JP5950291B1 - Ultrasonic diagnostic apparatus and program - Google Patents

Abstract

In an ultrasonic diagnostic apparatus, a three-dimensional elastic image in which noise is not noticeable is formed. Elastic volume data representing an elastic value distribution in the three-dimensional space is formed by transmitting and receiving ultrasonic waves to and from the three-dimensional space in the subject. In the three-dimensional elastic image forming unit 38, a plurality of rays are set for the elastic volume data, and the output light amount calculation using the elastic value and the opacity is sequentially executed for each ray, thereby each ray being processed. The pixel value corresponding to is calculated. As a result, a three-dimensional elastic image is formed. In each output light quantity calculation, the opacity is set according to the elasticity value used in the output light quantity calculation and the noise possibility of the elasticity value. For example, the opacity for an elastic value with a possibility of noise is set smaller than the opacity with respect to an elastic value without a possibility of noise. [Selection] Figure 1

Description

  The present invention relates to an ultrasonic diagnostic apparatus, and more particularly to a technique for forming a three-dimensional elastic image representing an elastic value distribution in a subject.

  In an ultrasonic diagnostic apparatus, for example, a technique for measuring an elastic value (such as tissue strain or elastic modulus) related to the hardness of a tissue such as a tumor is known. For example, a technique is known in which a static pressure is applied from the body surface of a subject by a probe to compress and deform the tissue in the subject, and the strain or the like of the tissue generated at that time is measured by ultrasonic waves. Further, a technique is known in which elastic volume data is formed from a plurality of elastic frame data representing elastic values, and volume rendering is applied to the elastic volume data to form a three-dimensional elastic image (see Patent Document 1).

International Publication No. 2010/026823 International Publication No. 2012/0294558 JP 2012-213545 A Japanese Patent No. 4455003

  By the way, in the case of obtaining an elastic value by compressing a subject with a probe, for example, if the probe is displaced due to camera shake or the like, the pressure applied in the subject becomes non-uniform, resulting in an elastic value. Noise may occur. As a countermeasure against the noise, a technique is known in which the image quality of a plurality of elastic frame data constituting elastic volume data is evaluated, noise frame data with a lot of noise is removed, or noise frame data is replaced with other elastic frame data. (See Patent Document 2). Patent Document 3 describes that noise frame data is not displayed, and Patent Document 4 describes a technique that does not display a noise portion in an elastic image.

  In the technology for removing noise frame data and noise portions, there is a problem that data is lost in the portions from which data is removed, and an unnatural three-dimensional elastic image having no continuity is formed. Further, in the technique of replacing the noise frame data with other elastic frame data, there is a problem that when the noise frame data increases, the replacement portion increases and the true data decreases.

  An object of the present invention is to form a three-dimensional elastic image in which noise is not noticeable in an ultrasonic diagnostic apparatus. Alternatively, the noise is made inconspicuous and an unnatural three-dimensional elastic image having no continuity is not formed.

  The ultrasonic diagnostic apparatus according to the present invention includes elastic volume data acquisition means for acquiring elastic volume data representing an elastic value distribution in the three-dimensional space by transmitting and receiving ultrasonic waves to and from the three-dimensional space in the subject, and the elasticity A pixel value corresponding to each ray is set by setting a plurality of rays for the volume data and sequentially executing an output light amount calculation using the elasticity value and opacity based on the elastic volume data along each ray for each ray. And a three-dimensional elastic image forming means for forming a three-dimensional elastic image, and in calculating each output light amount, the elasticity value used in the output light amount calculation and the noise value of the elasticity value depending on the possibility of noise. And opacity setting means for setting transparency.

  In the above configuration, the elastic value is, for example, strain, elastic modulus, displacement, or the like. For example, ultrasonic waves are transmitted and received in a state where pressure is applied from the body surface of the subject by a probe that transmits and receives ultrasonic waves and the tissue in the subject is compressed, thereby acquiring elastic volume data. . By applying volume rendering to the elastic volume data, three-dimensional elastic image data is formed. In volume rendering, for example, a ray casting method is applied. For example, a plurality of rays are set for the elastic volume data, and the output light amount calculation using the elastic value and the opacity (opacity) is sequentially executed along each ray, thereby forming three-dimensional elastic image data. The A portion in which large opacity is set in the elastic volume data has a higher contribution in the three-dimensional elastic image data, that is, the degree of visualization is increased (displayed sufficiently opaque), and the visibility of the portion is improved. On the other hand, the portion where the small opacity is set in the elastic volume data has a low contribution in the three-dimensional elastic image data, that is, the degree of visualization is low (displayed semi-transparently or becomes sufficiently transparent) and becomes inconspicuous. . By changing the opacity according to the noise possibility of the elasticity value, the non-noisy part is displayed sufficiently opaque and the noisy part is displayed sufficiently transparent or translucent. It becomes possible. As a result, even when the elastic volume data includes a noise portion, the noise portion can be made sufficiently inconspicuous in the three-dimensional elastic image data. Further, since the noise portion is not always completely removed, data loss does not occur. Therefore, it is possible to form natural three-dimensional elastic image data having continuity.

  Preferably, the opacity setting means makes the opacity for an elastic value with a possibility of noise smaller than the opacity with respect to an elastic value without a possibility of noise. As a result, in the three-dimensional elastic image data, the transparency of the part with the possibility of noise becomes higher than the part with no possibility of the noise, and the part with the possibility of noise becomes inconspicuous.

  Preferably, the opacity setting means multiplies a value obtained from an opacity function defining a relationship between the elasticity value and the opacity by a standard weighting factor for an elasticity value having no possibility of noise. Opacity is obtained, and for an elastic value that may cause noise, the opacity is obtained by multiplying the value obtained from the opacity function by a weighting factor smaller than the standard weighting factor.

  The opacity function (opacity function) is a function that defines the relationship between the elasticity value and the opacity. For example, a larger opacity is set for a tissue having a smaller elasticity value (hard tissue), and a smaller opacity is set for a tissue having a larger elasticity value (soft tissue). A weighting factor smaller than the standard weighting factor is used for an elastic value with a possibility of noise. Therefore, the opacity for an elastic value with a possibility of noise is smaller than the opacity with respect to an elastic value without a possibility of noise. As a result, in the three-dimensional elastic image data, a portion having a possibility of noise becomes inconspicuous. It should be noted that an opacity function for an elastic value with no possibility of noise and an opacity function for an elastic value with a possibility of noise may be used. For example, an opacity function for an elastic value with a possibility of noise is a function obtained by multiplying an opacity function for an elastic value with no possibility of noise by a weighting factor smaller than a standard weighting factor. By switching and applying these functions according to the presence or absence of the possibility of noise, it is possible to make a portion with a possibility of noise inconspicuous in the three-dimensional elastic image data.

  Preferably, the elastic volume data acquisition means acquires a plurality of elastic frame data by transmitting and receiving ultrasonic waves to and from the subject, forms the elastic volume data based on the plurality of elastic frame data, and generates noise of an elastic value. The possibility is determined based on whether or not the elasticity value belongs to noise elasticity frame data including noise in the plurality of elasticity frame data.

  According to said structure, it is judged whether it is noise per frame. For example, it is determined whether or not each point (voxel) belonging to each elastic frame data is noise, and elastic frame data in which the ratio of points (voxels) determined to be noise is equal to or greater than a threshold is noise elastic frame data. It is determined that there is. The elasticity value of a point (voxel) belonging to the noise elasticity frame data is processed as an elasticity value with a possibility of noise. In this case, even if a point (voxel) determined not to be noise is included in the noise elastic frame data, the elastic value of the point (voxel) is processed as an elastic value that may cause noise. It will be. Note that noise processing may be executed in units of voxels. That is, the elasticity value of a point (voxel) determined to be noise is processed as an elasticity value with a possibility of noise, and the elasticity value of a point (voxel) determined to be no noise is an elasticity value with no possibility of noise. May be processed as In this case, it is determined whether or not there is noise for each voxel. Therefore, even if a point (voxel) that belongs to the same elastic frame data as a point (voxel) determined to be noise is determined not to be noise, the elasticity value of the point (voxel) is Therefore, it is processed as an elastic value having no possibility of noise.

  The program according to the present invention is an elastic volume data acquisition unit that acquires elastic volume data representing an elastic value distribution in the three-dimensional space, which is formed by transmitting and receiving ultrasonic waves to and from the three-dimensional space in the subject. A plurality of rays are set for the elastic volume data, and an output light amount calculation using the elasticity value and opacity based on the elastic volume data is sequentially executed for each ray along each ray, thereby allowing each ray to be The three-dimensional elastic image forming means for calculating a corresponding pixel value and thereby forming a three-dimensional elastic image, and the elastic value used in the output light amount calculation and the noise possibility of the elastic value when calculating each output light amount The opacity setting means is configured to function as opacity setting means for setting the opacity accordingly.

  According to the present invention, it is possible to form a three-dimensional elastic image in which noise is not noticeable in the ultrasonic diagnostic apparatus.

1 is a block diagram showing an ultrasonic diagnostic apparatus according to an embodiment of the present invention. It is a schematic diagram which shows the scanning surface formed by the scanning of an ultrasonic beam. It is a schematic diagram which shows elastic volume data. It is a figure which shows the opacity function for luminance images. It is a figure which shows the opacity function for elastic images. It is a figure which shows the opacity function for elastic images. It is a figure which shows the relationship between an elastic value and a hue. It is a figure which shows the opacity function for elastic images. It is a schematic diagram which shows a three-dimensional elasticity image. It is a schematic diagram which shows a three-dimensional elasticity image. It is a schematic diagram which shows noise elastic frame data. It is a schematic diagram which shows the elastic volume data containing a noise part. It is a schematic diagram which shows a three-dimensional elasticity image. It is a schematic diagram which shows the sampling point and voxel in volume rendering. It is a schematic diagram which shows elastic frame data and elastic volume data.

  FIG. 1 shows a preferred embodiment of an ultrasonic diagnostic apparatus according to the present invention. FIG. 1 is a block diagram showing the overall configuration. An ultrasonic diagnostic apparatus is an apparatus that is installed in a medical institution such as a hospital and forms an ultrasonic image by transmitting and receiving ultrasonic waves to and from a human body.

  The probe 10 is a transducer that transmits and receives ultrasonic waves. The probe 10 includes a plurality of vibration elements that transmit and receive ultrasonic waves, and an ultrasonic beam is formed by the plurality of vibration elements. In the present embodiment, the probe 10 includes a 1D array transducer and a scanning mechanism that mechanically scans the 1D array transducer. The 1D array vibrator is formed by arranging a plurality of vibration elements in a line. A scanning surface is formed by electronic scanning of the ultrasonic beam by the 1D array transducer, and the scanning surface is mechanically scanned. Thus, a three-dimensional echo data capturing space is formed. Alternatively, the probe 10 may include a 2D array transducer. The 2D array vibrator is formed by two-dimensionally arranging a plurality of vibration elements. An ultrasonic beam is formed by the 2D array transducer, and the ultrasonic beam is scanned two-dimensionally. Thereby, a three-dimensional echo data capturing space is formed. As the electronic scanning method, electronic linear scanning, electronic sector scanning, and the like are known.

  The transmission unit 12 is a transmission beamformer. The transmission unit 12 supplies a plurality of transmission signals having a fixed delay relationship to the plurality of vibration elements of the probe 10 during transmission. Thereby, an ultrasonic transmission beam is formed.

  The receiving unit 14 is a receiving beamformer. The reception unit 14 forms a reception beam by performing phasing addition processing or the like on a plurality of reception signals obtained from a plurality of vibration elements during reception.

  The transmission beam and the reception beam are electronically scanned by the action of the transmission unit 12 and the reception unit 14. Thereby, a beam scanning surface is formed. The beam scanning plane corresponds to a plurality of beam data, which constitute reception frame data (RF signal frame data). Each beam data is composed of a plurality of echo data arranged in the depth direction. By repeating the electronic scanning of the ultrasonic beam, a plurality of reception frame data arranged on the time axis is output from the reception unit 14. They constitute a received frame sequence. It should be noted that techniques such as transmission aperture synthesis may be used in transmission / reception of ultrasonic waves.

  The tomographic image forming unit 18 includes a digital scan converter having a coordinate conversion function, an interpolation processing function, and the like. The tomographic image forming unit 18 performs signal processing such as gain correction, log compression, detection, contour enhancement, and filter processing on the received frame data output from the receiving unit 14 to form tissue display frame data. The tissue display frame data is B-mode tomographic image data. The tomographic image forming unit 18 forms a tissue display frame data sequence composed of a plurality of tissue display frame data based on the received frame data sequence output from the receiving unit 14. The tissue display frame data string is output and displayed on the display unit 42 such as a monitor. As a result, the B-mode tomographic image is displayed as a moving image in real time.

  The luminance volume data forming unit 20 forms luminance volume data based on the tissue display frame data sequence (a plurality of B-mode tomographic image data) formed by the tomographic image forming unit 18. For example, the luminance volume data forming unit 20 forms luminance volume data by sequentially arranging a plurality of tissue display frame data for each beam scanning plane. At this time, the luminance volume data forming unit 20 forms luminance volume data represented by an orthogonal coordinate system by applying coordinate transformation processing, interpolation processing, and the like to the plurality of tissue display frame data.

  The opacity setting unit 22 creates a luminance image opacity function (luminance image opacity function) for forming three-dimensional luminance image data, and sets the luminance image opacity function in the three-dimensional luminance image forming unit 24. To do. In the opacity function for luminance image, opacity (opacity) with respect to the luminance value (echo data) of the luminance volume data is defined.

  The three-dimensional luminance image forming unit 24 forms three-dimensional luminance image data by applying a volume rendering method to the luminance volume data. As the rendering, for example, a ray casting method is used. In the ray casting method, the three-dimensional luminance image forming unit 24 sets a plurality of rays (transmission lines) for luminance volume data, and the luminance value (echo) of each point (voxel) along the ray for each ray. Output light quantity calculation using data and opacity is executed sequentially. Thereby, the pixel value corresponding to each ray is calculated, and three-dimensional luminance image data is formed as a set of a plurality of pixel values. The luminance value, opacity, and output light quantity from each voxel are expressed by, for example, the following formulas (1) to (3). The three-dimensional luminance image forming unit 24 uses the luminance image opacity function set by the opacity setting unit 22 to apply the volume rendering method to the luminance volume data according to the equations (1) to (3), thereby Original luminance image data is formed.

Cout (i) = Cout (i-1) + (1−Aout (i-1)), A (i), C (i), S (i) (1)
Aout (i) = Aout (i-1) + (1−Aout (i-1)) ・ A (i) (2)
A (i) = Opacity [C (i)] (3)

In the above formula,
C (i) is a luminance value of the i-th voxel (attention voxel) on the line of sight.
Cout (i) is a luminance value (output light amount) output from the i-th voxel. For example, when N voxels are arranged on the line of sight, the calculation result Cout (N-1) from the 0th voxel to the (N-1) th voxel is the pixel value to be finally output. Become.
Cout (i-1) is a luminance value (output light amount) output from the (i-1) th voxel, and is a calculation result up to the (i-1) th voxel.
A (i) is the opacity for the i-th voxel on the line of sight, and is expressed as a function of the luminance value C (i). A (i) is, for example, a value between 0.0 and 1.0. The opacity corresponds to the degree of voxel contribution to the three-dimensional luminance image data.
Aout (i) is the accumulated opacity output from the i-th voxel.
Aout (i-1) is the cumulative opacity output from the (i-1) th voxel.
S (i) is a weighting component for shading and is determined from the gradient obtained from the luminance value C (i) of the i-th voxel and the surrounding luminance values. Depending on the positional relationship between the light source and the voxels, for example, a value between 0.0 and 1.0 is adopted as S (i).

  The initial values of Cout (i) and Aout (i) are both 0 (zero). As shown in Equation (2), Aout (i) is integrated and converges to 1.0 each time a ray passes through a voxel. Therefore, when the calculation result Aout (i-1) of the opacity of the voxels up to the (i-1) th is approximately 1.0 (≈1.0), as shown in the equation (1). In addition, the i-th and subsequent luminance values C (i) are not reflected in the three-dimensional luminance image data.

  The displacement calculator 26 calculates the amount of tissue displacement in the subject based on the two received frame data output from the receiver 14. For example, the displacement calculation unit 26 performs one-dimensional or two-dimensional correlation calculation processing on two received frame data adjacent on the time axis, and thereby, for each individual measurement point in each received frame data, A displacement vector indicating the displacement of the tissue is calculated. This displacement vector is a one-dimensional or two-dimensional vector related to the direction and magnitude of the displacement. By this calculation, a distribution of displacement vectors at a plurality of measurement points is obtained. In the calculation of the displacement vector, for example, a block matching method or a phase gradient method is used.

  In the block matching method, each received frame data is divided into a plurality of blocks each consisting of several pixels in the vertical direction and several pixels in the horizontal direction. Then, for each individual block, the block most similar to the block in one received frame data is searched for in the other received frame data. Thereby, the displacement is calculated for each measurement point (block) in each received frame data, and for example, a two-dimensional displacement vector is obtained. Note that a displacement vector at each measurement point may be obtained by referring to search results of a plurality of blocks and performing a process such as predictive encoding, that is, a process of determining a sample value based on a difference.

  In the phase gradient method, wave phase information is obtained from the echo data that makes up each received frame data, the amount of wave movement is calculated from the change in the phase information, and the displacement of each measurement point in each received frame data is calculated. To do. Thereby, for example, a one-dimensional displacement vector in the reception beam direction or a two-dimensional displacement vector in each reception frame data is obtained.

  The elasticity information calculation unit 28 calculates the elasticity value in the subject for each received frame data. For example, the elasticity information calculation unit 28 calculates the elasticity value of the tissue in the subject using the amount of displacement calculated by the displacement calculation unit 26. The elastic value is, for example, strain, elastic modulus, displacement, viscosity, strain ratio, and the like. For example, the elasticity information calculation unit 28 calculates an elasticity value for each measurement point based on a displacement vector at each measurement point. Further, the elasticity information calculation unit 28 calculates an elasticity value for each received frame data.

  When the elasticity value is calculated by the elasticity information calculation unit 28, for example, the probe 10 is pressed against the subject, the tissue in the subject is compressed from the body surface of the subject, and the displacement of the tissue due to the compression is measured. Is done. At this time, for example, a pressure sensor (not shown) detects the pressure between the transmission / reception surface of the probe 10 and the body surface of the subject, and a stress measurement unit (not shown) detects the pressure based on the pressure detected by the pressure sensor. The pressure at each measurement point inside the sample may be measured.

  The elasticity information calculation unit 28 calculates the elastic modulus of the tissue at each measurement point with reference to the stress measured by the stress measurement unit. Strain data is calculated by spatially differentiating the amount of tissue movement, for example, displacement. The elastic modulus data is calculated by dividing the change in stress by the change in strain.

  For example, assuming that the displacement calculated by the displacement calculator 26 is L (x) and the stress measured by the stress measurement unit is P (x) for the position x in each received frame data, the strain ΔS (x) is , L (x) can be calculated by spatial differentiation. For example, the strain can be calculated using an expression “ΔS (x) = ΔL (x) / Δx”. Further, the Young's modulus Ym (x) as the elastic modulus data can be calculated by the equation “Ym (x) = ΔP (x) / ΔS (x)”. For example, the elastic modulus at each measurement point in the received frame data is obtained from this Young's modulus Ym.

  The two-dimensional elastic image forming unit 30 is configured by a digital scan converter having a coordinate conversion function, an interpolation processing function, and the like. The two-dimensional elastic image forming unit 30 forms elastic frame data based on the elastic value obtained from the elastic information calculating unit 28. Elastic frame data is two-dimensional elastic image data. Elastic image data can be formed by a known technique. For example, the two-dimensional elastic image forming unit 30 forms elastic frame data representing an elastic value at each measurement point in the received frame data.

  The elastic volume data forming unit 32 forms elastic volume data representing an elastic value distribution in the three-dimensional space based on the plurality of elastic frame data formed by the two-dimensional elastic image forming unit 30. For example, the elastic volume data forming unit 32 forms elastic volume data by sequentially arranging a plurality of elastic frame data for each beam scanning plane. At this time, the elastic volume data forming unit 32 forms elastic volume data represented by an orthogonal coordinate system by applying coordinate transformation processing, interpolation processing, and the like to a plurality of elastic frame data.

  The opacity setting unit 34 creates an elasticity image opacity function (elasticity image opacity function) for forming 3D elasticity image data, and sets the elasticity image opacity function in the 3D elasticity image forming unit 38. To do. In the opacity function for elastic image, opacity with respect to the elastic value of the elastic volume data is defined.

  The noise determination unit 36 determines whether or not the elasticity value of each voxel included in the elasticity volume data is noise. The noise determination unit 36 may determine whether each elastic frame data included in the elastic volume data is noise. The noise determination unit 36 outputs information indicating the determination result to the opacity setting unit 34. By using a known technique (for example, Japanese Patent No. 4455003), it is possible to determine whether or not the elasticity value of each voxel is noise (useless information), and whether or not each elasticity frame data is noise. Can be determined. For example, it is possible to determine whether or not the elasticity value of the arbitrary voxel corresponds to noise based on a statistical characteristic (for example, a variance value) of the elasticity value of the voxel existing around the arbitrary voxel. For example, the noise determination unit 36 determines whether or not the elasticity value of each voxel included in the elasticity frame data is noise, and the elasticity frame data in which the ratio of the voxels determined to be noise is equal to or greater than a threshold value. It is determined that the noise elasticity frame data. This threshold value may be a value arbitrarily set by the user.

  The three-dimensional elastic image forming unit 38 forms a three-dimensional elastic image by applying a volume rendering method to the elastic volume data. As the rendering, for example, a ray casting method is used. In the ray casting method, the three-dimensional elastic image forming unit 38 sets a plurality of rays (transmission lines) for elastic volume data, and for each ray, the elastic value of each point (voxel) along with the elastic value is determined. The output light amount calculation using the transparency (opacity) is sequentially executed. Thereby, the pixel value corresponding to each ray is calculated, and three-dimensional elastic image data is formed as a set of a plurality of pixel values. The rendering viewpoint and the light source are set to the same conditions in the 3D elastic image forming unit 38 and the 3D luminance image forming unit 24. The elasticity value of each voxel value, the opacity, and the amount of light output from each voxel are expressed by, for example, the following equations (4) to (6). The three-dimensional elastic image forming unit 38 uses the elastic image opacity function set by the opacity setting unit 34 to apply the volume rendering method to the elastic volume data according to the equations (4) to (6), thereby obtaining a cubic. Original elastic image data is formed.

Eout (i) = Eout (i-1) + (1−Aout (i-1)) ・ A (i) ・ E (i) ・ S (i) (4)
Aout (i) = Aout (i-1) + (1−Aout (i-1)) ・ A (i) (5)
A (i) = Opacity [E (i)] (6)

In the above formula,
E (i) is the elasticity value of the i-th voxel (attention voxel) on the line of sight.
Eout (i) is an elastic value (output light amount) output from the i-th voxel. For example, when N voxels are arranged on the line of sight, the calculation result Eout (N−1) from the 0th voxel to the (N−1) th voxel is the pixel value to be finally output. Become.
Eout (i-1) is an elasticity value (output light amount) output from the (i-1) th voxel, and is a calculation result up to the (i-1) th voxel.
A (i) is the opacity for the i-th voxel on the line of sight, and is expressed as a function of the elastic value E (i). A (i) is, for example, a value between 0.0 and 1.0. The opacity corresponds to the degree of contribution of voxels to the three-dimensional elasticity image data.
Aout (i) is the accumulated opacity output from the i-th voxel.
Aout (i-1) is the cumulative opacity output from the (i-1) th voxel.
S (i) is a weighting component for shading, and is determined from the gradient obtained from the elasticity value E (i) of the i-th voxel and its surrounding elasticity values. Depending on the positional relationship between the light source and the voxels, for example, a value between 0.0 and 1.0 is adopted as S (i).

  The initial values of Eout (i) and Aout (i) are both 0 (zero). As shown in equation (5), Aout (i) is integrated and converges to 1.0 each time a ray passes through a voxel. Therefore, when the calculation result Aout (i-1) of the opacity of the voxels up to the (i-1) th is approximately 1.0 (≈1.0), as shown in the equation (4). In addition, the i-th and subsequent elasticity values E (i) are not reflected in the three-dimensional elasticity image data.

  In the present embodiment, volume rendering is executed using the elasticity value E (i). Depending on the elasticity value, the red value (R), the green value (G), and the blue value, which are the three primary colors of light, are used. (B) may be assigned to each voxel. Then, the elastic volume data is separated into three primary color components having hues corresponding to the elastic values, and volume rendering is executed for each component. In this case, the three primary color components of the hue corresponding to the elastic value E (i) are expressed by R (i), G (i), B (i), and E (i) in the equation (4) is R (i ), G (i), and B (i), and the calculation for each component is executed.

  In the present embodiment, the opacity setting unit 34 changes the opacity according to the noise possibility of the elasticity value. For example, the opacity setting unit 34 makes the opacity with respect to the elasticity value of the voxel with possibility of noise smaller than the opacity with respect to the elasticity value of the voxel with no possibility of noise. Specifically, the opacity setting unit 34 obtains the opacity by multiplying the value obtained from the elasticity image opacity function by a standard weighting factor for the elasticity value of the voxel without the possibility of noise, For the elasticity value of a voxel with a possibility of noise, opacity is obtained by multiplying a value obtained from the elasticity image opacity function by a weighting factor smaller than a standard weighting factor. The opacity setting unit 34 may perform noise processing in units of frames or may perform noise processing in units of voxels. In the noise processing in units of frames, the opacity setting unit 34 makes the opacity for each voxel belonging to the noise elastic frame data smaller than the opacity for the voxels not belonging to the noise elastic frame data. In the noise processing in units of voxels, the opacity setting unit 34 makes the opacity for voxels determined to be noise smaller than the opacity for voxels determined not to be noise.

For example, the three-dimensional elastic image forming unit 38 performs volume rendering using the opacity expressed by the following formula (7).
A (i) = Opacity [E (i)] · w (7)

In the above equation (7), w is a weighting factor determined by the presence or absence of noise.
For example, when noise processing is performed on a frame basis,
The voxel weighting factor belonging to the noise elasticity frame data is set to w = 0.05,
The weighting factor of voxels that do not belong to the noise elastic frame data is set to w = 1.0.
w = 1.0 corresponds to a standard weighting factor, and w = 0.05 corresponds to a weighting factor smaller than the standard weighting factor.

Also, when noise processing is performed on a voxel basis,
The weighting factor of the voxel determined to be noise is set to w = 0.05,
The voxel weighting factor determined not to be noise is set to w = 1.0.

  The value of the weighting factor w is an example, and the weighting factor w is not limited to the above value. When noise processing is performed in units of frames, if the voxels belonging to the noise elastic frame data are sufficiently transparent or semi-transparently displayed, the weight coefficient w of the voxels belonging to the noise elastic frame data is 0. A value other than 05 may be used. Similarly, when noise processing is performed in units of voxels, if the voxels determined to be noise are sufficiently transparent or displayed semi-transparently, the weighting factor of the voxel determined to be noise May be a value other than 0.05. If voxels that do not belong to the noise elasticity frame data or voxels that are determined not to be noise are displayed sufficiently opaquely, the weight coefficient of those voxels may be a value other than 1.0. Good.

  The display processing unit 40 performs overlay processing of necessary graphic data on the 3D luminance image data, 3D elasticity image data, B-mode tomographic image data, and 2D elasticity image data, thereby displaying the display image data. Form. For example, the display processing unit 40 composes display image data by synthesizing 3D luminance image data and 3D elasticity image data. The display image data is output to the display unit 42, and an image is displayed in a display form according to the display mode. Further, the display processing unit 40 may display a plurality of images side by side on the display unit 42. For example, the display processing unit 40 may display a two-dimensional elasticity image and a three-dimensional elasticity image in an arbitrary cross section on the display unit 42 side by side.

  The display unit 42 is configured by a display device such as a liquid crystal display. The display unit 42 may be configured by a plurality of display devices.

  The control unit 44 performs operation control of each configuration shown in FIG. An input unit 46 is connected to the control unit 44. As an example, the input unit 46 is configured by an operation panel including an input device such as a trackball or a keyboard. The user can use the input unit 46 to specify measurement conditions and the like.

  In the above-described ultrasonic diagnostic apparatus, the configuration other than the probe 10 can be realized by using hardware resources such as a processor and an electronic circuit, and a device such as a memory can be used as necessary in the realization. Good. The configuration other than the probe 10 may be realized by a computer, for example. That is, all or part of the configuration other than the probe 10 may be realized by cooperation of hardware resources such as a CPU, a memory, and a hard disk included in the computer and software (program) that defines the operation of the CPU and the like. . The program is stored in a storage device (not shown) via a recording medium such as a CD or DVD, or via a communication path such as a network. As another example, the configuration other than the probe 10 may be realized by a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), or the like.

  Hereinafter, processing by the ultrasonic diagnostic apparatus according to the present embodiment will be described in detail.

  FIG. 2 shows a beam scanning surface formed by scanning with an ultrasonic beam. For example, a plurality of elastic frame data 48 is acquired by mechanically swinging the 1D array transducer included in the probe 10 in the direction of the arrow, and elastic volume data is formed by the plurality of elastic frame data 48. Of course, elastic volume data may be acquired by two-dimensionally scanning an ultrasonic beam using a 2D array transducer.

  FIG. 3 shows an example of elastic volume data. For example, a spherical hard tissue 52 is represented at the center of the elastic volume data 50, and a soft tissue 54 is represented above and below the hard tissue 52. A tissue 56 having an intermediate hardness is shown so as to cover the hard tissue 52 and the soft tissue 54.

  FIG. 4 shows an example of a luminance image opacity function. The luminance image opacity function 58 is created by the opacity setting unit 22. In the graph in FIG. 4, the horizontal axis is the luminance value (echo data), and the vertical axis is the opacity (opacity). In the range where the luminance value is less than or equal to the reference value 58a, the opacity increases as the luminance value increases, and in the range where the luminance value is larger than the reference value 58a, the opacity is maintained at a certain maximum value. By applying volume rendering to the luminance volume data using this luminance image opacity function 58, voxels with a large luminance value are displayed opaque, and voxels with a small luminance value are displayed transparently or semi-transparently. The The luminance image opacity function 58 is merely an example, and other opacity functions may be used. For example, a luminance image opacity function created by a user may be used.

  FIG. 5 shows an example of an elasticity image opacity function. The elasticity image opacity function 60 is created by the opacity setting unit 34. In the graph in FIG. 5, the horizontal axis is an elastic value (strain, elastic modulus, etc.), and the vertical axis is opacity. The elasticity value corresponds to the hardness of the tissue. The smaller the elasticity value, the harder the tissue, and the larger the elasticity value, the softer the tissue. In the range where the elasticity value is a certain reference value 60a or less (range where the elasticity value is small and the tissue hardness is hard), the opacity is maintained at a certain maximum value. Thereby, a hard structure | tissue is displayed opaquely. In the range where the elasticity value is between the reference value 60a and the reference value 60b (a value larger than the reference value 60a), the opacity decreases as the elasticity value increases. In a range where the elasticity value is larger than the reference value 60b (a range where the elasticity value is large and the tissue is soft), the opacity is maintained at a certain minimum value (> 0). As a result, the soft tissue becomes transparent or displayed translucently. By applying volume rendering to elastic volume data using the elasticity image opacity function 60, voxels having a small elasticity value (voxels representing a hard tissue) are displayed opaque, and voxels having a large elasticity value (soft tissue). Voxel) is transparent or semi-transparent. However, according to the purpose, the opacity may be set so that the soft tissue is displayed opaque.

  Incidentally, although it depends on the number of voxels in the line-of-sight direction during volume rendering, generally, when the opacity is set to less than 0.1, translucent three-dimensional elastic image data can be formed. However, if translucent three-dimensional elasticity image data can be formed, a value of 0.1 or more may be employed as the opacity for that. Although it depends on the number of voxels in the line-of-sight direction, generally, when the opacity is set to 0.5 or more, opaque three-dimensional elastic image data can be formed. However, if opaque three-dimensional elastic image data can be formed, a value less than 0.5 may be employed as the opacity for that.

  Note that the elasticity image opacity function 60 shown in FIG. 5 is merely an example, and other opacity functions may be used. For example, an elasticity image opacity function created by the user may be used.

  FIG. 6 shows an example of the elasticity image opacity function. The elasticity image opacity function 62 is an opacity function obtained by multiplying the elasticity image opacity function 60 by a weight coefficient w = 0.05. That is, the elasticity image opacity function 60 shown in FIG. 5 is an opacity function when the weight coefficient w is 1.0 in the above equation (7), and the elasticity image opacity function 62 shown in FIG. It can be said that this is an opacity function when the weight coefficient w is 0.05 in 7). That is, the elasticity image opacity function 60 shown in FIG. 5 is an opacity function applied to voxels that do not belong to the noise elasticity frame or that are determined not to be noise. On the other hand, the elasticity image opacity function 62 shown in FIG. 6 is an opacity function applied to a voxel belonging to a noise elasticity frame or a voxel determined to be noise. In the elasticity image opacity function 62, since the opacity is set to be small as a whole, by applying volume rendering to the elasticity volume data using this elasticity image opacity function 62, a portion corresponding to noise is obtained. It becomes possible to make the display transparent or translucent. Note that if the opacity is reduced to 0, the three-dimensional elasticity image may become an unnatural image. Therefore, also in the elasticity image opacity function 62, the minimum value of opacity is a value larger than 0 (zero). Is set to

  FIG. 7 shows the relationship between the elastic value and the hue. When a color is assigned to a voxel according to an elasticity value, for example, a voxel having a small elasticity value (a voxel representing a hard tissue) is assigned a blue value (B) and a voxel having a large elasticity value (a voxel representing a soft tissue). ) Is assigned a red value (R), and a voxel having an intermediate elasticity value is assigned a green value (G). In this case, the elastic volume data is separated into the three primary color components of the hue corresponding to the elastic value, and volume rendering is executed for each component. In the example illustrated in FIG. 7, hues are assigned discretely, but, for example, hues that continuously change from blue to green to red may be assigned from a small elasticity value to a large elasticity value.

  FIG. 8 shows an example of an opacity function for elastic images according to a reference example. In FIG. 8, the horizontal axis is an elastic value (strain, elastic modulus, etc.), and the vertical axis is opacity. In the elasticity image opacity function 64, the opacity is set to 1.0 in the entire range of elasticity values. FIG. 9 shows a three-dimensional elasticity image formed using this elasticity image opacity function 64. The three-dimensional elasticity image 66 is an image formed by applying volume rendering to the elasticity volume data 50 shown in FIG. 3 using the elasticity image opacity function 64. As shown in FIG. 3, a spherical hard tissue 52 is represented at the center of the elastic volume data 50. If the opacity is set appropriately, the hard tissue 52 is represented in the three-dimensional elastic image 66. It should be. However, in the opacity function for elastic image 64, since the opacity is set to 1.0 in the entire range of the elastic value, the opacity is saturated in the soft tissue 54 existing on the near side in the visual line direction. A three-dimensional elastic image 66 in which the internal structure is not represented is formed.

  FIG. 10 shows a three-dimensional elasticity image formed using the elasticity image opacity function 60 shown in FIG. The three-dimensional elasticity image 68 is an image formed by applying volume rendering to the elasticity volume data 50 shown in FIG. 3 using the elasticity image opacity function 60. A hard tissue image 70 is opaquely displayed at the center of the three-dimensional elastic image 68, and a soft tissue image 72 is translucently displayed above and below the hard tissue image 70. The hard tissue image 70 is an image representing the hard tissue 52 represented in the elastic volume data 50, and the soft tissue image 72 is an image representing the soft tissue 54 represented in the elastic volume data 50. As shown in FIG. 5, in the elasticity image opacity function 60, a large opacity is set for a hard tissue (a voxel having a small elastic value), and a small opacity is set for a soft tissue (a voxel having a large elastic value). Has been. Therefore, the opacity is not saturated in the soft tissue 54 existing on the near side in the line-of-sight direction, and the soft tissue 54 is displayed translucently. This makes it possible to form a three-dimensional elastic image 68 showing the internal hard tissue.

  FIG. 11 shows an example of noise elastic frame data. The noise elastic frame data 74 represents a noise portion 78 together with a hard tissue 76. The noise portion 78 is caused by, for example, non-uniform compression. By using a known technique (for example, Japanese Patent No. 4455003), the noise portion 78 can be specified. FIG. 12 shows elastic volume data 80 including the noise elastic frame data 74. In this elastic volume data 80, a hard portion 82 and a noise portion 84 are also represented. When volume rendering is applied to the elastic volume data 80 using the elastic image opacity function 60 shown in FIG. 5, not only the image representing the hard tissue 82 in the formed three-dimensional elastic image, A noise image representing the noise portion 84 is also represented. Therefore, three-dimensional elastic image data with poor visibility of the hard tissue 82 existing inside is formed. For example, it is assumed that a noise image is superimposed on an image representing the hard tissue 82 and the visibility of the hard tissue 82 is deteriorated.

  FIG. 13 shows a three-dimensional elasticity image formed by the processing according to the present embodiment. The three-dimensional elasticity image 86 is obtained by using the elasticity image opacity function defined in the above equation (7), and the elasticity volume data 80 (elastic volume data including the noise elasticity frame data 74) shown in FIG. Is an image formed by applying volume rendering to the image. A hard tissue image 88 is opaquely displayed at the center of the three-dimensional elastic image 86, and a noise image 90 is translucently displayed around the hard tissue image 88.

  For example, when noise processing is performed on a frame basis, the opacity setting unit 34 uses a value obtained by multiplying the opacity obtained from the elasticity image opacity function by the weighting factor w = 1.0 as the noise. The value obtained by multiplying the opacity obtained from the opacity function for elastic image by the weight coefficient w = 0.05 is used as the opacity of the voxel not belonging to the elastic frame data, and belongs to the noise elastic frame data. Adopted as voxel opacity. Then, the three-dimensional elastic image forming unit 38 forms a three-dimensional elastic image 86 by applying volume rendering to the elastic volume data 80 using the opacity. For example, the three-dimensional elastic image forming unit 38 applies the elastic image opacity function 60 (standard opacity function) shown in FIG. 5 to the voxels not belonging to the noise elastic frame data, thereby generating the noise elastic frame data. The elasticity image opacity function 62 (noise opacity function) shown in FIG. 6 is applied to the voxels belonging to. The three-dimensional elastic image forming unit 38 forms a three-dimensional elastic image 86 by applying volume rendering to the elastic volume data 80 using these opacity functions. Since the opacity of the voxels belonging to the noise elastic frame data is suppressed to a low level, the noise image 90 is displayed semi-transparently in the three-dimensional elastic image 86. On the other hand, since a standard opacity function is applied to voxels that do not belong to the noise elasticity frame data, hard tissue is displayed opaquely and soft tissue is displayed translucently. Thus, by suppressing the opacity for the voxels belonging to the noise elastic frame data to a low level, the contribution of the noise elastic frame data to the three-dimensional elastic image 86 is reduced, and the third order in which the visibility of the hard tissue existing inside is improved. The original elastic image 86 can be formed.

  When noise processing is performed in units of voxels, the opacity setting unit 34 multiplies the opacity obtained from the elasticity image opacity function by a weight coefficient w = 1.0, Adopted as the opacity of the voxel determined not to be noise, and the value obtained by multiplying the opacity obtained from the elasticity image opacity function by the weighting factor w = 0.05 is determined to be noise. Adopted as the opacity of the processed voxels. Then, the three-dimensional elastic image forming unit 38 forms a three-dimensional elastic image 86 by applying volume rendering to the elastic volume data 80 using the opacity. For example, the three-dimensional elasticity image forming unit 38 applies the elasticity image opacity function 60 (standard opacity function) shown in FIG. 5 to the voxels determined not to be noise, and is considered to be noise. The elasticity image opacity function 62 (noise opacity function) shown in FIG. 6 is applied to the determined voxel. Thereby, a three-dimensional elastic image 86 is formed. Since the opacity with respect to the voxel determined to be noise is suppressed to a low level, the noise image 90 is displayed semi-transparently in the three-dimensional elastic image 86. On the other hand, since the standard opacity function is applied to voxels determined not to be noise, hard tissue is displayed opaquely and soft tissue is displayed translucently. Thus, by suppressing the opacity for the voxel determined to be noise, the contribution of the noise voxel to the three-dimensional elastic image 86 is reduced, and the visibility of the hard tissue existing inside is improved. The elastic image 86 can be formed.

  As described above, according to the present embodiment, by setting the opacity for the voxels belonging to the noise elastic frame data or the opacity for the voxels determined to be noise, the contribution of the noise elastic frame data is reduced. Or it becomes possible to make the contribution degree of a noise voxel small. This makes it possible to form three-dimensional elastic image data in which noise is not noticeable. In addition, since noise elastic frame data and noise voxels are included in the elastic volume data without being removed, it is possible to form continuous natural three-dimensional elastic image data without data loss. That is, when noise elastic frame data and noise voxels are removed, the removed data is lost, and unnatural three-dimensional elastic image data having no continuity is formed. In the present embodiment, it is possible to avoid data loss by setting the opacity of the noise elastic frame data and noise voxels to a small value without removing them.

(Modification 1)
Modification 1 will be described with reference to FIG. FIG. 14 shows a part of the elastic volume data and the line of sight in volume rendering. This elastic volume data includes voxels 92 that do not belong to the noise elastic frame data and voxels 94 that belong to the noise elastic frame data. Usually, the line of sight 96 in volume rendering and the voxels included in the elastic volume data rarely intersect. Therefore, the elasticity value of the sampling point 98 on the line of sight 96 is obtained by interpolation using the elasticity value of the neighboring voxel group, and volume rendering is performed using the elasticity value of the sampling point 98.

  In the first modification, the opacity setting unit 34 sets the opacity for the sampling point 98 after the interpolation according to the ratio of the voxels belonging to the noise elastic frame data included in the voxel group that is the interpolation source of the sampling point 98. decide. As an example, the elasticity value of the sampling point 98 is obtained by interpolation using the elasticity values of eight voxels existing around the sampling point 98. For example, when it is determined that four of the eight voxels are voxels belonging to the noise elastic frame data, the opacity setting unit 34 sets the weight coefficient w = 0.5 and sets the above formula (7 ) To determine the opacity for the sampling point 98. For example, the elasticity image opacity function 60 shown in FIG. 5 is used. The opacity setting unit 34 obtains an opacity corresponding to the elasticity value of the sampling point 98 from the elasticity image opacity function 60, and is obtained by multiplying the opacity by a weight coefficient w = 0.5. The value is taken as the opacity for the sampling point 98. Also, when it is determined that two of the eight voxels are voxels belonging to the noise elastic frame data, the opacity setting unit 34 sets the weight coefficient w = 0.75 to the above formula (7 ) To determine the opacity for the sampling point 98. When it is determined that 6 of the 8 voxels are voxels belonging to the noise elastic frame data, the opacity setting unit 34 sets the weighting factor w = 0.25 to the above formula (7 ) To determine the opacity for the sampling point 98. Note that the value of the weighting factor w is merely an example, and other values may be used as the weighting factor w. Of course, the user may determine the weighting coefficient w. As described above, when the elasticity value of each sampling point 98 is obtained by interpolation and the opacity for each sampling point 98 is determined, the three-dimensional elasticity image forming unit 38 performs volume rendering for the sampling point 98 as a target. . Thereby, three-dimensional elasticity image data is formed. As the ratio of voxels belonging to the noise elastic frame data is increased, the opacity is set to be smaller, so that it is possible to form three-dimensional elastic image data in which noise is not noticeable.

  As another example, the opacity setting unit 34 sets the opacity for the sampling point 98 after interpolation according to the ratio of the voxels determined to be noise included in the voxel group that is the interpolation source of the sampling point 98. You may decide. Also in this case, as in the above example, the greater the ratio of noise voxels contained in the interpolation source voxel group, the smaller the weighting factor w is set, thereby setting the opacity smaller. As a result, it is possible to form three-dimensional elastic image data in which noise is not noticeable.

(Modification 2)
In the second modification, the noise determination unit 36 determines the noise level (noise likelihood) for each elastic frame data according to the ratio of voxels determined to be noise in each elastic frame data. For example, the noise determination unit 36 divides the noise level into five levels (levels 1 to 5), and gives higher noise level to elastic frame data having a higher proportion of voxels determined to be noise. For example, it is assumed that the noise level 5 is a level indicating a state that seems to be the most noise. The opacity setting unit 34 uses the weighting factor w = 1.0 when the noise level is “1”, and uses the weighting factor w = 0.5 when the noise level is “2”. When “3”, the weighting factor w = 0.2 is used, when the noise level is “4”, the weighting factor w = 0.1 is used, and when the noise level is “5”, the weighting factor w = 0.05 is used. Of course, values other than these may be used as weighting factors. Further, the user may determine the weighting factor. The opacity setting unit 34 determines the opacity for each voxel belonging to each elastic frame data by multiplying the elastic image opacity function 60 shown in FIG. 5 by a weighting factor w corresponding to the noise level. . Then, the three-dimensional elastic image forming unit 38 forms three-dimensional elastic image data by executing volume rendering using the opacity set for each voxel. For voxels belonging to elastic frame data having a higher noise level, the weight coefficient w is set to be smaller, thereby setting the opacity to be smaller. As a result, it is possible to form three-dimensional elastic image data in which noise is not noticeable.

(Modification 3)
Modification 3 will be described with reference to FIG. FIG. 15 shows the elastic frame data 48 and a part of the elastic volume data 100. As shown in FIG. 2, when the 1D array transducer included in the probe 10 is mechanically swung, the obtained plurality of elastic frame data 48 is drawn as shown in FIGS. 2 and 15. Spatial arrangement. On the other hand, in volume rendering, the calculation is simpler when the data is represented in an orthogonal coordinate system. Therefore, in general, by performing coordinate conversion processing, elastic volume data 100 represented by an orthogonal coordinate system is formed from a plurality of elastic frame data 48. At this time, the elasticity value of the point (voxel) 102 in the elasticity volume data 100 is obtained by interpolation processing using the elasticity values of the plurality of points 104 on the plurality of elasticity frame data 48 existing around. Also in this embodiment, the elastic volume data forming unit 32 forms the elastic volume data 100 by executing the coordinate conversion process and the interpolation process.

  In the third modification, the opacity setting unit 34 forms weight coefficient volume data. This weight coefficient volume data corresponds to a three-dimensional weight coefficient table. For example, the opacity setting unit 34 determines the weighting coefficient w for the point (voxel) 102 depending on whether or not the elastic frame data 48 of the interpolation source of the point (voxel) 102 corresponds to the noise elastic frame data. .

  Specifically, when the elastic frame data 48 of the interpolation source of the point (voxel) 102 corresponds to the noise elastic frame data, the opacity setting unit 34 adopts 0.5 as the weighting coefficient w for the point (voxel). To do. When the elastic frame data 48 as the interpolation source of the point (voxel) 102 does not correspond to the noise elastic frame data, the opacity setting unit 34 adopts 1.0 as the weighting coefficient for the point (voxel) 102. In this way, the opacity setting unit 34 determines the weighting coefficient w of each point (voxel) 102 included in the elastic volume data 100. Thereby, weight coefficient volume data (three-dimensional weight coefficient table) including the weight coefficient w is created.

  Then, the opacity setting unit 34 determines the opacity for each point (voxel) 102 according to the equation (7) and the weight coefficient volume data. The opacity setting unit 34 obtains the opacity corresponding to the elasticity value (value obtained by interpolation) of the point (voxel) 102 from the elasticity image opacity function 60 shown in FIG. A value obtained by multiplying the weight coefficient w by is adopted as the opacity for the point (voxel) 102. When the opacity for each point (voxel) 102 is determined, the three-dimensional elastic image forming unit 38 performs volume rendering for the point (voxel) 102. Thereby, three-dimensional elasticity image data is formed. When the interpolation source elastic frame data corresponds to the noise elastic frame data, the weight coefficient w is set to be small and the opacity is reduced. This makes it possible to form three-dimensional elastic image data in which noise is not noticeable.

  Note that Modifications 1 and 3 may be combined. For example, the weighting factor w for the sampling point 98 on the line of sight 96 may be obtained by interpolation from the weighting factors w of eight neighboring voxels in the weighting factor volume data.

  10 probe, 12 transmitting unit, 14 receiving unit, 18 tomographic image forming unit, 20 luminance volume data forming unit, 22, 34 opacity setting unit, 24 three-dimensional luminance image forming unit, 26 displacement calculating unit, 28 elasticity information calculating unit , 30 Two-dimensional elastic image forming unit, 32 Elastic volume data forming unit, 36 Noise determining unit, 38 Three-dimensional elastic image forming unit, 40 Display processing unit, 42 Display unit, 44 Control unit, 46 Input unit.

Claims (5)

Elastic volume data acquisition means for acquiring elastic volume data representing an elastic value distribution in the three-dimensional space by transmitting and receiving ultrasonic waves to and from the three-dimensional space in the subject;
A plurality of rays are set for the elastic volume data, and an output light amount calculation using an elastic value and opacity based on the elastic volume data is sequentially executed for each ray, thereby corresponding to each ray. 3D elastic image forming means for calculating a pixel value and thereby forming a 3D elastic image;
In each output light amount calculation, an opacity setting means for setting the opacity according to the elasticity value used in the output light amount calculation and the noise possibility of the elasticity value;
An ultrasonic diagnostic apparatus comprising: The ultrasonic diagnostic apparatus according to claim 1,
The opacity setting means makes the opacity for an elastic value with a possibility of noise smaller than the opacity with respect to an elastic value without a possibility of noise.
An ultrasonic diagnostic apparatus. The ultrasonic diagnostic apparatus according to claim 2,
The opacity setting means sets the opacity by multiplying a value obtained from an opacity function that defines the relationship between the elasticity value and the opacity by a standard weighting factor for the elasticity value having no possibility of noise. For the elastic value having a possibility of noise, the opacity is obtained by multiplying the value obtained from the opacity function by a weighting factor smaller than the standard weighting factor.
An ultrasonic diagnostic apparatus. The ultrasonic diagnostic apparatus according to any one of claims 1 to 3,
The elastic volume data acquisition means acquires a plurality of elastic frame data by transmitting and receiving ultrasonic waves to a subject, and forms the elastic volume data based on the plurality of elastic frame data,
The noise possibility of the elasticity value is determined by whether or not the elasticity value belongs to noise elasticity frame data including noise in the plurality of elasticity frame data.
An ultrasonic diagnostic apparatus. Computer
Elastic volume data acquisition means for acquiring elastic volume data representing an elastic value distribution in the three-dimensional space formed by transmitting and receiving ultrasonic waves to and from the three-dimensional space in the subject;
A plurality of rays are set for the elastic volume data, and an output light amount calculation using an elastic value and opacity based on the elastic volume data is sequentially executed for each ray, thereby corresponding to each ray. 3D elastic image forming means for calculating a pixel value and thereby forming a 3D elastic image;
In each output light amount calculation, an opacity setting means for setting the opacity according to the elasticity value used in the output light amount calculation and the noise possibility of the elasticity value;
A program characterized by functioning as