JP2016214868A - Ultrasonic diagnostic apparatus and image diagnostic apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an ultrasonic diagnostic apparatus capable of accurately extracting a shadow in an ultrasonic image, and an image diagnostic apparatus.SOLUTION: An ultrasonic diagnostic apparatus has a control function and an image generation function. The control function causes an ultrasonic probe to perform ultrasonic scanning for a subject. The image generation function generates a shadow image by assigning at least one of color tone, chroma, and brightness according to the feature of an acoustic shadow that appears as a result of the ultrasonic scanning.SELECTED DRAWING: Figure 1

Description

  Embodiments described herein relate generally to an ultrasonic diagnostic apparatus and an image diagnostic apparatus.

  Conventionally, in an ultrasonic image, an acoustic artifact peculiar to ultrasonic waves may occur. For example, since ultrasonic waves are strongly reflected by a hard tissue, the ultrasonic waves reflected from a deeper position than the hard tissue are weakened, and an acoustic shadow (hereinafter referred to as shadow) that appears dark on the image may occur. Such shadows may occur not only in hard tissues such as bones, but also in tissues that are locally cured by diseases such as diffuse liver disease. In such a case, for example, a comb-like shadow may be shown on the image.

JP 2010-207492 A

  The problem to be solved by the present invention is to provide an ultrasonic diagnostic apparatus and an image diagnostic apparatus that can accurately extract a shadow from an ultrasonic image.

  The ultrasonic diagnostic apparatus according to the embodiment includes a control unit and a processing unit. The control unit causes the ultrasonic probe to execute ultrasonic scanning on the subject. The processing unit generates a shadow image by assigning at least one of hue, saturation, and brightness according to the characteristics of the acoustic shadow that appears in the result of the ultrasonic scanning.

FIG. 1 is a block diagram illustrating a configuration example of the ultrasonic diagnostic apparatus according to the first embodiment. FIG. 2 is a diagram illustrating an example of an ultrasound image including a shadow according to the first embodiment. FIG. 3A is a diagram for explaining a processing target of the calculation function according to the first embodiment. FIG. 3B is a diagram for explaining a processing target of the calculation function according to the first embodiment. FIG. 4 is a diagram for explaining an example of preprocessing according to the first embodiment. FIG. 5A is a diagram for explaining an example of threshold processing by the calculation function according to the first embodiment. FIG. 5B is a diagram for explaining an example of threshold processing by the calculation function according to the first embodiment. FIG. 5C is a diagram for explaining an example of threshold processing by the calculation function according to the first embodiment. FIG. 6 is a diagram illustrating an example of a superimposed image according to the first embodiment. FIG. 7 is a diagram illustrating an example of a shadow image according to the first embodiment. FIG. 8 is a diagram illustrating an example of a superimposed image according to the first embodiment. FIG. 9 is a diagram for explaining an example of a shadow pattern according to the first embodiment. FIG. 10 is a diagram for explaining an example of shadow pattern classification according to the first embodiment. FIG. 11 is a diagram illustrating an example of a color map of shadow characteristics according to the first embodiment. FIG. 12 is a diagram illustrating an example of a superimposed image according to the first embodiment. FIG. 13A is a diagram for describing an example of calculation of a shadow ratio according to the first embodiment. FIG. 13B is a diagram for describing an example of calculation of a shadow ratio according to the first embodiment. FIG. 14 is a flowchart for explaining a processing example of the ultrasonic diagnostic apparatus according to the first embodiment. FIG. 15A is a diagram schematically illustrating an example of preprocessing according to the second embodiment. FIG. 15B is a diagram schematically illustrating an example of preprocessing according to the second embodiment. FIG. 16 is a diagram for explaining an example of threshold setting according to the second embodiment.

  Hereinafter, embodiments of an ultrasonic diagnostic apparatus and an image processing apparatus will be described in detail with reference to the accompanying drawings. In the following description, common constituent elements are given common reference numerals, and redundant description is omitted.

(First embodiment)
First, the configuration of the ultrasonic diagnostic apparatus according to the first embodiment will be described. FIG. 1 is a block diagram illustrating a configuration example of the ultrasonic diagnostic apparatus according to the first embodiment. As illustrated in FIG. 1, the ultrasonic diagnostic apparatus according to the present embodiment includes an ultrasonic probe 1, a display 2, an input unit 3, and an apparatus main body 10.

  The ultrasonic probe 1 includes, for example, a plurality of piezoelectric vibrators, and the plurality of piezoelectric vibrators generate ultrasonic waves based on a drive signal supplied from a transmission / reception circuit 11 included in the apparatus main body 10 described later. The ultrasonic probe 1 receives a reflected wave from the subject P and converts it into an electrical signal. The ultrasonic probe 1 includes a matching layer provided in the piezoelectric vibrator, a backing material that prevents propagation of ultrasonic waves from the piezoelectric vibrator to the rear, and the like. The ultrasonic probe 1 is detachably connected to the apparatus main body 10.

  When ultrasonic waves are transmitted from the ultrasonic probe 1 to the subject P, the transmitted ultrasonic waves are reflected one after another at the discontinuous surface of the acoustic impedance in the body tissue of the subject P, and the ultrasonic probe is used as a reflected wave signal. 1 is received by a plurality of piezoelectric vibrators. The amplitude of the received reflected wave signal depends on the difference in acoustic impedance at the discontinuous surface where the ultrasonic wave is reflected. Note that the reflected wave signal when the transmitted ultrasonic pulse is reflected by the moving blood flow or the surface of the heart wall depends on the velocity component of the moving object in the ultrasonic transmission direction due to the Doppler effect. And undergoes a frequency shift.

  Here, the ultrasonic probe 1 according to the first embodiment may be an ultrasonic probe capable of scanning the subject P in two dimensions with ultrasonic waves and scanning the subject P in three dimensions. Good. Specifically, the ultrasonic probe 1 according to the first embodiment scans the subject P two-dimensionally with a plurality of piezoelectric vibrators arranged in a row, and moves the plurality of piezoelectric vibrators at a predetermined angle. By oscillating at a (oscillation angle), a mechanical 4D probe that scans the subject P in three dimensions and a plurality of piezoelectric vibrators are arranged in a matrix, so that the subject P is ultrasonicated in three dimensions. It may be a 2D probe capable of scanning. Note that the 2D probe can also scan the subject P in two dimensions by focusing and transmitting ultrasonic waves. Here, the ultrasonic scanning according to the present embodiment indicates that data for one frame is collected by at least one ultrasonic transmission / reception.

  The input unit 3 includes a mouse, a keyboard, a button, a panel switch, a touch command screen, a foot switch, a trackball, a joystick, and the like, receives various setting requests from an operator of the ultrasonic diagnostic apparatus, The various setting requests received are transferred. For example, the input unit 3 accepts a request for setting a region of interest (ROI) for an ultrasound image.

  The display 2 displays a GUI (Graphical User Interface) for an operator of the ultrasonic diagnostic apparatus to input various setting requests using the input unit 3, and displays various image data generated in the apparatus main body 10. To do.

  The apparatus main body 10 is an apparatus that generates ultrasonic image data based on a reflected wave signal received by the ultrasonic probe 1. For example, the apparatus main body 10 according to the first embodiment is an apparatus that can generate two-dimensional ultrasonic image data based on two-dimensional reflected wave data received by the ultrasonic probe 1. For example, the apparatus main body 10 according to the first embodiment is an apparatus that can generate three-dimensional ultrasonic image data based on three-dimensional reflected wave data received by the ultrasonic probe 1.

  As shown in FIG. 1, the apparatus main body 10 includes a transmission / reception circuit 11, a B-mode processing circuit 12, a Doppler processing circuit 13, an image memory 14, a processing circuit 15, and an internal storage circuit 16. In the ultrasonic diagnostic apparatus shown in FIG. 1, each processing function is stored in the internal storage circuit 16 in the form of a program that can be executed by a computer. The transmission / reception circuit 11, the B-mode processing circuit 12, the Doppler processing circuit 13, and the processing circuit 15 are processors that realize a function corresponding to each program by reading and executing the program from the internal storage circuit 16. In other words, each circuit that has read each program has a function corresponding to the read program.

  The term “processor” used in the above description is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an application specific integrated circuit (ASIC), a programmable logic device ( For example, it means circuits such as a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA). The function is realized by reading and executing the program stored in the memory circuit, but instead of storing the program in the memory circuit, the program may be directly incorporated in the circuit of the processor. In this case, the processor realizes the function by reading and executing the program incorporated in the circuit, but each processor of this embodiment is not limited to being configured as a single circuit for each processor, Independent circuits may be combined to form a single processor that implements its function.

  The transmission / reception circuit 11 includes a pulse generator, a transmission delay circuit, a pulser, and the like, and supplies a drive signal to the ultrasonic probe 1. The pulse generator repeatedly generates rate pulses for forming transmission ultrasonic waves at a predetermined rate frequency. Further, the transmission delay circuit generates a delay time for each piezoelectric vibrator necessary for focusing the ultrasonic wave generated from the ultrasonic probe 1 into a beam and determining transmission directivity. Give for each rate pulse. The pulser applies a drive signal (drive pulse) to the ultrasonic probe 1 at a timing based on the rate pulse. That is, the transmission delay unit arbitrarily adjusts the transmission direction of the ultrasonic wave transmitted from the piezoelectric vibrator surface by changing the delay time given to each rate pulse.

  The transmission / reception circuit 11 has a function capable of instantaneously changing a transmission frequency, a transmission drive voltage, and the like in order to execute a predetermined scan sequence based on an instruction from the processing circuit 15 described later. In particular, the change of the transmission drive voltage is realized by a linear amplifier type transmission circuit capable of instantaneously switching the value or a mechanism for electrically switching a plurality of power supply units.

  The transmission / reception circuit 11 includes a preamplifier, an A / D (Analog / Digital) converter, a reception delay unit, an adder, and the like, and performs various processing on the reflected wave signal received by the ultrasonic probe 1 to reflect Generate wave data. The preamplifier amplifies the reflected wave signal for each channel. The A / D converter A / D converts the amplified reflected wave signal. The reception delay circuit provides a delay time necessary for determining the reception directivity. The adder performs an addition process of the reflected wave signal processed by the reception delay circuit to generate reflected wave data. By the addition processing of the adder, the reflection component from the direction corresponding to the reception directivity of the reflected wave signal is emphasized, and a comprehensive beam for ultrasonic transmission / reception is formed by the reception directivity and the transmission directivity.

  The transmission / reception circuit 11 according to the first embodiment transmits a two-dimensional ultrasonic beam from the ultrasonic probe 1 in order to two-dimensionally scan the subject P. The transmitter / receiver circuit 11 according to the first embodiment generates two-dimensional reflected wave data from the two-dimensional reflected wave signal received by the ultrasonic probe 1. In addition, the transmission / reception circuit 11 according to the first embodiment transmits a three-dimensional ultrasonic beam from the ultrasonic probe 1 in order to three-dimensionally scan the subject P. The transmission / reception circuit 11 according to the first embodiment generates three-dimensional reflected wave data from the three-dimensional reflected wave signal received by the ultrasonic probe 1.

  The form of the output signal from the transmission / reception circuit 11 is various, for example, when it is a signal including phase information called an RF (Radio Frequency) signal or when it is amplitude information after the envelope detection processing. Can be selected.

  The B-mode processing circuit 12 receives the reflected wave data from the transmission / reception circuit 11, performs logarithmic amplification, envelope detection processing, etc., and generates data (B-mode data) in which the signal intensity is expressed by brightness. .

  The Doppler processing circuit 13 performs frequency analysis on velocity information from the reflected wave data received from the transmission / reception circuit 11, extracts blood flow, tissue, and contrast agent echo components due to the Doppler effect, and extracts moving body information such as velocity, dispersion, and power. Data extracted for multiple points (Doppler data) is generated. The moving body according to the present embodiment is a fluid such as blood flowing in a blood vessel or lymph fluid flowing in a lymph vessel.

  Note that the B-mode processing circuit 12 and the Doppler processing circuit 13 according to the first embodiment can process both two-dimensional reflected wave data and three-dimensional reflected wave data. That is, the B-mode processing circuit 12 generates two-dimensional B-mode data from the two-dimensional reflected wave data, and generates three-dimensional B-mode data from the three-dimensional reflected wave data. The Doppler processing circuit 13 generates two-dimensional Doppler data from the two-dimensional reflected wave data, and generates three-dimensional Doppler data from the three-dimensional reflected wave data. The three-dimensional B-mode data is data to which a luminance value corresponding to the reflection intensity of the reflection source located at each of a plurality of points (sample points) set on each scanning line in the three-dimensional scanning range is assigned. In the three-dimensional Doppler data, a luminance value corresponding to the value of blood flow information (speed, dispersion, power) is assigned to each of a plurality of points (sample points) set on each scanning line in the three-dimensional scanning range. Data.

  The image memory 14 is a memory for storing display image data generated by a processing circuit 15 described later. The image memory 14 can also store data generated by the B-mode processing circuit 12 and the Doppler processing circuit 13. The B-mode data and Doppler data stored in the image memory 14 can be called by an operator after diagnosis, for example, and become ultrasonic image data for display via the processing circuit 15.

  The internal storage circuit 16 stores various data such as a control program for performing ultrasonic transmission / reception, image processing and display processing, diagnostic information (for example, patient ID, doctor's findings, etc.), diagnostic protocol, and various body marks. To do. The internal storage circuit 16 is also used for storing image data stored in the image memory 14 as necessary. The data stored in the internal storage circuit 16 can be transferred to an external device via an interface (not shown).

  The processing circuit 15 controls the entire processing of the ultrasonic diagnostic apparatus. Specifically, the processing circuit 15 performs various processes by reading out and executing programs corresponding to the image generation function 151, the control function 152, and the calculation function 153 shown in FIG. 1 from the internal storage circuit 16. For example, the processing circuit 15 is based on various setting requests input from the operator via the input unit 3, various control programs and various data read from the internal storage circuit 16, and the transmission / reception circuit 11 and the B-mode processing circuit 12. The process of the Doppler processing circuit 13 is controlled. Further, the processing circuit 15 controls the display 2 to display ultrasonic image data for display stored in the image memory 14 or the internal storage unit 17. Further, the processing circuit 15 controls the display 2 to display the processing result of the image generation function 151. For example, the processing circuit 15 reads and executes a program corresponding to the control function 152, thereby controlling the entire apparatus and controlling the above-described treatment. The image generation function 151 and the calculation function 153 are also referred to as a processing unit. The control function 152 is also called a control unit.

  The image generation function 151 generates ultrasonic image data from the data generated by the B mode processing circuit 12 and the Doppler processing circuit 13. That is, the image generation function 151 generates B-mode image data in which the intensity of the reflected wave is expressed by luminance from the two-dimensional B-mode data generated by the B-mode processing circuit 12. The B-mode image data is data in which the tissue shape in the ultrasonically scanned region is depicted. The image generation function 151 generates Doppler image data representing moving body information from the two-dimensional Doppler data generated by the Doppler processing circuit 13. The Doppler image data is velocity image data, distributed image data, power image data, or image data obtained by combining these. The Doppler image data is data indicating fluid information regarding the fluid flowing in the ultrasonically scanned region.

  Here, the image generation function 151 generally converts (scan converts) a scanning line signal sequence of ultrasonic scanning into a scanning line signal sequence of a video format typified by a television or the like, and displays ultrasonic waves for display. Generate image data. Specifically, the image generation function 151 generates ultrasonic image data for display by performing coordinate conversion according to the ultrasonic scanning mode of the ultrasonic probe 1. In addition to the scan conversion, the image generation function 151 includes, for example, image processing (smoothing processing) for regenerating an average luminance image using a plurality of image frames after scan conversion, Image processing (edge enhancement processing) using a differential filter is performed in the image. Further, the image generation function 151 synthesizes character information, scales, body marks, and the like of various parameters with the ultrasonic image data.

  That is, the B-mode data and the Doppler data are ultrasonic image data before the scan conversion process, and the data generated by the image generation function 151 is the display ultrasonic image data after the scan conversion process. The B-mode data and the Doppler data are also called raw data (Raw Data).

  Furthermore, the image generation function 151 generates three-dimensional B-mode image data by performing coordinate conversion on the three-dimensional B-mode data generated by the B-mode processing circuit 12. The image generation function 151 generates three-dimensional Doppler image data by performing coordinate conversion on the three-dimensional Doppler data generated by the Doppler processing circuit 13. The three-dimensional B-mode data and the three-dimensional Doppler data are volume data before the scan conversion process. That is, the image generation function 151 generates “three-dimensional B-mode image data or three-dimensional Doppler image data” as “volume data that is three-dimensional ultrasound image data”.

  Further, the image generation function 151 performs a rendering process on the volume data in order to generate various two-dimensional image data for displaying the volume data on the display 2. The rendering process performed by the image generation function 151 includes a process of generating MPR image data from volume data by performing a cross-section reconstruction method (MPR: Multi Planer Reconstruction). The rendering processing performed by the image generation function 151 includes processing for performing “Curved MPR” on volume data and processing for performing “Maximum Intensity Projection” on volume data. The rendering processing performed by the image generation function 151 includes volume rendering (VR) processing that generates two-dimensional image data reflecting three-dimensional information.

  Further, the image generation function 151 generates various information based on the calculation result by the calculation function 153 described later. Specifically, the image generation function 151 generates a shadow image based on the calculation result and information indicating the measurement result regarding the shadow. The shadow image and information indicating the measurement result will be described later in detail.

  The control function 152 executes various controls in the entire apparatus described above. Further, the control function 152 causes the display 2 to display the shadow image generated by the image generation function 151 and information indicating the measurement result. The calculation function 153 generates shadow information based on the result of ultrasonic scanning. The processing by the calculation function 153 will be described later in detail.

  The overall configuration of the ultrasonic diagnostic apparatus according to the first embodiment has been described above. Under such a configuration, the ultrasonic diagnostic apparatus according to the first embodiment makes it possible to accurately extract a shadow from an ultrasonic image. As described above, in an ultrasonic image, for example, there may be an acoustic shadow (shadow) that is darkly shown at a position deeper than a diseased part. For example, when tissue properties change due to cirrhosis or fatty liver, shadows may occur. Therefore, if the shadow on the ultrasonic image can be extracted with high accuracy, the diagnostic ability based on the ultrasonic image can be improved.

  FIG. 2 is a diagram illustrating an example of an ultrasound image according to the first embodiment. In FIG. 2, an ultrasound image of the liver is shown. For example, as shown in FIG. 2, in an ultrasound image of the liver, there may be a comb-like shadow in which streaks are blackened from the upper side to the lower side of the image. If, for example, a shadow can be extracted quantitatively from such an ultrasonic image, it is expected that it is possible to diagnose what kind of disease it has. Therefore, in the ultrasonic diagnostic apparatus according to the first embodiment, shadows in an ultrasonic image can be accurately extracted by processing by the processing circuit 15 described in detail below.

  The control function 152 shown in FIG. 1 causes the ultrasonic probe 1 to perform ultrasonic scanning on the inside of the subject. The calculation function 153 shown in FIG. 1 is information on the acoustic shadow that appears in the ultrasonic scanning result based on the analysis result of a plurality of depths by analyzing the ultrasonic scanning result for each depth. Generate shadow information. Specifically, the calculation function 153 analyzes a signal collected by ultrasonic scanning for each depth and extracts a shadow included in the ultrasonic image. That is, the calculation function 153 analyzes the signal in the azimuth direction (lateral direction) and extracts a shadow.

  3A and 3B are diagrams for explaining the processing target of the calculation function 153 according to the first embodiment. In FIG. 3A, the scanning line in an ultrasonic image is shown. Further, in FIG. 3B, a graph is shown in which the vertical axis indicates the signal value and the horizontal axis indicates the azimuth direction signal (scanning line). For example, as illustrated in FIG. 3A, the calculation function 153 uses the signal values “s1” to “s250” at the depth “d1” in each of the scanning lines “1” to “250” when ultrasonic scanning is performed. Is analyzed. For example, the calculation function 153 extracts the signal values “s1” to “s250” at the depth “d1” and calculates the displacement of the signal value in the azimuth direction for each depth. For example, as shown in FIG. 3B, the calculation function 153 extracts a signal value of depth “d1” for each scanning line, generates a graph with the horizontal axis as the scanning line and the vertical axis as the signal value, Shadows are extracted based on the generated graph. Although only the depth “d1” is shown in FIGS. 3A and 3B, in reality, the calculation function 153 generates a signal in the azimuth direction for each depth corresponding to all sample points on the scanning line. To analyze. For example, the calculation function 153 performs analysis at a position shallower and deeper than the depth “d1” illustrated in FIG. 3A.

  Here, any signal can be used as the signal value handled by the calculation function 153. For example, as the signal value handled by the calculation function 153, reflected wave data subjected to addition processing by an adder in the transmission / reception circuit 11, amplitude data after envelope detection processing, luminance value, or the like is used. Hereinafter, a case where amplitude data or a luminance value is used will be described as an example.

  As described above, when the signal value for each depth is extracted, the calculation function 153 generates shadow information by analyzing the extracted signal value. For example, the calculation function 153 includes, as at least a part of the analysis performed for each depth, a comparison between a signal value of each signal at the same depth obtained by ultrasonic scanning and a predetermined threshold value, and the ultrasonic scanning. Shadow information is generated by performing at least one of the comparison between the difference between the signal value of each signal obtained at the same depth and the reference value and a predetermined threshold value. Here, the reference value described above is, for example, a signal value of a signal adjacent to each signal at the same depth.

  As an example, the calculation function 153 may calculate a difference between a signal that is less than a predetermined threshold in signals at each depth (each signal at the same depth) collected by ultrasonic scanning, and an adjacent signal at each depth. Shadow information is generated by extracting at least one of the signals exceeding a predetermined threshold. For example, the calculation function 153 extracts, as a shadow, the position of the scanning line whose signal value falls below a predetermined threshold in the signal value graph shown in FIG. 3B. Further, the calculation function 153 extracts, as a shadow, the position of the scanning line in which the difference between adjacent signals exceeds a predetermined threshold in the signal value graph shown in FIG. 3B. In addition, when comparing the difference between signals with a predetermined threshold value, not only between adjacent signals but also a difference between non-adjacent signals may be compared with a predetermined threshold value. For example, the difference between a signal indicating a maximum value and a signal indicating a minimum value among a plurality of signals within a predetermined range at the same depth may be compared with a predetermined threshold value. Here, the calculation function 153 can use the above-described two shadow extraction methods individually or in combination. In FIG. 3B, since the graph is schematically shown, a large change in the signal value is not seen, but in the actual graph including the shadow, the signal value changes greatly.

  The calculation function 153 executes the above-described threshold value processing for each depth. That is, the calculation function 153 extracts a shadow portion in the ultrasonic image for each depth. Here, in the ultrasonic image, since the intensity of the signal value for each depth differs depending on the gain, focus, and depth attenuation of the image, when the signal value is used as it is, a threshold value is set for each depth. Therefore, in order to remove Gain, Focus, and deep attenuation, the calculation function 153 can perform preprocessing for normalizing the signal value before performing the processing based on the threshold described above.

  FIG. 4 is a diagram for explaining an example of preprocessing according to the first embodiment. Here, in FIG. 4, the vertical axis shows the average value of the signals in the lateral direction, and the horizontal axis shows the depth. That is, FIG. 4 shows a graph obtained by calculating an average value for each depth of signal values extracted in the azimuth direction. As shown in FIG. 4A, the average value of the signal value for each depth is, for example, the average value of the signal value at the focused depth increases, and the average value increases as the depth increases. Get smaller. Therefore, when such a signal value is used as it is, an appropriate threshold value is set for each depth.

  Therefore, the calculation function 153 calculates an average value of signal values of a plurality of signals at the same depth obtained by ultrasonic scanning as at least a part of the analysis executed for each depth, and calculates a plurality of values for each depth. The shadow information is generated by calculating the difference between the signal value and the average value of each signal. In other words, the calculation function 153 calculates the average value of the signal for each depth, and generates shadow information using a value obtained by subtracting the average value of the corresponding depth from the value of the signal for each depth. An example will be described with reference to FIG. 3A. The calculation function 153 calculates the average value of the signal values “s1” to “s250” at the depth “d1” and calculates the average value from the signal values “s1” to “s250”. A value obtained by subtracting the average values is calculated. The calculation function 153 executes the above-described processing for all depths. That is, the calculation function 153 calculates a value obtained by subtracting the average value of the corresponding depth from the signal value for each depth for all depths. As a result, the value of the signal collected by the ultrasonic scanning is normalized, and the average value of the signal becomes “0” as shown in FIG. 4B, and one threshold value is used regardless of the depth. Processing can be performed.

  When the preprocessing is performed as described above, the calculation function 153 performs threshold processing using the signal value after the preprocessing, and extracts a shadow portion in the ultrasonic image. Hereinafter, an example of threshold processing will be described with reference to FIGS. 5A to 5C. 5A to 5C are diagrams for explaining an example of threshold processing by the calculation function 153 according to the first embodiment. Here, in FIG. 5A, the graph of the signal value after the pre-processing in the pixel of the same depth is shown. 5B and 5C show part of the graph.

  For example, as shown in FIG. 5A, the calculation function 153 extracts a signal that is less than a predetermined threshold in a signal at each depth, and extracts a signal in which a difference between the signals exceeds a predetermined threshold. The “Dip & Peak method” is executed. In the “threshold method”, for example, as shown in FIG. 5A, a threshold value is set for a pre-processed signal value, and a signal whose pre-processed signal value falls below the threshold value is extracted as a shadow. That is, the calculation function 153 extracts, as a shadow portion, a pixel in which a pre-processed signal value is below a threshold value in pixels having the same depth.

  For example, as illustrated in FIG. 5B, the calculation function 153 extracts, as a shadow, a pixel (sample point) corresponding to a portion where the signal value is lower than the threshold value a in the pre-processed signal value graph. Here, as illustrated in FIG. 5B, the calculation function 153 includes, as shadow characteristics, an “amplitude difference” that is a difference between the threshold value and “Dip” of the signal value, and a “width” of the portion extracted as the shadow. calculate.

  Further, as the “Dip & Peak method”, for example, as shown in FIG. 5A, a signal in a portion where the difference between “Peak” and “Dip” in the graph exceeds a predetermined threshold is extracted as a shadow. In other words, the calculation function 153 extracts, as a shadow portion, a portion of a pixel having the same depth and a portion having a large degree of unevenness in the pre-processed signal value. Here, the portion where the shadow is generated does not necessarily have a low baseline, and may not be extracted by a simple threshold. For example, in the position shown as “not visible” in FIG. 5A, the “Dip” portion of the signal value is higher than the threshold value in the “threshold method”, but is actually a portion where shadowing occurs. . The “Dip & Peak method” can extract such a shadow. Note that “Peak” and “Dip” in the graph may be adjacent to each other or may not be adjacent to each other. That is, two adjacent signals may be “Peak” and “Dip”, respectively, and two non-adjacent signals may be “Peak” and “Dip”, respectively (corresponding to “Peak” and “Dip”) In some cases, another signal is included between signals to be transmitted. The calculation function 153 extracts a shadow by comparing a difference between signal values corresponding to “Peak” and “Dip” in a pixel (signal) having the same depth with a predetermined threshold value.

  For example, as shown in FIG. 5C, the calculation function 153 calculates an “amplitude difference” that is a difference between “Peak” and “Dip”, and shadows a portion where the calculated “amplitude difference” exceeds a predetermined threshold value. Extract as Here, for example, as shown in FIG. 5C, the calculation function 153 calculates the half value of the “amplitude difference” between “Dip” extracted as a shadow and “Peak” on both sides, and calculates the calculated half value. Pixels (sample points) corresponding to portions between the positions are extracted as shadows, and the “width” of the portion extracted as shadows is calculated.

  As described above, the calculation function 153 uses the “threshold method” or the “Dip & Peak method” to extract a shadow portion for each depth, and uses the shadow “amplitude difference” and “ Width "is calculated. The shadow may be extracted by one of the above-described “threshold method” and “Dip & Peak method”, but the shadow is extracted by using both “threshold method” and “Dip & Peak method”. It may be. In such a case, for example, the calculation function 153 extracts, as a shadow, a portion of the signal value that is less than the threshold of the “threshold method” among the portions extracted as the shadow by the “Dip & Peak method”. The shadow extraction process described above may be performed on the entire ultrasound image, but may be performed on a predetermined area. In such a case, for example, the input unit 3 accepts the setting of the ROI, and the shadow in the ROI accepted by the processing circuit 15 is extracted.

  In the ultrasonic diagnostic apparatus according to the first embodiment, various information can be provided using the extracted shadow information. For example, the image generation function 151 generates a shadow image indicating at least one of the position and the feature of the shadow based on the shadow information. For example, the image generation function 151 generates a superimposed image in which a shadow image is superimposed on a morphological image based on the result of ultrasonic scanning. FIG. 6 is a diagram illustrating an example of a superimposed image according to the first embodiment. FIG. 6 shows a superimposed image obtained by superimposing a shadow image indicating a shadow position on a B-mode image before scan conversion in which the vertical direction is depth and the horizontal direction is a scanning line.

  For example, when the shadow area (position) in the ultrasonic image is extracted by the calculation function 153, the image generation function 151 generates a superimposed image indicating the shadow position on the B-mode image as shown in FIG. To do. Thereby, the observer can grasp | ascertain the position of the shadow in an ultrasonic image at a glance.

  The image generation function 151 can also generate a shadow image by assigning at least one of hue, saturation, and lightness according to the characteristics of the shadow. FIG. 7 is a diagram illustrating an example of a shadow image according to the first embodiment. Here, FIG. 7 shows a shadow image using “width” as a feature of the shadow. For example, as illustrated in FIG. 7, the image generation function 151 assigns a color to the shadow “width: 1 to 10”, and generates a shadow image that is colored according to the shadow “width”. In FIG. 7, the case where “width” is used as a shadow feature is taken as an example, but the embodiment is not limited to this, and for example, when “amplitude difference” is used, or “width” is used. And “amplitude difference” may be used.

  The image generation function 151 can also generate a superimposed image in which a shadow image indicating the characteristics of the shadow is superimposed on the morphological image. FIG. 8 is a diagram illustrating an example of a superimposed image according to the first embodiment. Here, FIG. 8 shows a superimposed image in which a shadow image using “amplitude difference” as a shadow feature is superimposed on a B-mode image before scan conversion. For example, as shown in FIG. 8, the image generation function 151 assigns a color for each degree of amplitude difference, and generates a shadow image colored according to the extracted “amplitude difference” of the shadow. For example, the image generation function 151 assigns colors in three stages according to the degree of the “amplitude difference”, and performs colorization according to the “amplitude difference” of the shadow.

  Then, as shown in FIG. 8, the image generation function 151 generates a superimposed image in which the generated shadow image is superimposed on the B-mode image. In FIG. 8, the case where “amplitude difference” is used as an example of the shadow feature is described as an example. However, the embodiment is not limited to this. For example, the case where “width” is used or “width” is used. And “amplitude difference” may be used.

  When the superimposed image and shadow image shown in FIGS. 6 to 8 are generated, the control function 152 controls the display 2 to display the generated superimposed image and shadow image. By observing these images, the observer can grasp at a glance the shadow position and the shadow characteristics for each position in the ultrasonic image.

  In the example described above, the case where a shadow image is displayed has been described. However, the ultrasonic diagnostic apparatus according to the first embodiment can also perform various measurements relating to shadows. Specifically, the calculation function 153 performs measurement related to the shadow based on the shadow information. For example, the calculation function 153 measures at least one of a value indicating a shadow characteristic and a ratio of the shadow in the ultrasonic scanning result.

  As described above, the calculation function 153 calculates “amplitude difference” and “width” as shadow characteristics. Furthermore, the calculation function 153 can determine a shadow pattern based on the calculated “amplitude difference” and “width”. FIG. 9 is a diagram for explaining an example of a shadow pattern according to the first embodiment. In FIG. 9, a scatter diagram (image diagram) is shown in which the vertical axis indicates “amplitude difference” and the horizontal axis indicates “width”.

  For example, the calculation function 153 calculates a “amplitude difference” and a “width” by extracting a shadow portion by at least one of the “threshold method” and the “Dip & Peak method” described above. Then, as shown in FIG. 9, the calculation function 153 uses the “A pattern” shadow, the “B pattern” shadow, and the “Speckle pattern” for the extracted shadow based on the “amplitude difference” and the “width”. Classify into:

  For example, the calculation function 153 classifies those extracted as shadows as “speckle patterns” when both “amplitude difference” and “width” are low values. Also, the calculation function 153 classifies those extracted as shadows that have a high “amplitude difference” and a low “width” as “A pattern” shadows. In addition, the calculation function 153 classifies those extracted as shadows that have high values of “amplitude difference” and “width” as shadows of “B pattern”.

  Thus, the calculation function 153 classifies the extracted shadows into various patterns based on the shadow characteristics. Thereby, for example, shadows and speckles can be further classified from those extracted as shadows. In addition, for example, a narrow “width” shadow such as a comb-shaped shadow and a wide “width” shadow generated by a bone or the like can be classified as an “A pattern” and a “B pattern”, respectively. Here, the values of “amplitude difference” and “width” for classifying each pattern can be arbitrarily set. That is, shadows can be classified based on values indicating the characteristics of shadows, and shadows can be analyzed quantitatively.

  FIG. 10 is a diagram for explaining an example of shadow pattern classification according to the first embodiment. In FIG. 10, a scatter diagram is shown in which the vertical axis indicates “width (number of pixels)” and the horizontal axis indicates “amplitude difference”. For example, as shown in FIG. 10, the calculation function 153 has three regions, a region corresponding to “A pattern”, a region corresponding to “B pattern”, and a region corresponding to “speckle pattern” in the scatter diagram. By classifying shadows into patterns. Here, what is included in the overlapping area in FIG. 10 may be classified into either according to the distance from the boundary of the area, or not classified into either. It may be the case.

  FIG. 11 is a diagram illustrating an example of a color map of shadow characteristics according to the first embodiment. In FIG. 11, the vertical axis indicates “width (number of pixels)”, the horizontal axis indicates “amplitude difference”, and a color map in which colors are assigned to the occurrence frequency differences is shown. For example, the calculation function 153 counts the number of occurrences for each of the “amplitude difference” value and the “width” value, and extracts a color corresponding to the counted value from the color bar to make it color. Note that, as shown in FIG. 11, pattern classification may be performed based on a color map.

  When the information shown in FIGS. 9 to 11 is generated, the control function 152 controls the display 2 to display the generated information. By observing these pieces of information, the observer can grasp at a glance the difference in the extracted shadow pattern and occurrence frequency. 9 to 11, the case where the extracted shadows are classified into three patterns has been described as an example. However, the embodiment is not limited to this, and for example, two or four or more are included. The pattern may be classified into the following patterns.

  As described above, the calculation function 153 can measure various information regarding the shadow. The image generation function 151 can generate various images using information measured by the calculation function 153. For example, the image generation function 151 generates a shadow image in which at least one of hue, saturation, and lightness is assigned according to a shadow pattern, and the generated shadow image is based on a result of ultrasonic scanning. A superimposed image superimposed on the image is generated.

  FIG. 12 is a diagram illustrating an example of a superimposed image according to the first embodiment. Here, FIG. 12 shows a superimposed image obtained by superimposing a shadow image in which colors are assigned to the three patterns described with reference to FIGS. 9 to 11 on a B-mode image before scan conversion. For example, as shown in FIG. 12, the image generation function 151 assigns a color to each of “speckle pattern”, “A pattern”, and “B pattern”, and colorizes the shadow image according to the extracted shadow pattern. Is generated.

  Then, as illustrated in FIG. 12, the image generation function 151 generates a superimposed image in which the generated shadow image is superimposed on the B-mode image. The control function 152 displays the generated superimposed image on the display 2. Thereby, the shadow pattern on the image can be grasped at a glance. In FIG. 12, the case where the shadows are classified into three patterns has been described as an example. However, the embodiment is not limited to this, and for example, the shadows are classified into two, four, or more patterns. It may be the case. In such a case, colors are assigned so that each pattern can be distinguished, and a shadow image is generated.

  As described above, the image generation function 151 can generate various images using the information calculated by the calculation function 153. Here, the calculation function 153 can measure various information in addition to the above-described example. For example, the calculation function 153 can also calculate the shadow ratio in the ultrasound image. 13A and 13B are diagrams for explaining an example of calculation of the shadow ratio according to the first embodiment. Here, FIG. 13A shows a diagram in which the region “R1” is set in the superimposed image shown in FIG. 8 (superposed image in which the shadow is colored according to the difference in amplitude difference). FIG. 13B shows a frequency distribution in which the vertical axis indicates the number of occurrences and the horizontal axis indicates “amplitude difference”.

  For example, as illustrated in FIG. 13A, when the input unit 3 receives a setting operation for the region “R1”, the calculation function 153 calculates a shadow ratio in the set region “R1”. For example, the calculation function 153 calculates “amplitude differences” for all the pixels included in the region “R1”, and generates the frequency distribution shown in FIG. 13B using the calculated “amplitude differences”. Then, the calculation function 153 calculates the ratio of pixels extracted as shadows. For example, the calculation function 153 calculates the ratio of each of the shadows divided into three stages according to the degree of the “amplitude difference”.

  For example, as shown in FIG. 13B, the calculation function 153 calculates the shadow ratio “47.0%” indicated by “R (Red)” on the superimposed image with “amplitude difference: 5 to 7”. calculate. Further, as illustrated in FIG. 13B, the calculation function 153 calculates a shadow ratio “21.4%” indicated by “G (Green)” on the superimposed image with “amplitude difference: 7 to 9”. Further, as shown in FIG. 13B, the calculation function 153 calculates the shadow ratio “5.04%” indicated by “B (Blue)” on the superimposed image with “amplitude difference: 9 or more”.

  Further, as shown in FIG. 13B, the calculation function 153 can calculate the average “4.99” of the “amplitude difference” in the region “R1”. Although not shown, the calculation function 153 can calculate not only the average value but also the standard deviation. Thus, when the shadow ratio is calculated by the calculation function 153, the control function 152 causes the display 2 to display the calculation result. For example, the control function 152 causes the display 2 to display the frequency distribution and ratio information illustrated in FIG. 13B.

  Note that the calculation function 153 can also calculate a ratio for each shadow pattern as the above-described shadow ratio. For example, the calculation function 153 can calculate the ratio of “speckle pattern”, “A pattern”, and “B pattern” for the region “R1” to generate a frequency distribution.

  Next, processing of the ultrasonic diagnostic apparatus according to the first embodiment will be described with reference to FIG. FIG. 14 is a flowchart for explaining a processing example of the ultrasonic diagnostic apparatus according to the first embodiment. Note that FIG. 14 shows processing when a shadow image and a measurement result are displayed. Step S101 shown in FIG. 14 is a step in which the processing circuit 15 reads the program corresponding to the control function 152 from the internal storage circuit 16 and executes it. In step S101, the processing circuit 15 determines whether or not the mode has been changed to the shadow extraction mode. In step S102, the processing circuit 15 reads the program corresponding to the calculation function 153 from the internal storage circuit 16, and is executed. In step S102, when it is determined that the mode is the shadow extraction mode (Yes in step S101), the processing circuit 15 extracts a shadow based on the reception signal in the azimuth direction.

  In step S103, the processing circuit 15 reads the program corresponding to the image generation function 151 from the internal storage circuit 16, and is executed. In step S103, the processing circuit 15 generates a shadow image. In step S <b> 104, the processing circuit 15 reads and executes a program corresponding to the calculation function 153 from the internal storage circuit 16. In step S104, the processing circuit 15 measures information related to the shadow.

  In step S105, the processing circuit 15 reads the program corresponding to the control function 152 from the internal storage circuit 16, and is executed. In step S105, the processing circuit 15 displays the shadow image and the measurement result on the display 2. Note that, in the above-described processing example, the case where information related to a shadow is measured after a shadow image is generated has been described as an example. However, the embodiment is not limited to this, and the shadow image may be generated after information related to the shadow is measured, or the generation and measurement of the shadow image are performed simultaneously. There may be.

  As described above, according to the first embodiment, the control function 152 causes the ultrasound probe to perform ultrasound scanning on the subject. The calculation function 153 analyzes the result of the ultrasonic scanning for each depth, and generates shadow information that is information regarding the shadow that appears in the result of the ultrasonic scanning, based on the analysis results for a plurality of depths. Therefore, the ultrasonic diagnostic apparatus according to the first embodiment makes it possible to accurately extract a shadow from an ultrasonic image.

  For example, in the prior art, a technique is known in which shadows in an image are extracted by analyzing the ultrasonic image in the depth direction. However, in such a conventional technique, after extracting a hard tissue, the tissue under the hard tissue is extracted as a shadow, and all the bottom of the hard tissue is extracted as a shadow. For example, shadows generated when the liver is scanned appear not only in the liver but also from the liver surface (including the vicinity) and the abdominal wall. For this reason, in the case of the processing in the distance direction as in the prior art, it is greatly affected by the structure from the abdominal surface to the liver surface. For example, when there is a hard tissue on the surface of the abdomen, all positions deeper than the tissue are extracted as shadows.

  However, since the ultrasonic diagnostic apparatus according to the first embodiment performs processing in the azimuth direction, it is also possible to identify whether the shadow is from the abdominal wall, the liver surface, or the liver. Furthermore, in the ultrasonic diagnostic apparatus according to the first embodiment, for example, even when shadows are generated stepwise in the depth direction, each shadow can be extracted.

  Further, according to the first embodiment, the image generation function 151 generates a shadow image indicating at least one of the position and the feature of the shadow based on the shadow information. In addition, the image generation function 151 generates a shadow image by assigning at least one of hue, saturation, and lightness according to the feature of the shadow. The image generation function 151 generates a superimposed image in which a shadow image is superimposed on a B-mode image based on the result of ultrasonic scanning. Therefore, the ultrasonic diagnostic apparatus according to the first embodiment makes it possible to provide an image that makes it easy to observe shadows in an ultrasonic image.

  Further, according to the first embodiment, the calculation function 153 determines a shadow pattern based on the shadow characteristics, and the image generation function 151 determines at least one of hue, saturation, and brightness as the shadow A shadow image assigned according to the pattern is generated, and a superimposed image is generated by superimposing the generated shadow image on a B-mode image based on the result of ultrasonic scanning. Therefore, the ultrasonic diagnostic apparatus according to the first embodiment can provide information reflecting the characteristics of the shadow.

  In addition, according to the first embodiment, the calculation function 153 performs measurement related to the shadow based on the shadow information. In addition, the calculation function 153 measures at least one of a value indicating the characteristics of the shadow and a ratio of the shadow in the ultrasonic scanning result. Therefore, the ultrasonic diagnostic apparatus according to the first embodiment makes it possible to quantitatively analyze shadows.

  In addition, according to the first embodiment, the calculation function 153 includes, as at least a part of the analysis performed for each depth, the signal value of each signal at the same depth obtained by ultrasonic scanning and a predetermined threshold value. Shadow information is generated by performing at least one of the comparison and the comparison between the signal value of each signal at the same depth obtained by ultrasonic scanning and the reference value and a predetermined threshold. Therefore, the ultrasonic diagnostic apparatus according to the first embodiment makes it possible to easily perform shadow extraction in the azimuth direction. Furthermore, the ultrasound diagnostic apparatus according to the first embodiment can also extract shadows that are difficult to extract by the “threshold method”.

  Further, according to the first embodiment, the calculation function 153 calculates an average value of signal values of a plurality of signals at the same depth obtained by ultrasonic scanning as at least a part of the analysis performed for each depth. Shadow information is generated by calculating the difference between the signal value of each of the plurality of signals and the average value for each depth. Therefore, the ultrasonic diagnostic apparatus according to the first embodiment can standardize signal values and facilitate processing.

(Second Embodiment)
The first embodiment has been described so far, but may be implemented in various different forms other than the first embodiment described above.

  In the first embodiment described above, the case where the average value subtraction processing is performed as the preprocessing has been described. However, the embodiment is not limited to this, and other processing can be executed as preprocessing. For example, pre-processing for removing speckle patterns included in the ultrasonic image can be executed. Specifically, the calculation function 153 generates shadow information after applying a smoothing filter in the depth direction to a signal collected by ultrasonic scanning. FIG. 15A and FIG. 15B are diagrams schematically illustrating an example of preprocessing according to the second embodiment.

  For example, the calculation function 153 obtains an ultrasonic image shown in FIG. 15B by applying a smoothing filter to the ultrasonic image shown in FIG. 15A in the depth direction. As a result, as shown in FIG. 15B, the speckle component is reduced, and the shadow can be extracted more accurately.

  Further, in the first embodiment described above, the case where amplitude data or a luminance value is used as a result of ultrasonic scanning has been described as an example. However, the embodiment is not limited to this, and reflected wave data including phase information before the envelope detection process can be used. In such a case, the calculation function 153 extracts shadows by a method different from the “threshold method” described above. For example, when the analysis is performed on the signal including the phase information, the calculation function 153 compares the amplitude of the signal including the phase information with a plurality of thresholds as at least a part of the analysis performed for each depth. Then, shadow information is generated. For example, when the signal collected by the ultrasonic scanning includes phase information, the calculation function 153 extracts the signal whose amplitude is included in a predetermined range in the signal for each depth, and generates shadow information.

  FIG. 16 is a diagram for explaining an example of threshold setting according to the second embodiment. For example, as shown in FIG. 16, the calculation function 153 extracts shadows using an upper threshold value b and a lower threshold value c set for the reflected wave data. For example, as shown in FIG. 16, the calculation function 153 extracts the position of the reflected wave data as a shadow when the reflected wave data is within the range of the threshold value b and the threshold value c. On the other hand, when the reflected wave data exceeds one of the threshold value b and the threshold value c, the calculation function 153 determines that it is not a shadow. The threshold value b and the threshold value c can be set arbitrarily.

  Further, when using reflected wave data including phase information, the reflected wave data may be squared to obtain amplitude information, and shadows may be extracted using the above-described “threshold method” and “Dip & Peak method”. .

  In the first embodiment described above, the case where the “amplitude difference” and the “width” are used as the shadow characteristics has been described. However, the embodiment is not limited to this, and may be, for example, a case where the depth information that is the starting point of the shadow or the analysis result of the frequency analysis of the reflected wave data of the signal extracted as the shadow may be used. .

  In the first embodiment described above, the case where the average value subtraction processing is performed as the preprocessing has been described. However, the embodiment is not limited to this, and the average value may not be subtracted. In such a case, a threshold value in the “threshold method” and a threshold value in the “Dip & Peak method” are set for each depth. Then, the calculation function 153 extracts a shadow by using a “threshold method” and a “Dip & Peak method” using a threshold corresponding to each depth.

  Further, in the first embodiment described above, the case where the “amplitude difference” or the ratio of the “pattern” classified based on the shadow information is calculated and the calculation result is displayed on the display 2 has been described. However, the embodiment is not limited to this, and various information can be further displayed based on the calculation result. Specifically, the calculation function 153 measures the proportion of shadow in the ultrasonic scanning result. Then, the control function 152 presents related disease information based on the shadow ratio measured by the calculation function 153. For example, as illustrated in FIG. 13B, the calculation function 153 calculates “amplitude differences” for all the pixels included in the region “R1” in the ultrasonic image. Then, the calculation function 153 includes a shadow ratio “47.0%” of “amplitude difference: 5 to 7”, a shadow ratio “21.4%” of “amplitude difference: 7 to 9”, and an “amplitude difference: 9”. The shadow ratio “5.04%” is calculated. The control function 152 causes the display 2 to display related disease information based on the ratio calculated by the calculation function 153.

  Here, the relationship between the shadow ratio and the disease is preset and stored in the internal storage circuit 16. For example, the internal memory circuit 16 may use “disease A”, “disease B”, and “disease” as related diseases when the shadow ratio of “amplitude difference: 5 to 7” exceeds “50%”. C "is stored. Further, the internal storage circuit 16 stores “disease D” and “disease E” as related diseases when the shadow ratio of “amplitude difference: 7 to 9” exceeds “20%”. Further, the internal storage circuit 16 stores “disease F” as a related disease when the shadow ratio of “amplitude difference: 9 or more” exceeds “10%”. As described above, the internal storage circuit 16 stores information on diseases set in advance according to the ratio. Note that the disease information stored by the internal storage circuit 16 is appropriately stored by the operator. That is, the relationship between the shadow ratio and the disease is arbitrarily set by the operator. The above-described example is merely an example, and various other shadow ratios and diseases are stored in association with each other. For example, not only “amplitude difference” but also “width” and “pattern” are stored in association with the ratio and the disease.

  In addition, the relationship between the shadow ratio and the disease may be a combination of shadows as appropriate. As an example, “disease A” is a disease when the shadow ratio exceeds “50%” and the shadow ratio of “amplitude difference: 7-9” exceeds “20%”. The case where it matches is also possible. Similarly, when the ratio of “pattern A” exceeds “50%” and the ratio of “pattern B” falls below “10”, “disease G” is associated with the disease. May be.

  When the ratio is calculated by the calculation function 153, the control function 152 refers to the disease information stored in the internal storage circuit 16 and displays it on the display 2. For example, the calculation function 153 allows the shadow ratio “47.0%” of “amplitude difference: 5 to 7”, the shadow ratio “21.4%” of “amplitude difference: 7 to 9”, and “amplitude difference: 9”. When the shadow ratio of “above” is calculated as “5.04%”, the control function 152 indicates that the shadow ratio of “amplitude difference: 7 to 9” exceeds “20%”. As the information, “Disease D” and “Disease E” are displayed on the display 2. Note that the above-described example is merely an example, and the control function 152 can display related disease information for various ratios. For example, the control function 152 can cause the display 2 to display related disease information based on the calculated ratio of the shadow “width” and the shadow “pattern”.

  In the above-described embodiment, the case where the ultrasonic diagnostic apparatus executes the process has been described. However, the embodiment is not limited to this, and may be executed by an image processing apparatus, for example. In such a case, the image processing apparatus includes the processing circuit 15 and the internal storage circuit 16 described above, and executes the image generation function 151, the control function 152, and the calculation function 153. For example, the internal storage circuit 16 stores the results of the ultrasonic scanning performed on the inside of the subject and programs corresponding to the image generation function 151, the control function 152, and the calculation function 153. Then, the processing circuit 15 reads out and executes a program corresponding to each function, thereby executing a shadow extraction process for the ultrasonic scanning result stored in the internal storage circuit 16.

  Note that each component of each device illustrated in the above description of the embodiment is functionally conceptual and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or a part of the distribution / integration is functionally or physically distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured. Furthermore, all or a part of each processing function performed in each device can be realized by a CPU and a program that is analyzed and executed by the CPU, or can be realized as hardware by wired logic.

  The processing method described in the above-described embodiment can be realized by executing a processing program prepared in advance on a computer such as a personal computer or a workstation. This processing program can be distributed via a network such as the Internet. The processing program is recorded on a computer-readable non-transitory recording medium such as a flash memory such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, a DVD, a USB memory, and an SD card memory. It can also be executed by being read from a non-transitory recording medium by a computer.

  As described above, according to the embodiment, it is possible to accurately extract a shadow from an ultrasonic image.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

151 Image generation function 152 Control function 153 Calculation function

Claims (13)

A control unit that causes the ultrasound probe to perform ultrasound scanning on the subject;
A processing unit that generates a shadow image by assigning at least one of hue, saturation, and brightness according to the characteristics of the acoustic shadow that appears in the result of the ultrasonic scanning;
An ultrasonic diagnostic apparatus comprising:   The processing unit analyzes the result of the ultrasonic scanning for each depth, and generates shadow information that is information regarding the acoustic shadow that appears in the result of the ultrasonic scanning based on the analysis result of a plurality of depths. The medical image diagnostic apparatus according to claim 1, wherein the shadow image is generated based on the generated shadow information.   The ultrasonic diagnostic apparatus according to claim 1, wherein the processing unit generates a superimposed image in which the shadow image is superimposed on a morphological image based on the result of the ultrasonic scanning.   The processing unit determines the acoustic shadow pattern based on the characteristics of the acoustic shadow, and assigns at least one of hue, saturation, and brightness according to the acoustic shadow pattern to the shadow image. The ultrasonic diagnostic apparatus according to claim 1, wherein a superimposed image is generated by superimposing the generated shadow image on a morphological image based on a result of the ultrasonic scanning.   The ultrasonic diagnostic apparatus according to claim 2, wherein the processing unit performs measurement related to the acoustic shadow based on the shadow information.   The ultrasonic diagnostic apparatus according to claim 5, wherein the processing unit measures at least one of a value indicating a characteristic of the acoustic shadow and a ratio of the acoustic shadow in a result of the ultrasonic scanning.   The processing unit is obtained by comparing the signal value of each signal at the same depth obtained by the ultrasonic scanning with a predetermined threshold and by the ultrasonic scanning as at least a part of the analysis performed for each depth. The ultrasonic diagnostic apparatus according to claim 2, wherein the shadow information is generated by performing at least one of a comparison between a difference between a signal value of each signal at the same depth and a reference value and a predetermined threshold value.   The processing unit calculates an average value of signal values of a plurality of signals at the same depth obtained by the ultrasonic scanning as at least a part of the analysis executed for each depth, and the plurality of the values for each depth. The ultrasound diagnostic apparatus according to claim 7, wherein the shadow information is generated by calculating a difference between a signal value of each of the signals and the average value.   The ultrasonic diagnostic apparatus according to claim 7, wherein the processing unit generates the shadow information after applying a smoothing filter in a depth direction to a signal obtained by the ultrasonic scanning.   When performing an analysis on a signal including phase information, the processing unit compares the amplitude of the signal including the phase information with a plurality of thresholds as at least a part of the analysis performed for each depth. The ultrasonic diagnostic apparatus according to claim 2, wherein the shadow information is generated.   The ultrasonic diagnosis according to claim 5, wherein the processing unit measures a ratio of the acoustic shadow in the result of the ultrasound scanning, and presents related disease information based on the measured ratio of the acoustic shadow. apparatus. A control unit that causes the ultrasonic probe to perform ultrasonic scanning on the inside of the subject;
A processing unit that analyzes the result of the ultrasonic scanning for each depth, and generates shadow information that is information relating to an acoustic shadow that appears in the result of the ultrasonic scanning based on an analysis result for a plurality of depths;
An ultrasonic diagnostic apparatus comprising: Obtain the results of the ultrasound scan on the subject,
A shadow image is generated by assigning at least one of hue, saturation, and lightness according to the characteristics of the acoustic shadow that appears in the result of the ultrasonic scanning.
An image generation method.