Ultrasonic diagnostic apparatus and diagnostic assistance method

Abstract

An ultrasonic diagnostic apparatus and a diagnosis assistance method are provided. An image analysis section (28) performs lesion portion detection on a per tomographic image basis. The image analysis section (28) outputs a position data series and a size data series indicating temporal changes in position and size of a lesion portion in a lesion portion detection state. A change rate calculation section (33) calculates a change rate indicating a degree of temporal change in contents of a tomographic image. A smoothing section (34) smoothes the position data series and the size data series based on the change rate. A marker is generated based on the smoothed position data series and the size data series.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to an ultrasonic diagnostic apparatus and a diagnosis assistance method, and particularly relates to a technique of displaying a marker that notifies of a lesion on an ultrasonic image. BACKGROUND

[0002] In an ultrasonic examination of a breast, a probe that comes into contact with the surface of the breast is scanned along the surface of the breast. During this scanning, a real-time tomographic image displayed on a display is observed by an examiner, and it is determined from this observation whether or not there is a lesion. In a case where a lesion is found, the lesion is examined in detail including the surrounding tissue. The same is true of ultrasonic examinations of other organs.

[0003] It is not easy to visually determine a lesion that temporarily appears on a real-time changing tomographic image. Particularly in ultrasonic examinations of a breast, the tissue appearing on the tomographic image has a multilayered structure, and it is not easy for an examiner to instantaneously recognize a lesion included therein.

[0004] As a technique to assist determination of a lesion, there is CADe (Computer Aided Detection). This technique detects a lesion (more correctly, a lesion candidate) within a tomographic image, for example, on a per frame basis, and notifies of the lesion when the lesion is included in the tomographic image. For example, a marker that encloses the lesion is displayed on the tomographic image. CADe is utilized together with or included in CAD (Computer Aided Diagnosis).

[0005] A medical apparatus having a CAD function is disclosed in Document 1 (Japanese Patent Application Publication No. 2020-178989). The medical apparatus has a function of prompting a probe scanning speed to an examiner by changing the color of a marker in accordance with the probe scanning speed. In Document 1, a technique related to smoothing of the marker is not disclosed. In addition, in the present application specification, a lesion means a site that is likely to be a disease or a site that needs to be carefully examined. SUMMARY

[0006] PROBLEMS TO BE SOLVED BY THE INVENTION

[0007] In an ultrasonic diagnostic apparatus equipped with a CADe function or a CAD function, a marker that notifies of a lesion is displayed on an ultrasonic image. By the appearance of the marker and its persistent display, it is possible to notify an examiner of the presence of a lesion, thereby prompting the examiner to perform a detailed examination of the lesion.

[0008] However, if the marker is generated and displayed faithfully according to the detection result of each lesion portion even though the content of the ultrasonic image hardly changes, the display of the marker can become unstable depending on the situation. If the position and size of the marker change every frame, the marker is displayed flickering, which can cause stress and uneasiness to an examiner who observes the marker. In contrast, it is also considered to display the marker on the basis of applying some smoothing processing, but in this case, in a situation where the content of the ultrasonic image changes greatly, there can be a problem that the marker cannot be displayed responsively and excellently with respect to a lesion portion that appears momentarily. This can become a major factor in overlooking the lesion portion.

[0009] An object of the present disclosure is to perform marker display that is appropriate to the situation when a detected lesion portion is informed by a marker.

[0010] Means for solving the problem

[0011] The ultrasonic diagnostic apparatus according to the present disclosure is characterized by including: an analysis section that determines the presence of a lesion portion per frame data based on a frame data series acquired by repeatedly scanning an ultrasonic beam, thereby outputting a presence data series; a smoothing section that dynamically changes a smoothing degree according to a change rate that indicates the degree of temporal change in the content of the frame data and smoothes the presence data series, thereby outputting a smoothed presence data series; and a generation section that generates a marker that informs the lesion portion based on the smoothed presence data series, and displays the marker on an ultrasonic image formed based on the frame data series.

[0012] The diagnostic assistance method according to the present disclosure is characterized by including: a process of determining the presence of a lesion portion per frame data based on a frame data series acquired by repeatedly scanning an ultrasonic beam, thereby generating a presence data series; a process of dynamically changing a smoothing degree according to a change rate that indicates the degree of temporal change in the content of the frame data and smoothing the presence data series, thereby generating a smoothed presence data series; and a process of generating a marker that informs the lesion portion based on the smoothed presence data series, and displaying the marker on an ultrasonic image formed based on the frame data series.

[0013] The program disclosed herein is a program for performing a diagnostic assistance method in an information processing device. The program is characterized by comprising: a function to determine the location of a lesion based on a series of frame data acquired by repeatedly scanning an ultrasound beam, thereby generating a location data series; a function to dynamically change the smoothing degree according to the rate of change representing the degree of temporal change in the content of the frame data and smooth the location data series, thereby generating a smoothed location data series; and a function to generate a marker notifying the lesion based on the smoothed location data series, and to display the marker on an ultrasound image formed based on the frame data series. Attached Figure Description

[0014] Figure 1 This is a block diagram illustrating an ultrasound diagnostic apparatus according to an embodiment.

[0015] Figure 2 This is a diagram illustrating the label display process.

[0016] Figure 3 This is a diagram showing an example of the structure of the smoothing section.

[0017] Figure 4 This is a graph showing the relationship between the rate of change and the smoothing number.

[0018] Figure 5 An example of a weighting function is shown.

[0019] Figure 6 This is a diagram showing the first example.

[0020] Figure 7 This is a diagram showing the second example.

[0021] Figure 8 This is a diagram illustrating an example of smoothing processing.

[0022] Figure 9 This is a flowchart illustrating the first action example.

[0023] Figure 10 This is a flowchart illustrating the second action example. Detailed Implementation

[0024] The embodiments will now be described with reference to the accompanying drawings.

[0025] (1) Overview of the implementation method

[0026] The ultrasound diagnostic apparatus according to the embodiment includes an analysis unit, a smoothing unit, and a generation unit. The analysis unit determines the location of a lesion based on a series of frame data acquired by repeatedly scanning an ultrasound beam, and outputs a location data series. The smoothing unit dynamically changes the smoothing degree according to the rate of change of the degree of temporal change in the frame data content and smooths the location data series, thereby outputting the smoothed location data series. The generation unit generates a marker indicating the lesion based on the smoothed location data series. The marker is displayed on the ultrasound image formed based on the frame data series. The analysis unit is equivalent to an analyzer. The smoothing unit is equivalent to a smoother (smoother, filter). The generation unit is equivalent to a generator.

[0027] According to the above structure, markers are displayed based on the smoothed data column. The smoothing degree is determined by the rate of change representing the temporal variation of the frame data content. Increasing the smoothing degree when the rate of change is small, such as when the content of an ultrasound image doesn't change much, can prevent or mitigate unstable marker display. For example, it can suppress flickering marker display. On the other hand, decreasing the smoothing degree when the rate of change is large, such as when the content of an ultrasound image changes significantly, can display markers with excellent responsiveness, thereby preventing or mitigating the overlooking of transiently appearing lesions. Based on the structure of the embodiment, marker display adapted to the situation can be achieved, thus improving the reliability of marker display.

[0028] The location of a lesion refers to the place or region where a lesion exists within the ultrasound image. The location of a lesion can be determined by identifying multiple points representing the lesion, or by identifying the area containing or containing the lesion. When calculating the rate of change, information such as detector movement, differential information between frames, and the transmit / receive frame rate can also be referenced.

[0029] In this embodiment, the analysis unit determines the location and size of the lesion as the location of the lesion, and outputs a location data column and a size data column as the location data column. The smoothing unit includes a first smoothing unit that smooths the location data column and a second smoothing unit that smooths the size data column. The generation unit generates a marker based on the smoothed location data column and the smoothed size data column. In this embodiment, each location data in the location data column represents the center position of the region including the lesion, and each size data in the size data column represents the corner position of the region. The first smoothing unit corresponds to a first smoother. The second smoothing unit corresponds to a second smoother.

[0030] The main factors contributing to the instability of marker display include temporal variations in the detected location and size of the lesion. These are smoothed individually. Therefore, the marker as a whole can be displayed stably even when the content of the ultrasound image remains relatively unchanged. Furthermore, variations involving smoothing the marker itself are also considered.

[0031] In this implementation, the smoothing unit reduces the smoothing degree as the rate of change increases. According to this structure, the greater the degree of change in the frame data content, the more emphasis is placed on responsiveness; conversely, the smaller the degree of change in the frame data content, the more emphasis is placed on smoothness or stability.

[0032] In this implementation, the smoothing unit increases or decreases the number of frame data used in smoothing by increasing or decreasing the smoothing degree. A weighting function may also be used during smoothing. The numerical value representing the smoothing degree or the number of frames used in smoothing may also be displayed on the screen. Alternatively, a mode may be set to fix the smoothing degree at a given value, either by user selection or automatic setting.

[0033] In one embodiment, the smoothing unit determines temporal discontinuities in the lesion based on the output of the analysis unit, and restricts marker generation if a temporal discontinuity is determined. In another embodiment, the smoothing unit determines spatial discontinuities in the lesion based on the output of the analysis unit, and restricts marker generation if a spatial discontinuity is determined. If either a temporal or spatial discontinuity is determined, marker generation may be restricted so that the markers are not displayed, or the display of smoothed markers may be restricted. The subsequent determination of the failure to meet the temporal continuity condition is equivalent to the determination of temporal discontinuity. The subsequent determination of the failure to meet the spatial continuity condition is equivalent to the determination of spatial discontinuity.

[0034] The diagnostic assistance method described in this implementation includes an analysis step, a smoothing step, and a generation step. In the analysis step, based on a series of frame data acquired by repeatedly scanning an ultrasound beam, the location of the lesion is determined for each frame, thereby generating a location data series. In the smoothing step, the smoothing degree is dynamically adjusted according to the rate of change representing the temporal variation of the frame data content, and the location data series is smoothed, thereby generating a smoothed location data series. In the generation step, based on the smoothed location data series, a marker indicating the lesion is generated. This marker is then displayed on an ultrasound image formed based on the frame data series.

[0035] The aforementioned diagnostic assistance methods can be implemented through hardware or software. In the latter case, the program for executing the diagnostic assistance method is installed in an information processing device via a portable storage medium or a network. The concept of an information processing device includes an ultrasound diagnostic device, an ultrasound image processing device, and a computer. The information processing device has a non-temporary storage medium storing the aforementioned program.

[0036] (2) Details of the implementation method

[0037] exist Figure 1 The structure of the ultrasound diagnostic apparatus according to the embodiment is shown in a block diagram. The ultrasound diagnostic apparatus, installed in medical institutions such as hospitals, is a medical device that forms an ultrasound image based on the received signal obtained by transmitting and receiving ultrasound waves directed at a living organism (the subject). In this embodiment, the organ targeted by the ultrasound diagnosis is, for example, the breast.

[0038] In large-scale breast screening, it is necessary to identify lesions quickly and without omission. The ultrasound diagnostic apparatus described in this embodiment, in order to assist in the identification of lesions based on the examiner, has a CADe function that automatically detects lesions (e.g., low-brightness tumor images) included in the ultrasound image. This will be described in detail later.

[0039] The detector 10 functions as a unit for transmitting and receiving ultrasound waves. The detector 10 is a portable transceiver that is held and operated by the examiner (physician, examination technician, etc.). During ultrasound diagnosis of the breast, the transceiver surface (specifically, the acoustic lens surface) of the detector 10 is in contact with the patient's chest surface 16. The detector 10 is manually scanned along the chest surface 16 while observing the real-time displayed tomographic images.

[0040] In the illustrated structural example, the detector 10 includes an array of vibrating elements consisting of multiple one-dimensionally arranged transducers. An ultrasonic beam (transmitting beam and receiving beam) 12 is formed by the vibrating element array, and a scanning surface 14 is formed by electronically scanning the ultrasonic beam 12. The scanning surface 14 is the observation surface, i.e., the two-dimensional data acquisition area. Known electronic scanning methods for the ultrasonic beam 12 include electronic sector scanning and electronic linear scanning. Convex scanning of the ultrasonic beam 12 can also be performed. Alternatively, a 2D vibrating element array can be provided within the ultrasonic detector 10, and body data can be acquired from a living organism through two-dimensional scanning of the ultrasonic beam. The received frame data sequence, described later, is generated by repeatedly scanning the ultrasonic beam.

[0041] In the illustrated structural example, a positioning system is provided to determine the position information of the detector 10. The positioning system consists of a magnetic sensor 18, a magnetic field generator 20, and a positioning controller 21. The magnetic sensor 18 is installed on the detector 10 (more precisely, the detector head within the detector). The magnetic field generated by the magnetic field generator 20 is detected by the magnetic sensor 18. Thus, the three-dimensional coordinate information of the magnetic sensor 18 is obtained. Based on this three-dimensional coordinate information, the position and orientation of the detector 10 are determined. The position information is transmitted from the positioning controller to the mark generation unit 30 and the main control unit 38.

[0042] The transmitting circuit 22 functions as a transmitting beamformer. Specifically, during transmission, the transmitting circuit 22 supplies multiple transmitting signals in parallel to the vibrating element array, thereby forming a transmitting beam. During reception, if reflected waves from the living organism reach the vibrating element array, multiple receiving signals are output in parallel from the multiple vibrating elements. The receiving circuit 24 functions as a receiving beamformer, generating beam data by performing phase-alignment and summing (also known as delay and summing) on ​​the multiple receiving signals.

[0043] Incidentally, each electronic scan generates multiple beam data arranged along the electronic scan direction, which constitute the received frame data corresponding to the scan surface 14. Each beam data consists of multiple echo data arranged along the depth direction. A beam data processing unit is provided in the subsequent stage of the receiving circuit 24, but its illustration is omitted.

[0044] The image forming unit 26 is an electronic circuit that generates tomographic images (B-mode tomographic images) based on received frame data. It has a DSC (Digital Scan Converter). The DSC has coordinate transformation, pixel interpolation, and frame rate conversion functions. More specifically, in the image forming unit 26, a display frame data column is formed based on the received frame data column. The multiple display frame data constituting the display frame data column are multiple tomographic image data, and their data constitute a real-time motion image. Ultrasound images other than tomographic images can also be generated. For example, color stream mapping images can be formed, and three-dimensional images representing tissues can also be formed. The display frame data column is transmitted to the image resolution unit 28 and the display processing unit 32.

[0045] The image analysis unit 28 is the module that performs the CADe function. The image analysis unit 28 performs lesion detection processing according to each display frame data, that is, according to each tomographic image. Specifically, it uses machine learning networks such as CNNs (Convolutional Neural Networks) to explore regions within the tomographic image that have pre-learned features similar to those of lesions. The lesions to be detected are predetermined by the network designer. For example, the lesions to be detected include neoplastic lesions and non-neoplastic lesions. During lesion detection processing, binarization, edge detection, and other processing can also be applied to the tomographic image.

[0046] When a lesion is detected, lesion information is output from the image analysis unit 28. This lesion information includes a lesion detection marker, the reliability of the lesion, the location information (location data) of the lesion, and the size information (size data) of the lesion. The lesion information is transmitted from the image analysis unit 28 to the marker generation unit 30 according to each display frame. In other words, the location data column and the size data column are transmitted from the image analysis unit 28 to the marker generation unit 30.

[0047] The location information of the lesion can be, for example, the coordinates of the center point (or centroid) of the enclosed region corresponding to the lesion, or the coordinates of the center point (or centroid) of the graphic surrounding the lesion. The size information of the lesion can be, for example, the size of the graphic including the lesion. For instance, a rectangle circumscribed and enclosing the lesion can be defined, and the size of the lesion can be determined based on the coordinates of its center point and its upper left corner. Given the coordinates of the center point, the coordinates of the upper left corner can also be considered as the size information of the lesion. Alternatively, the area of ​​the enclosed region corresponding to the lesion can be calculated as the size information of the lesion. Multiple lesions can also be detected in parallel. The location and size information of the lesion can be collectively referred to as the location information of the lesion.

[0048] The marker generation unit 30 generates markers based on lesion information according to each display frame data. A marker is a display element indicating the location of a lesion. Specifically, the marker has a shape that surrounds the lesion, and the center position and size of the lesion can be determined by observing the marker. When the marker is observed continuously on the timeline, it corresponds to a dynamic graphic (moving image). When the marker is observed individually according to each display frame data, it corresponds to a static graphic (still image).

[0049] The marker generation unit 30 according to the embodiment includes a rate of change calculation unit 33 and a smoothing unit 34. The rate of change calculation unit 33 calculates the rate of change for each display frame data as information representing the degree of temporal change in the display frame data content. For example, it may calculate the difference or correlation values ​​between display frame data and use the calculation result as the rate of change. It may also calculate the rate of change based on the temporal change of position information output from the positioning system. This is because a large detector movement (detector movement speed) presumes a large temporal change in the display frame data content, and a small detector movement presumes a small temporal change in the display frame data content. The rate of change may also be calculated based on multiple pieces of information representing the degree of temporal change in the display frame data content.

[0050] When calculating correlation values ​​between display frame data, a reference region can be set for each display frame data based on the center position of the lesion, and the correlation value can be calculated between two reference regions. In this case, the difference of pixel values ​​can be calculated according to each coordinate, and the sum of these differences can be normalized using the number of pixels (area) to calculate the correlation value. Alternatively, the rate of change can be calculated based on the correlation value of the histogram between two reference regions, the optical flow obtained from the calculation between the two reference regions, etc. Before calculating the rate of change, preprocessing such as segmentation and binarization can be applied to each display frame data.

[0051] The rate of change can be calculated based on the transmit / receive frame frequency, or the transmit / receive frame frequency itself can be used as the rate of change. This is because, with a high transmit / receive frame frequency, the temporal variation of the displayed frame data content is usually larger, while with a low transmit / receive frame frequency, the temporal variation of the displayed frame data content is usually smaller. However, when the detector 10 is completely stationary, the content of the displayed frame data is stable regardless of the transmit / receive frame frequency. Therefore, it is desirable to use the transmit / receive frame frequency as auxiliary information.

[0052] The smoothing unit 34 performs smoothing processing. In this embodiment, smoothing processing is applied separately to the position data column and size data column generated and output by the image analysis unit 28. In this embodiment, as will be explained later with specific examples, smoothing processing is applied to the center coordinates and the upper left corner coordinates of the rectangular region circumscribed with the lesion.

[0053] The smaller the rate of change, the greater the smoothing degree of the smoothing unit 34; conversely, the greater the rate of change, the smaller the smoothing degree of the smoothing unit 34. Through such adaptive changes in the smoothing degree, it is possible to achieve both stable display of markers when the content of the ultrasound image remains relatively unchanged and responsive marker display when the content of the ultrasound image changes significantly.

[0054] In practice, the smoothing unit 34 increases the number of referenced data (smoothing number) in the smoothing process when the rate of change is small, and decreases the number of referenced data in the smoothing process when the rate of change is large. Here, the number of data refers to the number of frames, which is equivalent to a time window that traces back a certain period from the present to the past. The maximum and minimum values ​​of the number of referenced frames can also be determined by the user or automatically.

[0055] The marker generation unit 30 generates markers as still images based on smoothed position data columns and smoothed size data columns, according to each display frame data. The marker generation unit 30 includes a memory for storing data required for smoothing processing.

[0056] More specifically, the marker generation unit 30 generates markers only when both temporal continuity and spatial continuity conditions are met. If either the temporal continuity or spatial continuity condition is not met, the marker is set not to be displayed. The temporal continuity condition is met when lesions are continuously detected as a whole of m (where m is an integer greater than or equal to 2) display frames, including the current display frame data. The spatial continuity condition is met when the distance between the center of the lesion in the reference display frame data and the center of the lesion in the current display frame data is less than or equal to a given value. The reference display frame data is, for example, the display frame data acquired at the time point when the lesion was first detected during continuous detection of the lesion. Alternatively, the reference display frame data may be the previous display frame data.

[0057] If lesion detection is interrupted within a certain time frame, marker display is restricted. Furthermore, if the movement of the lesion is equivalent to an unnatural jump, marker display is restricted. This avoids marker display when no lesion is detected, and prevents sudden marker display due to false detection.

[0058] However, lesion detection may be temporarily interrupted due to changes in detector contact or noise. Therefore, the marking display conditions or marking display limitations can be changed by the examiner or automatically. In cases where no continuous condition is met, marking can be generated and displayed based on unsmoothed position and size data instead of not displaying the markings.

[0059] In the marker generation unit 30, when determining the smoothing degree based on the rate of change, a transformation table or a transformation function can be used. During smoothing processing, a weighting function where the weights change along the time axis can also be used. In the marker generation unit 30, graphic data including markers is generated for each display frame and transmitted to the display processing unit 32.

[0060] The image forming unit 26, the image parsing unit 28, and the tag generation unit 30 can each be configured by a processor. A single processor can also function as the image forming unit 26, the image parsing unit 28, and the tag generation unit 30. The CPU described later can also function as the image forming unit 26, the image parsing unit 28, and the tag generation unit 30.

[0061] The display processing unit 32 has color processing and image synthesis functions. In the display processing unit 32, graphic data including markers is synthesized from display frame data (tomographic images), thereby generating an image displayed on the display 36. The display 36 is composed of an LCD, an organic EL display device, or the like. The tomographic image, as a moving image, is displayed in real time on the display 36, and markers are also displayed as part of the graphic image. The display processing unit 32 is, for example, composed of a processor.

[0062] Main control unit 38 control Figure 1 The operation of each element is shown. In this embodiment, the main control unit 38 consists of a CPU and a program. An operation panel 40 is connected to the main control unit 38. The operation panel 40 is an input device, which has multiple switches, multiple buttons, a trackball, a keyboard, etc. In this embodiment, the display frame data column is provided to the image analysis unit 28, but the received frame data column can also be provided to the image analysis unit 28 (reference symbol 42). In this case, a second image forming unit can also be provided to easily generate the display frame data column based on the received frame data column.

[0063] exist Figure 2 The labeling process is illustrated. A lesion 46 is included in the tomographic image 44. The lesion 46 is detected in the image resolution unit. When detecting the lesion 46, for example, a rectangle (or region) 52 is defined circumscribed by the lesion 46. In practice, the coordinates of the center point 48 and the coordinates of the upper left corner point 50 within the rectangle 52 can be determined. The lesion can also be detected based on image features such as edge quantity.

[0064] Rectangle 54 is defined as a shape that leaves certain margins 56 and 58 in the horizontal and vertical directions outside rectangle 52. This rectangle 54 is displayed as marker 64 on the tomographic image. Marker 64 is a shape that surrounds the lesion 46 and its surroundings. In the illustrated example, marker 64 is composed of dashed lines. The display style of marker 64 can be freely selected. For example, a marker composed of solid lines can also be displayed, or a marker composed of four elements representing only the four corner parts can also be displayed. Circular or elliptical markers can also be displayed.

[0065] If the position and size of the displayed marker 64 change constantly with each frame, even though the content of the displayed frame data remains almost unchanged (i.e., the lesion area shows almost no change), it can cause stress or anxiety for the examiner. On the other hand, it is also important to effectively prevent the omission of sudden lesions when the content of the displayed frame data changes significantly. From this perspective, in the implementation, as already explained, and further as will be explained in the specific examples below, adaptive smoothing processing based on the rate of change is performed.

[0066] exist Figure 3 The structure of the smoothing unit 34 is shown. The smoothing unit 34 has a first smoothing unit 34A and a second smoothing unit 34B. The first smoothing unit 34A smooths the position data column. The second smoothing unit 34B smooths the size data column. In addition, a third smoothing unit may be provided to smooth the reliability of lesion detection.

[0067] exist Figure 4 In the section on smoothing, the relationship between the rate of change R and the number of reference data (smoothing number) N is shown. As illustrated by the linear function 66A, the number of reference data N can also decrease monotonically as the rate of change R increases. Alternatively, the number of reference data N can be determined based on the rate of change R using the nonlinear function 66B.

[0068] exist Figure 5 The weight function 106 is shown in the diagram. The horizontal axis represents the time axis, where n represents the current frame number, and n-1 to n-5 represent past frames. The vertical axis represents the weight w. As shown by the weight function 106, newer data can be assigned a larger weight w. The weight function 106 can also be scaled appropriately for a time window determined by the rate of change R. The weight can be set uniformly within the time window, or it can vary linearly within the time window.

[0069] exist Figure 6 The first marker is shown as an example. Figure 7The second example of the label display is shown. The first example, for instance, represents a state where the detector's moving speed is high and a large rate of change is calculated. The second example, for instance, represents a state where the detector's moving speed is low and a small rate of change is calculated. Figure 6 as well as Figure 7 In the middle, the horizontal axis is the time axis.

[0070] exist Figure 6 The first example of marker display shown includes tomographic images 70A-70D at various time points, among which lesions 72A-72D are included. On the time axis, the appearance (content, location, etc.) of the lesions changes significantly over time. In this case, a small degree of smoothing is determined, and at each time point, markers 74A-74D surrounding the lesions 72A-72D are generated and displayed with excellent responsiveness. This prevents or reduces the possibility of overlooking lesions.

[0071] exist Figure 7 The second example shown includes tomographic images 76A–76D at various time points, which include lesions 78A–78D. The appearance of the lesions does not change significantly along the time axis. Under these circumstances, a large degree of smoothing is determined, and at each time point, the changes in the markers 79A–79D surrounding the lesions 78A–78D are suppressed. Thus, the phenomenon of flickering markers is suppressed.

[0072] exist Figure 8 The image shows an example of smoothing processing. The vertical axis is the time axis. Symbol 80 indicates one data set. Multiple data sets are arranged along the time axis. Along the horizontal axis are shown frame number 82, presence or absence of lesions 84, detector movement speed as rate of change 86, smoothing number (reference data number) 88, center point coordinates 90, smoothed center point coordinates 92, top left corner coordinates 94, and smoothed top left corner coordinates 96.

[0073] At the time point determined by frame number 11, no lesion was detected. No smoothing was performed. At the time point determined by frame number 12, a lesion was detected, and a smoothing number of 5 was determined based on the movement speed 10. However, no smoothing was performed at this time point; a marker was generated based on the center point coordinates C12 and the upper left corner coordinates L12. At the time point determined by frame number 13, a lesion was detected, and a smoothing number of 5 was determined based on the movement speed 11. At this time point, the smoothed center point coordinates C13' were calculated based on the two center point coordinates C12 and C13 (see symbol 98. The two coordinates in parentheses indicate the smoothing range). Similarly, the smoothed upper left corner coordinates L13' were calculated based on the two upper left corner coordinates L12 and L13 (see symbol 100). A marker was generated based on the smoothed center point coordinates C13' and the smoothed upper left corner coordinates L13'.

[0074] At the time point determined by frame number 18, a lesion was detected (detected consecutively across frames 12-18). The smoothed center point coordinate C18' was calculated based on the five center point coordinates C14-C18 (refer to symbol 102). Similarly, the smoothed upper left corner coordinate L18' was calculated based on the five upper left corner coordinates L14-L18. A marker was generated based on the smoothed center point coordinate C18' and the smoothed upper left corner coordinate L18' (refer to symbol 104).

[0075] From the time point determined by frame number 31 to the time point determined by frame number 34, lesion detection is continuous, but the movement speed is relatively high during this period, and the smoothing factor is small. In this implementation, the smoothing degree is adaptively determined based on the variation in the rate of change. This includes adaptive switching of smoothing on and off.

[0076] exist Figure 9 The first action example of the marker generation unit is shown. In S10, it is determined whether a lesion has been detected. For example, it can also be determined that a lesion has been detected if the reliability is above a given value. If the termination condition is met in S10, the process ends.

[0077] If a lesion is detected, in S12, the smoothing number (reference data number) is determined based on the rate of change. In S14, it is determined whether the temporal continuity condition (condition 1) is met. In S15, it is determined whether the spatial continuity condition (condition 2) is met. If both conditions 1 and 2 are met, proceed to S16; otherwise, proceed to S18.

[0078] In S16, markers are generated based on the smoothing process results, specifically based on the smoothed position and size data columns. In S20, the generated markers are displayed. In S18, the display of the markers is restricted. Specifically, the markers are set to not be displayed. The above process is repeated.

[0079] exist Figure 10 The second action example of the marker generation unit is shown in the diagram. Additionally, in... Figure 10 In the middle, to and Figure 9 The same steps in the process shown are labeled with the same step number, and their descriptions are omitted.

[0080] In the second action example, if neither the first nor the second condition is met, in S21, a marker is generated based on restrictions on smoothing. That is, a marker is generated based on the unsmoothed position data and size data, and then displayed in S20.

[0081] In either the first or second action example, smoothed markers are displayed based on the smoothing degree according to the rate of change, under certain conditions. In cases where the content of the tomographic image remains almost unchanged, flickering marker display can be effectively prevented or mitigated. In cases where the content of the tomographic image changes significantly, markers can reliably notify of suddenly detected lesions.

Claims

1. An ultrasonic diagnostic device, characterized in that, include: The analysis unit (28) determines the location of the lesion based on the frame data column obtained by repeatedly scanning the ultrasound beam, and outputs the location data column accordingly; The smoothing unit (34) dynamically changes the smoothing degree according to the rate of change representing the degree of temporal change in the frame data content and smooths the data column in question, thereby outputting the smoothed data column in question. The smoothing unit (34) reduces the smoothing degree as the rate of change increases; and The generation unit (30) generates a marker to notify the lesion based on the smoothed data column. The marker is displayed on the ultrasound image formed based on the frame data column.

2. The ultrasonic diagnostic device according to claim 1, characterized in that, The parsing unit (28) determines the location and size of the lesion as the location of the lesion, and outputs a location data column and a size data column as the location data column. The smoothing unit (34) includes a first smoothing unit (34A) that smooths the position data column and a second smoothing unit (34B) that smooths the size data column. The generation unit (30) generates the mark based on the smoothed position data column and the smoothed size data column.

3. The ultrasonic diagnostic device according to claim 2, characterized in that, Each location data in the location data column represents the center location of the region including the lesion. Each dimension in the dimension data column represents the corner position of the region.

4. The ultrasonic diagnostic device according to claim 1, characterized in that, When the smoothing unit (34) increases or decreases the smoothing degree, it increases or decreases the number of frame data used in the smoothing process.

5. The ultrasonic diagnostic device according to claim 1, characterized in that, The generating unit (30): Based on the output of the analysis unit (28), a temporal discontinuity is determined for the lesion. The generation of the marker is restricted when the time discontinuity is determined.

6. The ultrasonic diagnostic device according to claim 1, characterized in that, The generating unit (30): Based on the output of the analysis unit (28), a spatial discontinuity is determined for the lesion. The generation of the marker is restricted when the spatial discontinuity is determined.

7. A diagnostic aid method, characterized in that, include: The process (28) involves determining the location of the lesion based on the frame data obtained by repeatedly scanning the ultrasound beam, and thereby generating the data column. The smoothing degree is dynamically changed based on the rate of change representing the temporal change of the frame data content, and the data column is smoothed accordingly, thereby generating a smoothed data column. The smoothing degree decreases as the rate of change increases (34). The process (30) involves generating a marker to notify the lesion based on the smoothed data column. The marker is displayed on the ultrasound image formed based on the frame data column.

8. A program product comprising a program for executing a diagnostic assistance method in an information processing device, characterized in that, The procedure includes: Based on the frame data obtained by repeatedly scanning the ultrasound beam, the location of the lesion is determined according to each frame data, thereby generating the location data column (28). The smoothing degree is dynamically changed based on the rate of change representing the temporal change of the frame data content, and the data column is smoothed accordingly, thereby generating a smoothed data column. A function (34) is also provided to reduce the smoothing degree as the rate of change increases. (30) A function to generate a marker to notify the lesion based on the smoothed data column. The marker is displayed on the ultrasound image formed based on the frame data column.

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