment, the reference frame determination module 32 screens out three frames of images from M frames of images as reference frames, the first frame in the reference frames is used as the image before compression, and the other two frames are used as Compressed image; grid division module 33 is used to carry out grid division of U rows and V columns to the image before compression and the image after two frames of compression; calculation module 34 please refer to Figure 9 , including a cross-correlation phase calculation unit 345 , a displacement matrix calculation unit 346 and a fourth strain value calculation unit 347 .

[0078] The cross-correlation phase calculation unit 345 is used to calculate the cross-correlation phase based on the gridded pre-compression image and the two compressed images using the following formula:

[0079]

[0080] in, is the cross-correlation phase of a node in the node matrix, I 1 and Q 1 is...

technical field

[0001] The present application relates to a medical device, in particular to an elastic image imaging method and its device, and an ultrasonic imaging device. Background technique

[0002] Medical ultrasound elastography mainly refers to a series of imaging and signal processing techniques aimed at displaying tissue elasticity differences. There are currently several categories including pressure elastography, acoustic radiation force imaging (Acoustic Radiation Force Imaging, ARFI), shear wave elastography (Shear Wave Elastography, SWE) and so on. Among them, pressure elastography has the longest development time and the most mature technology. Pressure elastography, as an important auxiliary method for B-mode sonographic detection in cancer detection, especially in the discrimination of benign and malignant breast cancer, has been rapidly applied in clinic.

[0003] Pressure elastography mainly uses a hand-held ultrasonic probe to apply pressure to the ta...

Examples

Embodiment 1

[0053] The inventive idea of ​​this embodiment is to fix the pre-compression image data frame first, and then filter out the compressed data frame with the best matching effect with the pre-compression data frame in several adjacent frames through certain criteria, and then use these two frames to calculate elastic data. Based on this concept, in this embodiment, the reference frame determination module 32 is as Figure 4 As shown, it includes a pre-compression image determination unit 321 , an extraction unit 323 , a quality score calculation unit 324 and a post-compression image determination unit 325 . The pre-compression image determination unit 321 is used to determine a certain frame from the M frames of images as the pre-compression image, and the remaining frames are used as candidate images; Extract some data from the selected image to form a respective data matrix, wherein the number of nodes in the data matrix is ​​less than the number of nodes in the node matrix; ...

Embodiment 2

[0068] The inventive concept of this embodiment is to calculate several sets of elastic data for several frames within a certain range, and the methods for obtaining several sets of elastic data include but are not limited to the calculation of two adjacent frames, the calculation of two frames with fixed intervals, etc., and then All elastic data are composited to obtain one frame of composite elastic data.

[0069] Based on this concept, in this embodiment, N is equal to 2, and the reference frame determination module 32 selects two frames of images at least one frame apart from the M frame images as the pre-compression image and the compressed image respectively, then the calculation module 34 is as follows: Figure 6 As shown, it includes: a second strain value calculation unit 342 and a third strain value calculation unit 343 . The second strain value calculation unit 342 is used to take the image before compression, the image after compression and several frames of image...

Embodiment 3

[0077] When N is equal to 3, in a specific embodiment, the reference frame determination module 32 screens out three frames of images from M frames of images as reference frames, the first frame in the reference frames is used as the image before compression, and the other two frames are used as Compressed image; grid division module 33 is used to carry out grid division of U rows and V columns to the image before compression and the image after two frames of compression; calculation module 34 please refer to Figure 9 , including a cross-correlation phase calculation unit 345 , a displacement matrix calculation unit 346 and a fourth strain value calculation unit 347 .

[0078] The cross-correlation phase calculation unit 345 is used to calculate the cross-correlation phase based on the gridded pre-compression image and the two compressed images using the following formula:

[0079]

[0080] in, is the cross-correlation phase of a node in the node matrix, I 1 and Q 1 is...

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