JP7832026B2 - Medical image processing device, medical image diagnostic device, ultrasound diagnostic device, medical image processing method, and medical image processing program - Google Patents

Description

The embodiments disclosed herein and in the drawings relate to medical image processing equipment, medical image diagnostic equipment, ultrasound diagnostic equipment, medical image processing methods, and medical image processing programs.

In the field of medical imaging, when performing examinations or treatments, it is necessary to register the three-dimensional image data of the examination site on the subject with the three-dimensional image data acquired before the examination or treatment. In other words, alignment is required.

For example, before performing a diagnosis or surgery on a subject's examination site, a CT (Computed Tomography) or MR (Magnetic Resonance) scan is typically performed on the examination site to acquire three-dimensional CT or MR volume data with a good anatomical environment. Next, when performing a diagnosis or surgery on the examination site, a three-dimensional US (Ultra-Sonic) scan is performed on the examination site to acquire real-time three-dimensional US volume data. Subsequently, the three-dimensional CT or MR volume data and the three-dimensional US volume data are registered. This allows for rapid locating of the anatomical plane in the high-resolution three-dimensional CT or MR volume data corresponding to the real-time three-dimensional US volume data of the examination site during diagnosis or surgery. This facilitates accurate analysis and judgment by the physician, enabling accurate diagnosis or precise surgical procedures.

Here, we will explain the registration method for 3D CT or MR volume data and 3D US volume data using surgical procedures as an example. When 3D CT or MR volume data of the examination site is acquired, and 3D US volume data of the same examination site is acquired during surgery, a target structure, which serves as the registration criterion, is determined based on the surgical information obtained during the surgery on the examination site. This target structure is then artificially located in the 3D CT or MR volume data. Subsequently, the US probe is manipulated to find structures similar to the target structure found in the 3D CT or MR volume data in the 3D US volume data. These two structures are then used as the basis for registration between the 3D CT or MR volume data and the 3D US volume data.

However, because it is difficult for physicians to accurately locate target structures from three-dimensional CT or MR volume data, there is usually a significant discrepancy between the target structure found from three-dimensional CT or MR volume data and similar structures found from three-dimensional US volume data. Furthermore, the initial transformation parameters used in registration calculations are calculated based on the target structure and similar structures, and therefore these initial transformation parameters are not accurate. Because it is necessary to constantly search for the target structure and its similar structures to obtain accurate initial transformation parameters, the time required for registration becomes longer.

Japanese Patent Publication No. 2014-239731

One of the problems that the embodiments disclosed herein and in the drawings aim to solve is to perform registration in a short time. However, the problems solved by the embodiments disclosed herein and in the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems.

The medical image processing apparatus according to this embodiment comprises a first acquisition unit, a cross-section determination unit, a second acquisition unit, a cross-section detection unit, a cross-section acquisition unit, and a registration unit. The first acquisition unit acquires first volume data of the examination area of the subject. The cross-section determination unit determines the cross-section at the examination area. The second acquisition unit acquires second volume data of the examination area of the subject. The cross-section detection unit automatically detects the cross-section in the first volume data. The cross-section acquisition unit acquires the cross-section in the second volume data. The registration unit registers the first volume data and the second volume data based on the cross-section in the first volume data and the cross-section in the second volume data.

Figure 1 is a block diagram showing the configuration of a medical image processing apparatus according to the first embodiment. Figure 2 is a flowchart of the registration process in the first embodiment. Figure 3 is a flowchart of the registration process when the heart of the first embodiment is the subject of examination. Figure 4 is a schematic diagram illustrating a method for finding the 4CH plane from three-dimensional CT volume data of the heart. Figure 5A shows a 4CH plane obtained from three-dimensional CT volume data. Figure 5B shows a 4CH plane obtained from three-dimensional US volume data. Figure 6 is a flowchart of the registration process when the heart is the subject of examination according to the second embodiment. Figure 7 is a block diagram showing the configuration of an ultrasound diagnostic apparatus according to the third embodiment. Figure 8 is a block diagram showing the configuration of the processing circuit of the ultrasound diagnostic apparatus according to the third embodiment.

The following describes the medical image processing apparatus, medical image diagnostic apparatus, ultrasound diagnostic apparatus, medical image processing method, and medical image processing program according to the embodiment, with reference to the attached drawings. Note that the embodiments described below are merely examples and are not limited to the embodiments described below. Furthermore, the contents described in one embodiment are, in principle, applicable to other embodiments as well.

(First Embodiment)
Figure 1 is a block diagram showing the configuration of a medical image processing apparatus 1 according to the first embodiment. For example, as shown in Figure 1, the medical image processing apparatus 1 includes an input interface 102, a display 103, a storage circuit 150, and a processing circuit 160.

The input interface 102 is implemented using a trackball for various settings, switch buttons, a mouse, a keyboard, a touchpad for input operations by touching the operating surface, a touchscreen integrating the display screen and touchpad, a non-contact input circuit using an optical sensor, and an audio input circuit. The input interface 102 is connected to the processing circuit 160 and converts the input operations received from the operator into electrical signals, which are then output to the processing circuit 160.

The display 103 is connected to the processing circuit 160 and displays various information and image data output from the processing circuit 160. For example, the display 103 can be implemented as a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, a touch panel, etc. For instance, the display 103 displays a GUI (Graphical User Interface) for receiving operator instructions, various display images, and various processing results from the processing circuit 160. The display 103 is an example of a display unit.

The memory circuit 150 is connected to the processing circuit 160 and stores various types of data. For example, the memory circuit 150 can be implemented using semiconductor memory elements such as RAM (Random Access Memory) or flash memory, or by means of a hard disk or optical disc. The memory circuit 150 also stores programs corresponding to each processing function executed by the processing circuit 160.

The processing circuit 160 controls each component of the medical image processing device 1 in response to input operations received from the operator via the input interface 102. The processing circuit 160 functions as a medical image processing device according to this embodiment.

For example, the processing circuit 160 is implemented by a processor. As shown in Figure 1, the processing circuit 160 performs the following functions: three-dimensional CT volume data acquisition function 11, cross-sectional determination function 12, three-dimensional US volume data acquisition function 13, cross-sectional detection function 14, cross-sectional acquisition function 15, and registration function 16. Here, each processing function performed by the components of the processing circuit 160 shown in Figure 1—the three-dimensional CT volume data acquisition function 11, cross-sectional determination function 12, three-dimensional US volume data acquisition function 13, cross-sectional detection function 14, cross-sectional acquisition function 15, and registration function 16—is recorded in the storage circuit 150 of the medical image processing device 1 in the form of a program that can be executed by a computer. The processing circuit 160 is a processor that reads each program from the storage circuit 150 and executes it to realize the processing function corresponding to each program. In other words, the processing circuit 160 in the state where each program has been read will have the functions shown in the processing circuit 160 of Figure 1.

Next, we will explain the processing details of the three-dimensional CT volume data acquisition function 11, the cross-section determination function 12, the three-dimensional US volume data acquisition function 13, the cross-section detection function 14, the cross-section acquisition function 15, and the registration function 16, all of which are executed by the processing circuit 160.

The three-dimensional CT volume data acquisition function 11 acquires three-dimensional CT volume data of the examination site of the subject. Here, before performing an examination or treatment on the subject, in order to fully understand the condition of the examination site, it is usually necessary to acquire clear three-dimensional CT (computed tomography) volume data of the examination site with a good anatomical environment by performing a three-dimensional scan of the examination site. For example, the three-dimensional CT volume data acquisition function 11 acquires three-dimensional CT volume data by performing a CT scan on the examination site of the subject in advance. Specifically, the three-dimensional CT volume data acquisition function 11 is, for example, composed of memory and acquires three-dimensional CT volume data of the examination site of the subject by storing the three-dimensional CT volume data of the examination site of the subject generated by the X-ray CT device. Note that the three-dimensional CT volume data acquisition function 11 is an example of the first acquisition unit, and the three-dimensional CT volume data is an example of the first volume data.

Here, the examination site may be a single organ such as the heart, liver, or prostate, or it may be a single body part such as the abdomen including the liver.

The section determination function 12 determines the cross-section of the examination site of the subject. This cross-section is one of several representative anatomical planes of the examination site. Typically, there are multiple representative anatomical planes of the examination site. For example, if the examination site is the heart, the representative anatomical planes are the 4CH (chamber) plane, the 3CH plane, and the 2CH plane. If the examination site is the abdomen, the representative anatomical planes are the intercostal plane and the subcostal plane. Therefore, the section determination function 12 selects one cross-section from the multiple representative anatomical planes of the examination site and determines it as the cross-section of the examination site. Note that the section determination function 12 is an example of a section determination unit.

The three-dimensional US volume data acquisition function 13 acquires three-dimensional US volume data of the examination site of the subject. For example, when performing surgery on the examination site of a subject, US scanning of the examination site may be used to assist the surgery. When US (Ultra-Sonic; ultrasound) scanning is performed on the examination site, the three-dimensional US volume data acquisition function 13 acquires three-dimensional US volume data of the examination site of the subject. Note that the three-dimensional US volume data acquisition function 13 is an example of the second acquisition unit, and the three-dimensional US volume data is an example of the second volume data.

The cross-section detection function 14 automatically detects the cross-sections determined by the cross-section determination function 12 in the three-dimensional CT volume data. For example, the cross-section detection function 14 automatically detects the cross-sections determined by the cross-section determination function 12 based on multiple anatomical points in the three-dimensional CT volume data. A specific example of detecting cross-sections based on multiple anatomical points will be described later. Note that the cross-section detection function 14 is an example of a cross-section detection unit.

The cross-section acquisition function 15 acquires the cross-section determined by the cross-section determination function 12 in the three-dimensional US volume data. For example, if the cross-section detection function 14 detects a cross-section determined by the cross-section determination function 12 in the three-dimensional CT volume data, the cross-section acquisition function 15 can refer to that cross-section and find (acquire) a similar cross-section from the three-dimensional US volume data. The cross-section acquisition function 15 can also acquire the cross-section determined by the cross-section determination function 12 before the cross-section detection function 14 automatically detects it. In this case, the physician can find the cross-section determined by the cross-section determination function 12 by translating or rotating the US probe based on their experience, and then acquire that cross-section using the cross-section acquisition function 15. Note that the cross-section acquisition function 15 is an example of a cross-section acquisition unit.

The registration function 16 registers the three-dimensional CT volume data and three-dimensional US volume data of the inspection area based on the cross-sections detected by the cross-section detection function 14 in the three-dimensional CT volume data and the cross-sections acquired by the cross-section acquisition function 15 in the three-dimensional US volume data. Specifically, the registration function 16 uses the positions of the cross-sections detected by the cross-section detection function 14 in the three-dimensional CT volume data and the positions of the cross-sections acquired by the cross-section acquisition function 15 in the three-dimensional US volume data as registration reference positions to register the three-dimensional CT volume data and three-dimensional US volume data of the inspection area. Note that the registration function 16 is an example of a registration unit.

Furthermore, in the processing circuit 160, the cross-sectional acquisition function 15 may display the cross-sections in the three-dimensional CT volume data automatically detected by the cross-sectional detection function 14 on the display 103. The cross-sectional acquisition function 15 acquires the corresponding cross-sections in the three-dimensional US volume data based on the cross-sections in the three-dimensional CT volume data displayed on the display 103. Specifically, the physician (user) refers to the cross-sections in the three-dimensional CT volume data displayed on the display 103 and performs a US scan on the examination site of the subject. The cross-sectional acquisition function 15 then selects the cross-section with the highest similarity to the cross-section in the three-dimensional CT volume data from among multiple cross-sections in the three-dimensional US volume data acquired by the three-dimensional US volume data acquisition function 13 as the corresponding cross-section.

The registration process between the three-dimensional CT volume data and the three-dimensional US volume data of the inspection site will be explained below, with reference to Figure 2.

Step S1 in Figure 2 is a step in which the processing circuit 160 calls and executes a program corresponding to the three-dimensional CT volume data acquisition function 11 from the memory circuit 150. In step S1, the physician (user) performs a CT scan on the examination area of the subject, and the three-dimensional CT volume data acquisition function 11 acquires three-dimensional CT volume data of the examination area of the subject.

Step S2 in Figure 2 is a step in which the processing circuit 160 calls and executes a program corresponding to the cross-sectional determination function 12 from the memory circuit 150. In step S2, for the type of examination site, such as the heart, liver, prostate, or abdomen, the cross-sectional determination function 12 determines one representative anatomical plane in the examination site.

Step S3 in Figure 2 is a step in which the processing circuit 160 calls and executes a program corresponding to the cross-sectional detection function 14 from the memory circuit 150. In step S3, the cross-sectional detection function 14 automatically detects a representative anatomical plane of the inspection area determined in step S2, based on multiple anatomical points in the three-dimensional CT volume data acquired in step S1. The cross-sectional detection function 14 displays the detected anatomical plane on the display 103.

Step S4 in Figure 2 is a step in which the processing circuit 160 calls and executes programs corresponding to the three-dimensional US volume data acquisition function 13 and the cross-sectional acquisition function 15 from the memory circuit 150. In step S4, the physician performs a US scan on the examination site of the subject, and the three-dimensional US volume data acquisition function 13 acquires three-dimensional US volume data of the examination site. Then, the physician performs a US scan based on experience or by referring to the anatomical plane displayed on the display 103, and the cross-sectional acquisition function 15 acquires the anatomical plane (corresponding cross-section) corresponding to the anatomical plane detected in step S3. For example, if the anatomical plane detected in step S3 is the 4CH plane of the patient's (subject's) heart, then in step S4, the 4CH plane in the three-dimensional US volume data of the heart is acquired.

Step S5 in Figure 2 is a step in which the processing circuit 160 calls and executes a program corresponding to the registration function 16 from the storage circuit 150. In step S5, the registration function 16 registers the three-dimensional CT volume data and the three-dimensional US volume data based on the anatomical plane of the three-dimensional CT volume data detected in step S3 and the anatomical plane of the three-dimensional US volume data acquired in step S4.

In the example shown in Figure 2, first, in step S3, the cross-sectional detection function 14 automatically detects cross-sections in the three-dimensional CT volume data. Then, in step S4, the cross-sectional acquisition function 15 acquires the corresponding cross-sections in the three-dimensional US volume data. However, the order of processing in steps S3 and S4 can also be reversed. Specifically, in step S4, the physician performs a US scan on the examination site of the subject, using the representative anatomical planes of the examination site determined in step S2. The three-dimensional US volume data acquisition function 13 acquires three-dimensional US volume data of the examination site, and the cross-sectional acquisition function 15 acquires representative anatomical planes. Then, in step S3, the cross-sectional detection function 14 automatically detects the corresponding anatomical planes from the three-dimensional CT volume data acquired in step S1.

The registration process between three-dimensional CT volume data and three-dimensional US volume data will be specifically explained below, using the heart as an example, with reference to Figure 3. Here, steps S101, S102-S103, S104-S106, S107, and S108 in Figure 3 correspond to steps S1, S2, S3, S4, and S5 in Figure 2, respectively.

During cardiac surgery, the physician (user) needs to accurately determine the location of the lesion by performing a ultrasound (US) scan of the heart while simultaneously referring to the corresponding CT or MRI images. In this embodiment, the use of CT images will be explained as an example.

For example, before performing surgery on a patient's (subject's) heart, a physician needs to obtain clear three-dimensional CT volume data of the patient's heart by performing a CT scan on the patient's heart beforehand. Therefore, in step S101, the physician performs a CT scan on the examination area of the subject, and the three-dimensional CT volume data acquisition function 11 acquires three-dimensional CT volume data of the patient's heart.

Next, when a physician performs surgery on a patient's heart, before performing a ultrasound scan, they need to select a target ultrasound examination type from a list of ultrasound examination types, such as heart, prostate, or abdomen. Therefore, in step S102, the cross-sectional determination function 12 selects the target ultrasound examination type. Specifically, the cross-sectional determination function 12 displays a screen on the display 103 that accepts the selection of the target ultrasound examination type from the list of types such as heart, prostate, or abdomen. For example, in this embodiment, the physician selects the heart as the target ultrasound examination type.

Next, in step S103, if the physician selects the patient's heart, the section determination function 12 selects a target section from the candidate section list. Specifically, the section determination function 12 displays a candidate section list on the display 103 that accepts the selection of one representative anatomical plane from among several representative anatomical planes, such as the 4CH plane, 3CH plane, and 2CH plane. In this embodiment, the physician selects the 4CH plane, which can evaluate the cardiac contractility, from the candidate section list as one representative anatomical plane. In this case, the section determination function 12 determines the 4CH plane selected by the physician as the target section.

Next, in step S104, to locate the 4CH plane, the cross-sectional detection function 14 uses an existing image analysis algorithm to locate at least three anatomical points in the three-dimensional CT volume data of the patient's heart. Specifically, as shown in Figure 4, the cross-sectional detection function 14 locates the mitral valve point M, the apex point A, and the atrioventricular junction points J from the three-dimensional CT volume data. The mitral valve point M, the apex point A, and the atrioventricular junction points J are three anatomical points that are not located on the same straight line. In this embodiment, three anatomical points are given as an example of the anatomical points to be found, but for example, more than three anatomical points may be found. Also, in this embodiment, the anatomical points are found from a cross-section (plane) as an example, but for example, anatomical points may be found from a curved surface.

Next, in step S105, the cross-sectional detection function 14 calculates the long-axis vector V1 based on the positions of the mitral valve point M and the apex point A, and further calculates the short-axis vector V2 based on the long-axis vector V1 and the position of the atrioventricular junction point J.

Next, in step S106, the cross-sectional detection function 14 identifies cross-sections of the patient's heart's three-dimensional CT volume data based on the long-axis vector V1 and the short-axis vector V2, and detects the identified cross-sections as 4CH planes. The cross-sectional detection function 14 then displays the detected 4CH planes on the display 103. For example, the cross-sectional detection function 14 displays a 4CH plane as shown in Figure 5A on the display 103.

Next, in step S107, the physician performs a US scan of the patient's heart, and the three-dimensional US volume data acquisition function 13 acquires the three-dimensional US volume data of the patient's heart. Then, the physician performs a US scan referring to the 4CH plane in the three-dimensional CT volume data displayed on the display 103, and the cross-sectional acquisition function 15 displays a cross-section similar to the 4CH plane in the three-dimensional CT volume data from the three-dimensional US volume data acquired by the three-dimensional US volume data acquisition function 13 on the display 103. For example, the cross-sectional acquisition function 15 displays a cross-section similar to the 4CH plane in the three-dimensional CT volume data, as shown in Figure 5B, on the display 103. This allows the physician to find the cross-section corresponding to the 4CH plane in the three-dimensional CT volume data (corresponding cross-section), and the cross-sectional acquisition function 15 acquires the cross-section found by the physician as the 4CH plane in the three-dimensional US volume data.

Finally, in step S108, the registration function 16 registers the three-dimensional CT volume data and the three-dimensional US volume data based on the 4CH plane in the three-dimensional CT volume data and the 4CH plane in the three-dimensional US volume data.

As a result, the medical image processing device 1 according to the first embodiment can quickly find a clear CT image corresponding to a cross-section shown during ultrasound probe scanning when performing surgery on a patient's heart, thereby assisting the physician in making a quick and accurate decision and significantly improving surgical efficiency.

Furthermore, in the medical image processing device 1 according to the first embodiment, the major axis vector V1 and minor axis vector V2 are identified based on three anatomical points that are not located on the same straight line: the mitral valve point M, the apex point A, and the atrioventricular junction point J, in the three-dimensional CT volume data of the patient's heart. The 4CH plane in the three-dimensional CT volume data is then identified based on the major axis vector V1 and minor axis vector V2. Here, it is also possible to directly identify the 4CH plane in the three-dimensional CT volume data based on the three anatomical points that are not located on the same straight line: the mitral valve point M, the apex point A, and the atrioventricular junction point J; that is, the cross-section where these three anatomical points are located is identified as the 4CH plane in the three-dimensional CT volume data.

Furthermore, in the medical image processing device 1 according to the first embodiment, the 4CH plane in the automatically detected three-dimensional CT volume data is referenced, and a plane similar to the 4CH plane in the three-dimensional US volume data is searched for and designated as the 4CH plane in the three-dimensional US volume data. However, instead of referring to the automatically detected 4CH plane in the three-dimensional CT volume data, the physician can also search for the 4CH plane in the three-dimensional US volume data based on their own experience.

Furthermore, while the medical image processing device 1 according to the first embodiment was described as one in which three-dimensional CT volume data of the patient's heart is acquired in advance and then the acquired three-dimensional CT volume data and the patient's heart's three-dimensional US volume data are registered, the device is not limited to this. For example, since three-dimensional MR volume data also has a good anatomical environment and is clear three-dimensional volume data, it is also possible to acquire three-dimensional MR volume data of the patient's heart in advance and then register the acquired three-dimensional MR volume data and the heart's three-dimensional US volume data.

(Second Embodiment)
A second embodiment of the medical image processing device 1 will be described below with reference to Figure 6. In Figure 6, the registration process between three-dimensional CT volume data and three-dimensional US volume data will be explained using the heart as an example.

In the second embodiment, the description of parts identical to those in the first embodiment will be omitted. Steps S201 to S208 in the second embodiment are identical to steps S101 to S108 in the first embodiment, and therefore their description will be omitted. In the medical image processing apparatus 1 according to the second embodiment, point cloud registration is performed using a registration algorithm.

In step S209, the registration function 16 initializes the registration parameters in the registration algorithm using the information of the mitral valve point M, apex point A, and atrioventricular junction point J found in step S204.

In step S210, the registration function 16 executes a registration algorithm and calculates the similarity of corresponding points between the three-dimensional CT volume data and the three-dimensional US volume data, assigning additional weights to points located near the mitral valve point M, the apex point A, and the atrioventricular junction point J in the three-dimensional CT volume data and the three-dimensional US volume data.

In step S211, the registration function 16 outputs a conversion matrix between the three-dimensional CT volume data and the three-dimensional US volume data, and further registers the three-dimensional CT volume data and the three-dimensional US volume data using this conversion matrix.

Thus, in the medical image processing device 1 according to the second embodiment, additional weights are assigned to points located near the mitral valve point M, the apex point A, and the atrioventricular junction point J in the three-dimensional CT volume data and the three-dimensional US volume data. That is, in the medical image processing device 1 according to the second embodiment, points located near these three points in the three-dimensional CT volume data and the three-dimensional US volume data are given higher weights than other points. As a result, the medical image processing device 1 according to the second embodiment calculates the similarity of corresponding points between the three-dimensional CT volume data and the three-dimensional US volume data, and by improving the accuracy of the registration algorithm, accurate registration between the three-dimensional CT volume data and the three-dimensional US volume data can be achieved.

The medical image processing apparatus 1 according to the first and second embodiments is not limited to the forms described above. For example, the processing circuit 160 may be a workstation installed separately from the medical image processing apparatus 1. In this case, the workstation has a processing circuit similar to that of the processing circuit 160 and performs the processing described above.

Furthermore, for example, the medical image processing device 1 may be incorporated into a medical imaging diagnostic device that generates three-dimensional CT volume data or three-dimensional MR volume data of the examination site of a subject. The medical imaging diagnostic device includes, for example, an X-ray CT scanner, a magnetic resonance imaging (MRI) scanner, etc. For example, if the medical image processing device 1 is incorporated into an X-ray CT scanner, the processing circuit 160 of the X-ray CT scanner includes a three-dimensional CT volume data acquisition function 11 that acquires three-dimensional CT volume data generated within the medical imaging diagnostic device, and a three-dimensional US volume data acquisition function 13 that acquires three-dimensional US volume data generated by an ultrasound diagnostic device.

(Third Embodiment)
The processing circuit 160, which is a medical image processing apparatus according to the first and second embodiments, may be provided in an ultrasound diagnostic apparatus.

Figure 7 is a block diagram showing the configuration of the ultrasound diagnostic apparatus 2 according to the third embodiment. As shown in Figure 7, the ultrasound diagnostic apparatus 2 in the third embodiment includes a main body 200, an ultrasound probe 201, an input device 202, and a display 203. The ultrasound probe 201, the input device 202, and the display 203 are connected to the main body 200.

The ultrasonic probe 201 has multiple transducers (e.g., piezoelectric transducers), which generate ultrasonic waves based on drive signals supplied from a transmitting/receiving circuit 210 in the main body 200 (described later). The transducers of the ultrasonic probe 201 also receive reflected waves from the subject P and convert them into electrical signals. Furthermore, the ultrasonic probe 201 has a matching layer provided on the transducers and a backing material to prevent the propagation of ultrasonic waves backward from the transducers. A magnetic sensor is also attached to the ultrasonic probe 201 to acquire its positional information.

The input device 202 includes an input device that can be operated by the operator and an input circuit that receives signals from the input device. The input device can be implemented as a tracking ball, switch, mouse, keyboard, touch panel (which allows input by touching the operating surface), touchscreen (which integrates a display screen and a touch panel), non-contact input device using an optical sensor, or voice input device. When the input device is operated by the operator, the input circuit generates a signal corresponding to that operation and outputs it to the processing circuit.

The display 203 is implemented using a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, a touch panel, etc. The display 203 displays a GUI (Graphical User Interface) for the operator of the ultrasound diagnostic device 2 to input various setting requests using the input device 202, and also displays US (ultrasound) image data generated by the device body 200. The display 203 is an example of a display unit.

The main unit 200 is a device that generates US image data based on the reflected wave signal received by the ultrasonic probe 201. As shown in Figure 7, it includes a transmitting/receiving circuit 210, a signal processing circuit 220, an image generation circuit 230, an image memory 240, a storage circuit 250, and a processing circuit 260. The transmitting/receiving circuit 210, the signal processing circuit 220, the image generation circuit 230, the image memory 240, the storage circuit 250, and the processing circuit 260 are interconnected and can communicate with each other.

The transmitting/receiving circuit 210 controls the transmission of ultrasound by the ultrasound probe 201. For example, based on instructions from the processing circuit 260, the transmitting/receiving circuit 210 applies the aforementioned drive signal (drive pulse) to the ultrasound probe 201 at a timing that includes a predetermined transmission delay time for each transducer. This causes the transmitting/receiving circuit 210 to transmit an ultrasound beam, which is focused into a beam, to the ultrasound probe 201. The transmitting/receiving circuit 210 also controls the reception of the reflected wave signal by the ultrasound probe 201. As described above, the reflected wave signal is the signal obtained when the ultrasound transmitted from the ultrasound probe 201 is reflected by the body tissue of the subject P. For example, based on instructions from the processing circuit 260, the transmitting/receiving circuit 210 adds the reflected wave signal received by the ultrasound probe 201 after applying a predetermined delay time. This emphasizes the reflected component from the direction corresponding to the reception directivity of the reflected wave signal.

The signal processing circuit 220 performs various signal processing on the reflected wave signal received by the transmitting/receiving circuit 210. For example, by performing various signal processing on the reflected wave signal, the signal processing circuit 220 generates data (B-mode data) in which the signal intensity for each sample point (observation point) is represented by brightness. Furthermore, the signal processing circuit 220 generates data (Doppler data) in which motion information based on the Doppler effect of a moving object is extracted at each sample point within the scanning area.

The image generation circuit 230 generates image data (US images) from data that has undergone various signal processing by the signal processing circuit 220, and performs various image processing on the US images. For example, the image generation circuit 230 generates a two-dimensional US image from two-dimensional (2D) B-mode data, representing the intensity of reflected waves as brightness. The image generation circuit 230 also generates a two-dimensional US image from two-dimensional Doppler data, visualizing blood flow information.

Here, the image generation circuit 230 generates a display-ready US image by performing coordinate transformations according to the ultrasonic scanning mode of the ultrasonic probe 201. For example, the B-mode data and Doppler data are US image data before scan-conversion processing, and the data generated by the image processing circuit 240 is the display-ready US image data after scan-conversion processing. In other words, the image generation circuit 230 generates a two-dimensional display-ready US image data from the two-dimensional US image data before scan-conversion processing. Furthermore, the image generation circuit 230 generates a three-dimensional US image by performing coordinate transformations on the three-dimensional (3D) B-mode data generated by the signal processing circuit 220. Also, the image generation circuit 230 generates a three-dimensional US image by performing coordinate transformations on the three-dimensional Doppler data generated by the signal processing circuit 120. Furthermore, the image generation circuit 230 performs rendering processing on the volume data in order to generate various two-dimensional US images for displaying the volume data on the display 203.

The image generation circuit 230 stores the US image and the US image after various image processing steps in the image memory 240. The image memory 240 and the storage circuit 250 are, for example, semiconductor memory elements such as RAM (Random Access Memory) and flash memory, or storage devices such as hard disks and optical discs.

The processing circuit 260 controls the entire processing of the ultrasound diagnostic device 2. Specifically, the processing circuit 260 controls the processing of the transmitting/receiving circuit 210, signal processing circuit 220, image generation circuit 230, and image memory 240 based on various setting requests input from the operator via the input device 202, and various control programs and data read from the memory circuit 250. The processing circuit 260 controls the display to show the display 203 either the display-ready US image generated by the image generation circuit 230 or the display-ready US image stored in the image memory 240.

For example, the processing circuit 260 is implemented by a processor. As shown in Figure 8, the processing circuit 260 performs a three-dimensional CT volume data acquisition function 11, a cross-sectional determination function 12, a three-dimensional US volume data acquisition function 13, a cross-sectional detection function 14, a cross-sectional acquisition function 15, and a registration function 16. The three-dimensional CT volume data acquisition function 11, the cross-sectional determination function 12, the three-dimensional US volume data acquisition function 13, the cross-sectional detection function 14, the cross-sectional acquisition function 15, and the registration function 16 of the processing circuit 160 in Figure 1, respectively. That is, the ultrasound diagnostic device 2 is equipped with a processing circuit 260 corresponding to the processing circuit 160 in Figure 1, and acquires three-dimensional US volume data using an ultrasound probe 201.

In the above description, the term "processor" refers to circuits such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), Application Specific Integrated Circuit (ASIC), and programmable logic device (e.g., Simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD), and Field Programmable Gate Array (FPGA)). When the processor is a CPU, for example, it functions by reading and executing a program stored in the memory circuit 150 in Figure 1 or the memory circuit 250 in Figure 7. On the other hand, when the processor is an ASIC, for example, instead of storing the program in the memory circuit 150 in Figure 1 or the memory circuit 250 in Figure 7, the program is directly incorporated into the processor's circuit. Note that each processor in this embodiment is not limited to being configured as a single circuit; multiple independent circuits may be combined to form a single processor and realize its functions. Furthermore, the multiple components shown in Figures 1 and 7 may be integrated into a single processor to realize their functions.

The components of each device illustrated in the above-described embodiments are functional concepts and do not necessarily need to be physically configured as shown. That is, the specific forms of distribution and integration of each device are not limited to those illustrated; all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads and usage conditions. Furthermore, each processing function performed by each device can be implemented, in whole or in any part, by a CPU and the program executed by that CPU, or by wired logic hardware.

Furthermore, the processing method (medical image processing method) described in the above embodiment can be implemented by executing a pre-prepared program on a computer such as a personal computer or workstation. This program can be distributed via a network such as the Internet. Alternatively, this program can be recorded on a computer-readable non-temporary recording medium such as a hard disk, flexible disk (FD), CD-ROM, MO, or DVD, and executed by reading it from the recording medium by a computer.

According to at least one embodiment described above, registration can be performed in a short time.

While several embodiments have been described, these embodiments are provided as examples only and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included within the scope and spirit of the invention, as well as within the scope of the invention described in the technical proposal and its equivalents.

11 Three-dimensional CT volume data acquisition function 12 Cross section determination function 13 Three-dimensional US volume data acquisition function 14 Cross section detection function 15 Cross section acquisition function 16 Registration function 160 Processing circuit

Claims (9)

A first acquisition unit that acquires first volume data of the examination site of the subject,
A section determination unit that determines the cross-section of the inspection area,
A second acquisition unit that acquires second volume data of the examination site of the subject,
A cross-section detection unit that automatically detects multiple anatomical points that are not located on the same straight line from the first volume data, and automatically detects the cross-sections where the multiple anatomical points are located as the cross-sections in the first volume data,
A cross-section acquisition unit that acquires the cross-section in the second volume data,
Based on the cross-section in the first volume data and the cross-section in the second volume data, the first volume data and the second volume data are registered.
Using the information from the aforementioned multiple anatomical points, the registration parameters in the registration algorithm used for registering the point cloud are initialized.
The similarity between the first volume data and the second volume data is calculated so that additional weights are assigned to points located near the plurality of anatomical points in the first volume data and the second volume data, and a matrix for registering the point cloud is output.
A registration unit that further registers the first volume data and the second volume data using the matrix ,
A medical image processing device equipped with [a specific feature]. The cross-section determination unit selects one cross-section from a plurality of representative anatomical planes of the inspection site and determines it to be the cross-section of the inspection site.
The medical image processing apparatus according to claim 1. The cross-section detection unit automatically detects at least three anatomical points as the plurality of anatomical points , and sets the cross-section in which the at least three anatomical points are located as the cross-section in the first volume data.
The medical image processing apparatus according to claim 2. The system further includes a display unit that displays the cross-section in the first volume data,
The cross-section acquisition unit acquires the cross-section in the second volume data based on the cross-section in the displayed first volume data.
A medical image processing apparatus according to any one of claims 1 to 3 . The first volume data is three-dimensional CT volume data or three-dimensional MR volume data.
The aforementioned second volume data is three-dimensional US volume data.
A medical image processing apparatus according to any one of claims 1 to 4 . A medical image processing apparatus according to any one of claims 1 to 5 ,
A medical imaging diagnostic device equipped with [a specific feature]. The medical image processing apparatus according to claim 5 , wherein the second volume data is acquired using an ultrasound probe,
Ultrasound diagnostic equipment. First volume data of the examination site of the subject is obtained.
Determine the cross-section at the aforementioned inspection site,
The second volume data of the examination site of the subject is acquired,
The system automatically detects multiple anatomical points that are not located on the same straight line from the first volume data, and automatically detects the cross-sections where the multiple anatomical points are located as the cross-sections in the first volume data.
The cross-section in the second volume data is obtained,
Based on the cross-section in the first volume data and the cross-section in the second volume data, the first volume data and the second volume data are registered.
Using the information from the aforementioned multiple anatomical points, the registration parameters in the registration algorithm used for registering the point cloud are initialized.
The similarity between the first volume data and the second volume data is calculated so that additional weights are assigned to points located near the plurality of anatomical points in the first volume data and the second volume data, and a matrix for registering the point cloud is output.
The first volume data and the second volume data are further registered using the matrix .
A medical image processing method that includes the following. First volume data of the examination site of the subject is obtained.
Determine the cross-section at the aforementioned inspection site,
The second volume data of the examination site of the subject is acquired,
The system automatically detects multiple anatomical points that are not located on the same straight line from the first volume data, and automatically detects the cross-sections where the multiple anatomical points are located as the cross-sections in the first volume data.
The cross-section in the second volume data is obtained,
Based on the cross-section in the first volume data and the cross-section in the second volume data, the first volume data and the second volume data are registered.
Using the information from the aforementioned multiple anatomical points, the registration parameters in the registration algorithm used for registering the point cloud are initialized.
The similarity between the first volume data and the second volume data is calculated so that additional weights are assigned to points located near the plurality of anatomical points in the first volume data and the second volume data, and a matrix for registering the point cloud is output.
The first volume data and the second volume data are further registered using the matrix .
A medical image processing program that uses a computer to perform the processing.