JP5087341B2 - Ultrasonic diagnostic equipment - Google Patents

Description

  The present invention relates to an ultrasonic diagnostic apparatus for generating and displaying a tomographic image of a target region in a subject and an elastic image indicating the hardness or softness of a living tissue using ultrasonic waves.

  The ultrasonic diagnostic apparatus transmits an ultrasonic wave to the inside of the subject by an ultrasonic probe, receives an ultrasonic reception signal that is a reflected echo signal of an ultrasonic wave corresponding to the structure of the living tissue from the inside of the subject, for example, A tomographic image such as an ultrasonic tomographic image is reconstructed and displayed for diagnosis.

  In recent years, the ultrasonic reception signal is measured by compressing a subject with an ultrasonic probe by a manual or mechanical method, and frame data (hereinafter referred to as RF signal frame data) of two ultrasonic reception signals having different measurement times. )), The displacement of each part of the living body caused by the compression is obtained, and the elasticity information such as the displacement, strain, elastic modulus and the like of the living tissue of each part in the frame is obtained based on the displacement data, and the elasticity image is generated. It has been proposed.

  Further, the distortion obtained for each part in the frame is compared with one or a plurality of set thresholds to detect a plurality of areas having different elasticity, and the boundary lines of these areas are overlaid on the elasticity image and drawn. Has been proposed (for example, Patent Document 1). This method can be applied to elastic scoring for diagnosing the degree of malignancy of a tumor by observing the hardness and distribution of a lesion such as a tumor.

  In addition, a reference region is set for a tissue that appears to be normal or benign on an elastic image, a region of interest (ROI) is set for a region of interest to be diagnosed, and an average value of distortions obtained for each region in each region is obtained. It has been proposed to calculate the strain ratio of these two regions and display the calculated strain ratio value superimposed on the elastic image (for example, Patent Document 2). According to this, the difference in tissue hardness of the region of interest with respect to the reference region can be quantitatively evaluated, which can be linked to a highly accurate diagnosis.

JP 2004-135929 A WO2006 / 013916

  By the way, since the strain is a value obtained by spatially differentiating the displacement of the living tissue, it varies depending on the magnitude of the compression force. Elastic information. Therefore, according to the technique described in Patent Document 1 that detects the boundary of a region with different distortion compared to a threshold value, the boundary of a region with different elasticity is quantified unless the threshold value is changed according to the strength of compression. Therefore, it cannot be detected with high accuracy.

  Therefore, it is conceivable to detect the size of the compression with a pressure sensor, etc., and automatically change the threshold value of the strain according to the strength of the compression to automatically detect the boundary of the region with different elasticity quantitatively with high accuracy. However, in order to detect the compression force by the pressure sensor, there remains a problem that must be solved by a detection method and the like.

  In addition, in the case of a tumor that is unevenly distorted in the periphery, it is difficult to identify how the tumor has spread because boundary extraction based on the threshold value of elasticity information can only detect areas with the same elasticity information. . As a result, for example, there is a possibility that the extraction range by surgery cannot be accurately determined.

  The problem to be solved by the present invention is to quantitatively detect a boundary between biological tissues having different elasticity.

The present invention, tomographic images and an elastic based on the reflected echo signal of the tomographic site of the subject received by the ultrasonic probe you transmitting and receiving ultrasonic waves, wherein the ultrasonic probe between the object and image Zo構 forming means for generating an image, the basic configuration of the ultrasonic diagnostic apparatus having a display means for displaying the image generated by該画Zo構 formed unit.

In particular, in order to solve the above problems, the ratio of the elasticity information of the plurality of measurement points of the tomographic image and the elastic one put on the reference area set in the image that the elastic information of the image and the elastic image The elastic image is divided into a plurality of regions having different elastic ratios based on the elastic ratio calculating means for obtaining the elastic ratio, and the elastic ratio and the predetermined threshold value at each obtained measurement point. characterized by comprising a boundary detector for detecting a line, a boundary line drawing means demarcating drawing the said detected boundaries.

  That is, the compressive force applied to the subject by the ultrasound probe is substantially the same in the depth direction of the subject, and is therefore applied to each part of the elastic image generated based on the same RF signal frame data. The compression force can be considered to be almost the same. Therefore, the compression force applied to the tissue in the reference region set in the same elasticity image and the compression force applied to the other tissue other than the reference region can be considered to be substantially the same. If the ratio of information (elastic ratio) is taken, the element of compression force can be eliminated. Therefore, by obtaining the elasticity ratio, which is the ratio of the elasticity information of the reference area and the elasticity information of other tissues other than the reference area, and setting the threshold value by the elasticity ratio, the boundary of the biological tissue with different elasticity affects the compression situation. It is possible to detect with high accuracy. As a result, it is possible to visually grasp how the tumor has spread, etc., and link it to a highly accurate diagnosis. For example, it is possible to accurately determine the surgical extraction range.

  In the present invention, the tissue region in which the reference region (ROR) is set can be set to, for example, an adipose tissue with little individual difference between subjects. Further, as the elasticity information of the reference region, the average value of the strain or the elastic modulus at each measurement point in the reference region can be used.

  Further, the region other than the reference region for obtaining the elastic ratio may be the entire region of the elastic image, but the processing time can be reduced by obtaining the elastic ratio by focusing on one or a plurality of regions of interest (ROI).

  Furthermore, in the present invention, by setting a plurality of elastic ratio thresholds, for example, the distribution of the sclerosing region of the entire tumor can be grasped, and the tumor extent can be easily diagnosed by accurately diagnosing the spread of the tumor. Judgment can be made.

  Further, in the present invention, a change rate calculation means for obtaining a change rate of the elastic ratio between a plurality of boundary lines corresponding to a plurality of threshold values, and a graph of the obtained change rate are drawn in association with the elasticity image. A change rate graph drawing means can be provided. According to this, since it is possible to grasp the change in the hardening of the tumor, it is possible to identify the type of tumor having a characteristic in the internal structure of the tumor. In this case, the direction in which the change rate of the elastic ratio is desired to be observed can be set on the elastic image as a reference line.

  Further, the boundary line drawing means of the present invention can display an elastic image by attaching a hue corresponding to the rate of change to a region between a plurality of boundary lines. According to this, it is possible to easily grasp the change in the hardening of the tumor, and it becomes easy to identify the type of tumor having a characteristic in the internal structure of the tumor.

  Furthermore, a plurality of reference areas are set, and the boundary line detection means can obtain the elastic ratios for the plurality of reference areas and draw the boundary lines in comparison with one or a plurality of threshold values. This makes it possible to evaluate the elastic ratio with reference regions of different tissues. For example, when the lesion tissue is complex, it is possible to see the correlation between the boundary lines by drawing the boundary lines using threshold values obtained based on a plurality of reference regions. The plurality of reference regions can be set, for example, in adipose tissue and organs. In other words, by automatically drawing the boundary line between the tissue that becomes the multiple reference regions and the elastic ratio of any number of regions of interest that exceed the threshold elastic ratio, the fat layer can be formed like the liver or thyroid gland. Tumors can be evaluated even in organs that are difficult to use in the reference region.

  According to the present invention, it is possible to quantitatively detect a boundary between regions having different elasticity.

  An ultrasonic diagnostic apparatus of the present invention will be described based on an embodiment. FIG. 1 is a block diagram showing the configuration of the ultrasonic diagnostic apparatus according to this embodiment. As shown in the figure, the ultrasonic diagnostic apparatus of the present embodiment has an ultrasonic probe 12 used in contact with the subject 10 and a time interval between the subject 10 via the ultrasonic probe 12. And a transmission unit 14 that repeatedly transmits ultrasonic waves, and a reception unit 16 that receives a time-series reflection work signal (RF signal) generated from the subject 10. The transmission / reception control unit 17 controls the transmission timing of the transmission unit 14 and the reception timing of the reception unit 16. The RF signal received by the receiving unit 16 is input to the phasing addition unit 18, and the phasing addition unit 18 performs phasing addition on the input RF signal to generate RF signal frame data.

  The RF signal frame data generated by the phasing addition unit 18 is input to the tomographic image construction unit 20. Based on the input RF signal frame data, the tomographic image construction unit 20 reconstructs a tomographic image of a tomographic site of the subject 10 scanned by the ultrasound probe 12, for example, a black and white tomographic image. The tomographic image data of the black and white tomographic image reconstructed by the tomographic image construction unit 20 is input to the black and white scan converter 22. The black and white scan converter 22 converts the input tomographic image data so as to match the display of the image display 26.

  On the other hand, the RF signal frame data selection unit 28 stores the RF signal frame data output from the phasing addition unit 18, selects at least two pieces of frame data having different acquisition times, and outputs them to the displacement measurement unit 30. . The displacement measuring unit 30 measures the displacement of the living tissue of the subject 10 based on the input two pieces of frame data, and outputs the displacement information to the elasticity information calculating unit 32. The elasticity information calculation unit 32 obtains elasticity information such as strain or elastic modulus based on the input displacement information, and outputs the obtained elasticity information to the elasticity image construction unit 34. The elastic image construction unit 34 composes a color elastic image based on the inputted elasticity information, and outputs the color elastic image data to the color scan converter 36. The color scan converter 36 converts the input color elasticity image data so as to match the display of the image display 26. The switching addition unit 24 performs switching for superimposing the monochrome tomographic image and the color elastic image output from the monochrome scan converter 22 and the color scan converter 36 or displaying them in parallel, and displays the synthesized composite image as an image display. The data is output to the display 26 and displayed.

  Here, the detail of each part of the ultrasonic diagnostic apparatus of FIG. 1 is demonstrated. The ultrasonic probe 12 is formed by arranging a plurality of transducers, and has an ultrasonic transmission / reception surface that transmits / receives ultrasonic waves to / from the subject 10 via the transducers. Further, the ultrasound transmitting / receiving surface of the ultrasound probe 12 is brought into contact with the body surface of the subject 10 to apply a compressive force to the subject 10. This compression force can be applied by means of use or mechanical means.

  The transmission unit 14 has a function of generating a transmission pulse for generating an ultrasonic wave by driving the ultrasonic probe 12 and setting a convergence point of the transmitted ultrasonic wave to a certain depth. Yes. The receiving unit 16 amplifies the reflected echo signal received by the ultrasonic probe 12 with a predetermined gain to generate an RF signal, that is, a received signal. The phasing addition unit 18 receives the RF signal amplified by the reception unit 16 and performs phase control, and forms an ultrasonic beam at one point or a plurality of convergence points to generate RF signal frame data.

  The tomographic image construction unit 20 receives the RF signal frame data from the phasing addition unit 18 and performs signal processing such as gain correction, log compression, detection, contour enhancement, filter processing, etc., and generates tomographic image data. The monochrome scan converter 22 also includes an A / D converter that converts tomographic image data from the tomographic image construction unit 20 into a digital signal, a frame memory that stores a plurality of converted tomographic image data in time series, and a control. It is configured to include a controller. The black and white scan converter 22 acquires tomographic frame data in the subject stored in the frame memory as one image, and reads the acquired image frame data in synchronization with the television.

  The RF signal frame data selection unit 28 stores a plurality of RF signal frame data from the phasing addition unit 18, and selects one set, that is, two RF signal frame data from the stored RF signal frame data group. For example, the RF signal frame data generated in time series from the phasing adder 18 based on the frame rate of the image is sequentially stored in the RF signal frame data selector 28, and the stored RF signal frame data (N) is stored in the first order. One RF signal frame data (N−M, N−2, N−3,..., N−M) is selected from the RF signal frame data group (N−1, N−2, N−3,. X) is selected. Here, N, M, and X are index numbers assigned to the RF signal frame data, and are natural numbers.

  The displacement measuring unit 30 performs one-dimensional or two-dimensional correlation processing from the selected set of data, that is, RF signal frame data (N) and RF signal frame data (X), and corresponds to each measurement point of the tomographic image. A one-dimensional or two-dimensional displacement distribution relating to the displacement vector of the living tissue, that is, the direction and magnitude of the displacement is obtained. Here, a block matching method is used to detect the displacement vector. The block matching method is to divide an image into blocks consisting of, for example, n × n pixels, focus on the block in the region of interest, find the block closest to the block of interest from the previous frame, and move the block Calculate the displacement vector by calculating the quantity.

  The elasticity information calculation unit 32 calculates the strain of the biological tissue at each measurement point on the tomographic image from the displacement vector output from the displacement measurement unit 30, and generates elasticity frame data based on the strain. If the displacement of the measurement point ij measured by the displacement measuring unit 30 is ΔLij, the distortion Δεij is calculated by spatially differentiating ΔLij.

  The elasticity information calculation unit 32 calculates the change Δσij of the stress σij at each measurement point ij on the tomographic image from the calculated strain and the pressure value output from the pressure measurement unit 37, and obtains the calculated stress change and the previous one. Based on the strain, the elastic modulus of the living tissue at each measurement point is calculated, and elastic frame data can be generated based on the elastic modulus. That is, the elastic modulus at each measurement point ij, for example, Young's modulus Yij, is obtained by Yij = Δσij / Δεij. From the Young's modulus Yij, the elastic modulus of the living tissue at each measurement point of the tomographic image is obtained. The Young's modulus is a ratio of a simple tensile stress applied to the object and a strain generated in parallel with the tension.

  The elastic image construction unit 34 is configured to include a frame memory and an image processing unit, and secures elastic frame data output in time series from the elastic information calculation unit 32 in the frame memory. In contrast, image processing is performed.

  The color scan converter 36 has a function of adding hue information to the elastic frame data from the elastic image construction unit 34. That is, the light is converted into the three primary colors (red (R), green (G), and blue (B)) based on the elastic frame data. For example, elastic information with a large strain is converted into a red code, and elastic information with a small strain is converted into a blue code.

  The switching addition unit 24 includes a frame memory, an image processing unit, and an image selection unit. The frame memory stores tomographic image data from the monochrome scan converter 22 and elasticity image data from the color scan converter 36. The image processing unit combines the tomographic image data and the elasticity image data secured in the frame memory by changing the combining ratio. For example, the luminance information and hue information of each pixel of the composite image are obtained by adding the information of the black and white tomographic image and the color elastic image at the composite ratio. Further, the image selection unit selects an image to be displayed on the image display 26 from the tomographic image data and elasticity image data in the frame memory and the composite image data of the image processing unit.

  Next, the structure of the characteristic part which concerns on this invention is demonstrated. The present invention is characterized in that a boundary between biological tissues having different elasticity is quantitatively detected with high accuracy. As shown in FIG. 1, the embodiment for realizing such a feature includes a boundary processing unit 38, a boundary line drawing unit 39, a change rate processing unit 40, a control unit 42, and an elastic information output unit 44. Configured.

  The elasticity information output unit 44 sends the elasticity image frame data output from the color scan converter 36 to the switching addition unit 24, and sends the elasticity image frame data to the boundary processing unit 38 based on a command from the control unit 42. It is supposed to be.

  The control unit 42 includes an input unit that sets the reference region ROR of the biological tissue on the elastic image displayed on the image display 26 via the elastic information output unit 44. Note that the input means for setting the reference region ROR of the control unit 42 may set the reference region ROR on the image of the tomographic image displayed on the image display 26. A plurality of reference regions ROR can be set. Further, the control unit 42 is configured to set one or a plurality of threshold values of the elastic ratio, which will be described later, automatically or manually.

  The boundary processing unit 38 includes an elastic ratio calculation unit 38a and a boundary line detection unit 38b. The elasticity ratio calculation unit 38a takes in the frame data of the elasticity image sent from the elasticity information output unit 44 and the data of the reference region ROR set by the control unit 42, and the distortion or elastic modulus of each measurement point in the reference region ROR. The average value of the elasticity information is obtained, and the average value of the elasticity information and the elasticity information and the ratio of the plurality of measurement points ij of the elasticity image in the observation area other than the reference area ROR are obtained as the elasticity ratio.

  The boundary line detection unit 38b compares the elasticity ratio of each measurement point ij obtained by the elasticity ratio calculation unit 38a with one or more threshold values of the elasticity ratio input from the control unit 42, and elasticizes the elasticity image. The boundary line of each region is detected by dividing it into a plurality of regions having different ratios. When a plurality of threshold values of the elastic ratio are set, the boundary line detection unit 38b detects a plurality of boundary lines.

  The boundary line drawing unit 39 generates image data of the boundary line of each region obtained by the boundary line detection unit 38b. The generated boundary line image data is temporarily stored in the frame data of the switching addition unit 24. Thereby, the image processing unit of the switching addition unit 24 draws boundary lines of a plurality of regions having different elastic ratios on the color elastic image displayed on the image display 26.

  When there are a plurality of boundary lines obtained by the boundary line detection unit 38b, the change rate processing unit 40 includes a change rate calculation means for obtaining a change rate of the elastic ratio between the plurality of boundary lines, and a change rate graph A change rate graph drawing means for generating image data is provided. The image data of the change rate graph is temporarily stored in the frame data of the switching addition unit 24. The image processing unit of the switching addition unit 24 draws the change rate graph in association with the color elastic image displayed on the image display 26.

  Hereinafter, specific processing procedures for detecting the boundary of a living tissue having different elasticity in this embodiment quantitatively with high accuracy, and an image of a boundary line generated thereby will be described in specific examples. .

  A first embodiment in which the boundary between biological tissues having different elasticity is quantitatively detected with high accuracy will be described with reference to FIGS. The present embodiment is an example in which a tumor boundary detection process is performed using a strain as elasticity information, a strain ratio as an elasticity ratio, and a strain ratio threshold value as a threshold value of the elasticity ratio, and an image is displayed. FIG. 2 is a flowchart showing a processing procedure related to the boundary processing unit 38 and the control unit 42, and FIG. 3 is an example of a display image of an elasticity image and a boundary line according to the present embodiment.

  In step S1 of FIG. 2, as shown in FIG. 3A, the tissue (for example, a fat layer) to be a tissue elastic reference body 46 is controlled on the elastic image 45 displayed on the image display 26, for example. A reference region (ROR: Region of Reference) 47 is set through the unit 42. Then, the distortion at each measurement point of the ROR 47 of the elasticity image 45 input from the elasticity information output unit 44 is extracted, and the average value εmean of the distortion of the ROR 47 is calculated.

  Next, in step S2, the region of interest (ROI: Region of Interest) that is set to include the entire observation region excluding the ROR 47 of the elastic image 45 or the region of interest such as the tumor 48 is expressed by Equation (1). Then, the strain ratio Rij is calculated by dividing the strain average value εmean in the ROR 47 by the strain Δεij of each measurement point ij input from the elasticity information output unit 44.

Rij = εmean / Δεij (1)
Next, in step S3, the distortion ratio Rij at each measurement point ij is compared with a distortion ratio threshold Sk (k = 1) set by the examiner, and a measurement point satisfying Rij ≦ S1 is extracted. In step S4, the region is divided into a region of Rij ≦ S1 including the extracted measurement points and a region of Rij> S1, the boundary points are determined, and a boundary line B1 connecting the boundary points is obtained.

  The coordinate data of the boundary line B1 is output to the boundary line drawing unit 39, converted into image data of the boundary line, and output to the switching addition unit 24. The switching addition unit 24 adds and combines the boundary line image data with the frame data of the elastic image, and synthesizes the elastic image 49 on which the boundary line B1 is displayed as shown in FIG. 26. At this time, the elastic image 49 displays the display line of the color corresponding to the boundary line B1 and the threshold value S1 in association with each other.

  According to the present embodiment described above, the compression force applied to the subject 10 by the ultrasonic probe 12 is substantially the same in the depth direction of the subject 10, so that the elasticity image 45 in FIG. The compression force applied to the ROR 47 and the compression force applied to the observation region or the region of interest can be considered to be substantially the same. Therefore, the distortion ratio Rij at each measurement point ij is an index value from which the influence of the compression force is eliminated. Then, by comparing the distortion ratio Rij of each measurement point ij with the threshold value of the distortion ratio, it is possible to detect the boundary of the living tissue with different distortion with high accuracy without being affected by the compression state (compression strength).

  As a result, it is possible to visually grasp how a lesion site such as a tumor has spread, etc., and link it to a highly accurate diagnosis. For example, it is possible to accurately determine the surgical extraction range.

  In the present embodiment, an example is shown in which the ROR 47 is set to an adipose tissue with a small individual difference between subjects. However, the present invention is not limited to this, and an arbitrary living tissue is selected as a reference body and the ROR 47 is set. Can do.

  The region other than the ROR 47 for obtaining the distortion ratio may be the entire region of the elastic image, but the processing time can be shortened by obtaining the distortion ratio by focusing on one or more regions of interest (ROI).

  A second embodiment in which a boundary between biological tissues having different elasticity is automatically detected quantitatively with high accuracy will be described with reference to FIG. This embodiment is different from the first embodiment in that a plurality of distortion ratio threshold values are set. Since the other points are the same as those in the first embodiment, the flowchart of the processing procedure related to the boundary processing unit 38 and the control unit 42 is omitted, and the elasticity image and the boundary according to the present embodiment shown in FIG. 4 are used. A description will be given with reference to an example of a line display image.

  As shown in FIG. 4A, an ROR 47 is provided on a tissue (for example, a fat layer) to be a tissue elasticity reference body 46 on the elasticity image 45 displayed on the image display 26 via the control unit 42. The setting point is the same as in the first embodiment. In this embodiment, a plurality of distortion ratio threshold values Sk (for example, k = 1, 2, 3, 4) are set manually or automatically by the examiner via the control unit 42.

  The processing in steps S1 and S2 in FIG. 2 is the same in this embodiment. In step S3, a plurality of strain ratio threshold values Sk are compared with the strain ratio Rij of each measurement point ij and divided into a plurality of tissue regions. Here, for example, when the strain ratio Rij of each measurement point ij is defined as in equation (1), the larger the value of Rij, the harder tissue that the strain Δεij is smaller and is not distorted. Note that the strain ratio can be defined by exchanging the numerator and denominator on the right side of Equation (1). In this case, the larger the value of Rij, the larger the strain Δεij and the softer the tissue. Now, it is assumed that the distortion ratio Rij is defined as in the equation (1), and the four threshold values S1 to S4 of the distortion ratio are set to satisfy the relationship of S1> S2> S3> S4. In this case, the distortion ratio Rij of each measurement point ij is extracted by being classified into the following regions.

Rij> S1 region,
Region of S1 ≧ Rij> S2,
Region of S2 ≧ Rij> S3,
Region of S3 ≧ Rij> S4,
Rij ≦ S4 region,
Then, in step S4 in FIG. 2, the boundary points of each region are determined, and boundary lines B1 to B4 connecting the boundary points are obtained. The obtained coordinate data of the boundary lines B <b> 1 to B <b> 4 is output to the boundary line drawing unit 39, converted into image data of the boundary line, and output to the switching addition unit 24. The switching addition unit 24 adds and synthesizes the boundary line image data to the elastic image frame data, and synthesizes the elastic image 50 on which the boundary lines B1 to B4 are superimposed as shown in FIG. This is displayed on the display 26. At this time, display lines of colors corresponding to the boundary lines B1 to B4 and threshold values S1 to S4 are displayed in the elastic image 50 in association with each other.

  With this configuration, according to the second embodiment, in addition to the effects of the first embodiment, the living tissue is divided into a plurality of regions according to the magnitude of the strain ratio, and the boundaries between the plurality of regions. Since each line is displayed, for example, the distribution of the sclerosing region of the entire tumor can be grasped, the spread of the tumor can be accurately diagnosed, and the treatment range of the tumor can be easily determined. In other words, since the tumor is hardened as it becomes malignant, it is possible to accurately diagnose the spread of the tumor by grasping the distribution of the hardened region of the whole tumor by displaying the boundary between the regions of different hardness Therefore, it becomes possible to easily determine the treatment range of the tumor.

  With reference to FIG. 5 and FIG. 6, a description will be given of a third embodiment in which a boundary between biological tissues having different elasticity is automatically detected quantitatively with high accuracy. The difference between the present embodiment and the second embodiment is that the change rate of the distortion ratio is calculated by differentiating the interval (width) between the boundary lines Bk detected from the threshold values Sk of the plurality of distortion ratios, and the color coding. And graph it.

  In step S11 of FIG. 5, the reference line 60 is set on the elastic image 50 in which the boundary line Bk (k = 1 to 4) is drawn, as shown in FIG. 6, manually or automatically via the control unit 42. . The reference line 60 can be set at an arbitrary position where it is desired to visually observe the change in the distortion ratio between the boundary lines Bk.

  In step S12, the change rate processing unit 40 obtains the coordinates A to L of the intersection between the reference line 60 and each boundary line Bk, obtains the interval Δx on the reference line 60 between the adjacent coordinates A to L, The distortion ratio change rate ΔRk is obtained by dividing the difference ΔSk between the thresholds Sk related to the two corresponding boundary lines Bk by Δx.

  In step S 13, the distortion ratio change rate ΔRk is graphed in association with the elastic image, and the image data is output to the switching addition unit 24. As shown in the lower diagram of FIG. 6, the distortion ratio change graph 61 is generated with the vertical axis corresponding to the distortion ratio and the horizontal axis corresponding to the position of the reference line 60. The switching addition unit 24 adds and synthesizes the graph of the change rate of the distortion ratio in association with the elastic image 50 and displays the resultant on the screen display 26.

  Here, the rate-of-change processing unit 40 can display the graph line 62 in a region with a large rate of change by color coding. Further, the color or luminance of the elastic image corresponding to the line 62 of the graph with a large change rate is, for example, “blue” or “bright” when the change rate is large, and “red” or “dark” when the change rate is small. Can be set.

  By graphing the rate of change of the strain ratio as in this embodiment, it is possible to visually grasp the change in the hardening of the tumor in the reference line direction. This makes it possible to identify the type of tumor that is characterized by the internal structure.

  A fourth embodiment in which the boundary between biological tissues having different elasticity is automatically detected quantitatively with high accuracy will be described with reference to FIG. The difference between the present embodiment and the other embodiments 1 to 3 is that a plurality of different living tissues are used as reference bodies, reference regions ROR are set for the respective reference bodies, and distortion with the tissues serving as the plurality of reference bodies is set. It is possible to extract a boundary of a region where the ratio exceeds a single or a plurality of set threshold values. As a result, even in an organ such as the liver or thyroid gland where it is difficult to use the fat layer as a reference body, it is possible to perform tissue diagnosis based on the strain distribution in the same region.

  FIG. 7A is a diagram corresponding to FIG. 3A of the first embodiment, and a plurality (m) of reference bodies for tissue elasticity are displayed on the elastic image 70 displayed on the image display 26, for example. Set ROR (m) for the organization. In the example of FIG. 7A, m is A to C, ROR (A) is set in the fat layer 46, ROR (B) is set in the tissue 71 surrounding the tumor 48, and ROR (C) is set in the tissue 73. To do. Then, the distortion at each measurement point of the ROR (m) of the elasticity image 70 input from the elasticity information output unit 44 is extracted, and the average value εmean (m) of the ROR distortion is calculated.

  Next, the average value εmean (m) of the strain of each ROR is measured from the elasticity information output unit 44 for the entire observation region excluding ROR (A) of the elastic image 70 in the same manner as Expression (1). A distortion ratio Rij (m) is calculated by the following equation (2) by dividing by the distortion Δεij at the point ij.

Rij (m) = εmean (m) / Δεij (2)
Next, the distortion ratio Rij (m) of each measurement point ij is compared with a distortion ratio threshold Sk set by the examiner, and a measurement point satisfying Rij (m) ≦ Sk is extracted. Then, it is divided into a region of Rij (m) ≦ Sk including the extracted measurement points and a region of Rij (m)> Sk, the boundary point is determined, and the boundary line B (m) connecting these boundary points is defined. Ask. For example, assuming that the distortion ratios Rij (m) corresponding to ROR (A) to (C) are distortion ratios A to C, the boundary lines B (A) to (C) are obtained correspondingly.

  The coordinate data of the boundary line B (m) is output to the boundary line drawing unit 39, converted into image data of the boundary line, and output to the switching addition unit 24. The switching addition unit 24 adds the image data of the boundary line to the frame data of the elastic image and combines them, and the boundary lines B (A) to (C) are displayed in an overlapping manner as shown in FIG. The elastic image 75 is displayed on the screen display 26. At this time, display lines of colors corresponding to the boundary lines B (A) to (C) and distortion ratios A to C are displayed in the elastic image 49 in association with each other.

  FIG. 8 shows another example of the elasticity image of this embodiment. In the elastic image 80 shown in FIG. 8A, a complicated lesion 81 is displayed. In such a case, in addition to the fat layer 46, the organ 82 shown in the same frame is selected as a reference body, and ROR (A) and (B) are set for each reference body tissue. Similarly to the above, when the distortion ratios A and B are obtained and the boundary lines B (A) and (B) are obtained, the boundary lines B (A) and (B) are obtained as shown in FIG. An elastic image 85 displayed in an overlapping manner is obtained.

  According to the present embodiment, in addition to the effects of the first to fourth embodiments, even in an organ in which it is difficult to use the fat layer as a reference body, it is possible to perform tissue diagnosis based on strain distribution at the same site. . In particular, in the case of a complicated lesion, an appropriate diagnosis can be performed by observing the correlation between the boundary lines obtained based on a plurality of reference body tissues. For example, when performing a cell inspection of a lesioned part, the accuracy of the inspection is improved by performing the inspection on a region where a plurality of boundary lines overlap. That is, it can be considered that there is a high probability that a region shared by a boundary drawn using a plurality of reference body tissues is a true lesion. In the case where a part having a difference in hardness between individuals is used as a reference body tissue, it is considered that detection accuracy can be improved by using a plurality of reference body tissues.

  In Examples 1 to 4 described above, the strain ratio is used as the elasticity information of the reference region ROR, the observation region, or the region of interest. However, the present invention is not limited to this, and other elastic information such as elastic modulus can be applied. For example, it is possible to detect a boundary between biological tissues having different elastic moduli using an elastic modulus and an elastic modulus ratio.

It is a block block diagram of one Embodiment of the ultrasonic diagnosing device of this invention. It is a flowchart which shows the process sequence of Example 1 of the characteristic part of this invention. FIG. 6 is a diagram illustrating a display example of an elasticity image according to the first embodiment. It is a figure which shows the example of a display of the elasticity image of Example 2 of the characteristic part of this invention. It is a flowchart which shows the process sequence of Example 3 of the characteristic part of this invention. 10 is a diagram illustrating a display example of an elasticity image of Example 3. FIG. It is a figure which shows the example of a display of the elasticity image of Example 4 of the characteristic part of this invention. FIG. 10 is a diagram illustrating a display example of an elasticity image according to a modification of the fourth embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Subject 12 Ultrasonic probe 20 Tomographic image structure part 22 Black-and-white scan converter 24 Switching addition part 26 Image display device 28 RF signal frame data selection part 30 Displacement measurement part 32 Elastic information calculation part 34 Elastic image structure part 36 Color scan Converter 38 Boundary processing unit 38a Elastic ratio calculation unit 38b Boundary line detection unit 39 Boundary line drawing unit 40 Change rate processing unit 42 Control unit 44 Elastic information output unit

Claims (3)

An image that generates a tomographic image and an elastic image based on an ultrasonic probe that transmits and receives ultrasonic waves to and from the subject, and a reflected echo signal of a tomographic region of the subject that is received by the ultrasonic probe In an ultrasonic diagnostic apparatus comprising: a configuration unit; and a display unit that displays an image generated by the image configuration unit.
Elastic ratio calculation means for obtaining, as an elastic ratio, a ratio between elasticity information in a reference region set on one of the tomographic image and the elasticity image and the elasticity information at a plurality of measurement points of the elasticity image; Boundary line detecting means for detecting the boundary line of each region by dividing the elastic image into a plurality of regions having different elastic ratios based on the elastic ratio at each measurement point and a preset threshold value, and detected A border line drawing means for drawing the border line;
A plurality of the reference areas are set,
The elastic ratio calculation means obtains the elastic ratio of each measurement point with respect to a plurality of the reference regions,
The boundary line detection means detects the boundary line based on the obtained elastic ratio and a threshold value of one,
The ultrasonic diagnostic apparatus, wherein the boundary line drawing means creates the image data by associating the boundary line with an elastic ratio with respect to each reference region . An image that generates a tomographic image and an elastic image based on an ultrasonic probe that transmits and receives ultrasonic waves to and from the subject, and a reflected echo signal of a tomographic region of the subject that is received by the ultrasonic probe In an ultrasonic diagnostic apparatus comprising: a configuration unit; and a display unit that displays an image generated by the image configuration unit.
Elastic ratio calculation means for obtaining, as an elastic ratio, a ratio between elasticity information in a reference region set on one of the tomographic image and the elasticity image and the elasticity information at a plurality of measurement points of the elasticity image; Boundary line detecting means for detecting the boundary line of each region by dividing the elastic image into a plurality of regions having different elastic ratios based on the elastic ratio at each measurement point and a plurality of preset threshold values. A boundary line drawing means for drawing a plurality of boundary lines on an elastic image; and a rate of change of an elastic ratio between the plurality of boundary lines on a reference line set on the elastic image on which the plurality of boundary lines are drawn And a change rate processing means for generating image data of the change rate graph with the vertical axis as the elastic ratio and the horizontal axis as the position of the reference line . The ultrasonic diagnostic apparatus according to claim 2,
The ultrasonic diagnostic apparatus characterized in that the change rate processing means displays the lines of the graph between the boundary lines having a large change rate in different colors .

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