Medical image processing apparatus, X-ray diagnostic apparatus, medical image processing method, and medical image processing program

Abstract

To reduce artifacts caused by differences in the sensitivity of X-ray detectors. [Solution] The medical image processing apparatus according to this embodiment includes: an acquisition unit that acquires a plurality of projection data corresponding to a plurality of rotation angles based on output signals from a plurality of X-ray detection elements in an X-ray detector that rotates around a rotation axis around a subject; a filter averaging unit that applies a reconstruction filter to each of the plurality of projection data and generates a first averaged image by averaging the plurality of projection data to which the reconstruction filter has been applied; a region setting unit that sets regions in the plurality of X-ray detection elements in which the X-ray sensitivity is relatively high based on the first averaged image; a correction unit that performs a correction process for the difference in sensitivity inside and outside the region in each of the plurality of projection data multiple times with different correction amounts; and a reconstruction unit that performs a reconstruction process accompanied by the execution of the reconstruction filter based on the corrected plurality of projection data.

Description

Technical Field

[0001] The embodiments disclosed in this specification and the drawings relate to a medical image processing apparatus, an X-ray diagnostic apparatus, a medical image processing method, and a medical image processing program.

Background Art

[0002] Conventionally, an X-ray diagnostic apparatus includes an X-ray detector that detects X-rays. When a part of the X-ray detector is continuously irradiated with X-rays, the sensitivity of the X-rays in the irradiated part may change. Then, when the X-ray diagnostic apparatus reconstructs a three-dimensional volume image using the projection data generated in a state where the X-ray sensitivity of the X-ray detector has changed, a ring artifact may occur.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to reduce artifacts due to sensitivity differences in the X-ray detector. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problems. The problems corresponding to the respective effects of each configuration shown in the embodiments described later can also be regarded as other problems.

Means for Solving the Problems

[0005] The medical image processing apparatus according to this embodiment includes an acquisition unit, a filter averaging unit, a region setting unit, a correction unit, and a reconstruction unit. The acquisition unit acquires multiple projection data corresponding to multiple rotation angles based on output signals from multiple X-ray detection elements in an X-ray detector that rotates around a rotation axis around a subject. The filter averaging unit applies a reconstruction filter to each of the multiple projection data and generates a first averaged image by averaging the multiple projection data to which the reconstruction filter has been applied. The region setting unit sets regions in the multiple X-ray detection elements where the X-ray sensitivity is relatively high based on the first averaged image. The correction unit performs a correction process for the region in each of the multiple projection data, correcting the difference in sensitivity inside and outside the region multiple times with different correction amounts. The reconstruction unit performs a reconstruction process, including the execution of the reconstruction filter, based on the corrected multiple projection data. [Brief explanation of the drawing]

[0006] [Figure 1] Figure 1 shows an example of the configuration of an X-ray diagnostic apparatus according to an embodiment. [Figure 2] Figure 2 shows an example of a 3D volume image with ring artifacts. [Figure 3] Figure 3 shows an example of a first averaged image obtained by averaging processing according to an embodiment. [Figure 4] Figure 4 is a diagram showing an example of a profile representing the signal value (pixel value) of each pixel in the search region E1 shown in Figure 3, relating to an embodiment. [Figure 5] Figure 5 shows an example of the mask position relative to the first averaged image, relating to an embodiment. [Figure 6] Figure 6 shows an example of a profile in the second averaged image according to an embodiment. [Figure 7] Figure 7 is a flowchart showing an example of the procedure for projection data correction processing according to the embodiment. [Figure 8]Figure 8 shows an example of an embodiment, illustrating the reconstructed image before correction, a reconstructed image with overcorrection as a comparative example, and the reconstructed image generated by this embodiment. [Figure 9] Figure 9 is a diagram illustrating an embodiment, showing an example of a reconstructed image before correction, a reconstructed image as a comparative example, and a reconstructed image generated by this embodiment. [Figure 10] Figure 10 illustrates an example of an application of the embodiment, showing a predetermined range in the first averaged image and an average profile calculated based on that predetermined range. [Figure 11] Figure 11 illustrates an example of an application of the embodiment, showing a first averaged image and two profiles selected from a plurality of profiles. [Modes for carrying out the invention]

[0007] Hereinafter, with reference to the drawings, a medical image processing apparatus, an X-ray diagnostic apparatus, a medical image processing method, and a medical image processing program according to this embodiment will be described. In the following embodiments, parts with the same reference numerals perform similar operations, and redundant explanations will be omitted as appropriate.

[0008] Furthermore, in the following description, the medical image processing device is assumed to be mounted on an X-ray diagnostic device, and the X-ray diagnostic device will be described accordingly. However, the embodiments relating to this application are not limited thereto. For example, the medical image processing device may be implemented as a server device in a picture archiving and communication system (PACS), a radiology information system (RIS), or a server device connected to a hospital information system (HIS).

[0009] Furthermore, medical image processing devices are not limited to those mounted on X-ray diagnostic equipment, but may also be mounted on nuclear medicine diagnostic equipment such as X-ray computed tomography (X-ray CT) devices, positron emission tomography (PET) and single-photon emission computed tomography (SPECT) devices, and combined nuclear medicine diagnostic equipment and X-ray CT devices (PET-CT devices, SPECT-CT devices).

[0010] (Embodiment) Figure 1 is a diagram showing an example of the configuration of an X-ray diagnostic apparatus 1 according to an embodiment. In the following description, for the sake of detail, the X-ray diagnostic apparatus 1 will be described as an X-ray angiography apparatus. The X-ray diagnostic apparatus 1 comprises an imaging unit 3, a patient table 5, a drive unit 7, an operation unit 9, an X-ray high-voltage device 11, and a medical image processing device 100. The medical image processing device 100 comprises a memory circuit 21, a display unit 23, an input interface 25, and a processing circuit 27.

[0011] The imaging unit 3 comprises an X-ray tube 13 for irradiating the subject P (object) with X-rays, an X-ray detector 17 for detecting X-rays, an X-ray diaphragm 15, and a support device 19. The imaging unit 3 is supported by the support device 19. The patient bed 5 includes an operating unit 9 for operating the imaging unit 3 and the patient bed 5. The imaging unit 3 may also be referred to as the imaging system. The configuration of the operating unit 9 is the same as that of the input interface 25 described later, so its explanation is omitted.

[0012] The drive unit 7 drives the imaging unit 3 and the patient bed 5. The drive unit 7 also includes an imaging system movement drive unit 71 and a tabletop movement drive unit 73. The imaging system movement drive unit 71 drives the imaging unit 3 to move the imaging system, including the X-ray tube 13 and X-ray detector 17, in a desired direction under the control of the processing circuit 27. The imaging system movement drive unit 71 is provided on the support device 19 for each of the multiple support members that support the multiple components to be moved. The tabletop movement drive unit 73 drives the patient bed 5 to move the tabletop 51 in a desired direction under the control of the processing circuit 27. The tabletop movement drive unit 73 is provided on the patient bed 5, for example. The imaging system movement drive unit 71 and the tabletop movement drive unit 73 are implemented by motors and / or actuators.

[0013] The X-ray high-voltage device 11 includes an electrical circuit such as a transformer and a rectifier, a high-voltage generator, and an X-ray control device. The high-voltage generator has the function of generating the high voltage applied to the X-ray tube 13 and the filament current supplied to the X-ray tube 13. The X-ray control device controls the output voltage according to the X-rays irradiated by the X-ray tube 13. The high-voltage generator may be of the transformer type or the inverter type. The X-ray high-voltage device 11 may be installed on the support device 19.

[0014] The X-ray tube 13 is a vacuum tube that generates X-rays by irradiating thermionic electrons from the cathode (filament) to the anode (target) by applying a high voltage from the X-ray high-voltage device 11 and supplying filament current. X-rays are generated when thermionic electrons collide with the target. For example, the X-ray tube 13 includes a rotating anode type X-ray tube that generates X-rays by irradiating a rotating anode with thermionic electrons. However, the X-ray tube 13 is not limited to the rotating anode type, and any type of X-ray tube can be applied.

[0015] The X-ray aperture 15 is provided in front of the X-ray emission window in the X-ray tube 13. The X-ray aperture 15 has, for example, four aperture blades made of a metal plate such as lead. The aperture blades are driven by a drive device (not shown) according to the region of interest input by the operator via the operation unit 9 and the input interface 25. The X-ray aperture 15 adjusts the size of the region where the X-ray is shielded to an arbitrary size by sliding these aperture blades by the drive device. With the adjusted aperture blades, the X-ray aperture 15 shields the X-rays outside the opening region. Thereby, the X-ray aperture 15 narrows down the X-rays generated by the X-ray tube 13 so as to irradiate the region of interest of the subject P.

[0016] The X-ray detector 17 detects the X-rays generated by the X-ray tube 13. The X-ray detector 17 is, for example, a flat panel detector (hereinafter referred to as FPD). The FPD has a plurality of semiconductor detection elements (X-ray detection elements). That is, the X-ray detector 17 has a plurality of X-ray detection elements. The semiconductor detection element has a direct conversion method that directly converts X-rays into electrical signals and an indirect conversion method that converts X-rays into light with a phosphor and then converts the light into electrical signals. Either method may be used for the FPD.

[0017] The electrical signals generated in the plurality of semiconductor detection elements with the incidence of X-rays are output to an analog-to-digital converter (hereinafter referred to as A / D converter) not shown. The A / D converter converts the electrical signals into digital data. The A / D converter outputs the digital data to the processing circuit 27. Note that an image intensifier may be used as the X-ray detector 17.

[0018] The support device 19 is a C-arm that holds the X-ray tube 13 and the X-ray aperture 15 and the X-ray detector 17 so as to face each other with the subject P interposed therebetween. The support device 19 is rotated by a motor (not shown) around the subject P lying horizontally on the bed 5. Here, the support device 19 is supported so as to be rotatable with respect to the XYZ axes, which are three orthogonal axes, and is rotated around each axis by a drive unit (not shown). By the support device 19, the X-ray detector 17 rotates around the periphery of the subject P, for example, around the rotation axis (Y axis).

[0019] The storage circuit 21 is a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an integrated circuit storage device that stores various information. The storage circuit 21 may be referred to as a memory. The storage circuit 21 stores, for example, projection data, image data, and programs corresponding to various functions read out and executed by the processing circuit 27. In addition to HDDs, SSDs, etc., the storage circuit 21 may be a drive device that reads and writes various information to and from portable storage media such as CDs (Compact Discs), DVDs (Digital Versatile Discs), flash memories, and semiconductor memory elements such as RAMs (Random Access Memories). Further, the storage area of the storage circuit 21 may be in an external storage device connected by a network.

[0020] The display unit 23 is composed of a display 231 that displays medical images and the like, an internal circuit that supplies a display signal to the display 231, and peripheral circuits such as connectors and cables that connect the display 231 and the internal circuit. The internal circuit generates display data by superimposing additional information such as subject information and projection data generation conditions on the image data. Next, the internal circuit performs D / A conversion and TV format conversion on the obtained display data. The internal circuit displays the display data on which these conversions have been performed on the display 231 as a medical image. In addition to this, the display unit 23 displays a GUI (Graphical User Interface) or the like for receiving various operations from the operator.

[0021] As the display 231, for example, a liquid crystal display (LCD), a cathode ray tube (CRT) display, an organic electroluminescent display (OELD), a plasma display, or any other display can be used as appropriate. Furthermore, the display 231 may be a desktop type, or it may be composed of a tablet terminal or the like that which can communicate wirelessly with the processing circuit 27.

[0022] The input interface 25 receives various input operations from the operator, converts the received input operations into electrical signals, and outputs them to the processing circuit 27. For example, the input interface 25 receives from the operator operations to operate at least one of the imaging unit 3 and the patient table 5, X-ray conditions related to X-ray generation, and conditions related to image processing performed by the image processing function 270. The input interface 25 can be appropriately configured to include, for example, a mouse, keyboard, trackball, switch, button, joystick, foot switch, touchpad, and touch panel display. While the input interface 25 is shown mounted on the medical image processing device 100 in Figure 1, it may also be mounted on a console device installed in a separate control room from the examination room.

[0023] In this embodiment, the input interface 25 is not limited to those comprising physical operating components such as a mouse, keyboard, trackball, switch, button, joystick, touchpad, and touch panel display. For example, an electrical signal processing circuit that receives electrical signals corresponding to input operations from an external input device provided separately from the device and outputs these electrical signals to the processing circuit 27 is also included as an example of the input interface 25. The input interface 25 may also consist of a tablet terminal or the like that can communicate wirelessly with the processing circuit 27. The input interface 25 may also be referred to as the input unit. The input interface 25, composed of the above operating components, may be installed on the bed 5 as an operation unit 9.

[0024] The processing circuit 27 controls the operation of the entire X-ray diagnostic apparatus 1. The processing circuit 27 has, for example, an image processing function 270. The image processing function 270 has an acquisition function 271, a filter averaging function 272, a region setting function 273, a correction information generation function 274, a correction function 275, a judgment function 276, and a reconstruction function 277. In this embodiment, each processing function performed by the image processing function 270 is stored in the storage circuit 21 in the form of a program that can be executed by a computer. The processing circuit 27 is a processor that reads programs from the storage circuit 21 and executes them to realize the functions corresponding to each program. In other words, the processing circuit 27 in the state in which each program has been read has the functions shown in the processing circuit 27 of Figure 1.

[0025] In Figure 1, the image processing function 270 is explained as being implemented by a single processor. However, it is also possible to configure a processing circuit 27 by combining multiple independent processors, and each processor executes a program to implement the various functions included in the image processing function 270. Furthermore, in Figure 1, a single memory circuit such as the memory circuit 21 is explained as storing the program corresponding to each processing function. However, it is also possible to configure the processing circuit 27 by distributing multiple memory circuits and reading the corresponding program from each individual memory circuit.

[0026] In the above explanation, the term "processor" refers to circuits such as CPUs (Central Processing Units), GPUs (Graphical Processing Units), Application Specific Integrated Circuits (ASICs), and Programmable Logic Devices (e.g., Simple Programmable Logic Devices (SPLDs), Complex Programmable Logic Devices (CPLDs), and Field Programmable Gate Arrays (FPGAs)).

[0027] The processor performs its functions by reading and executing the program stored in the memory circuit 21. Alternatively, instead of storing the program in the memory circuit 21, the processor may be configured to directly incorporate the program into its own circuitry. In this case, the processor performs its functions by reading and executing the program incorporated into the circuitry.

[0028] In this configuration, the X-ray diagnostic device 1 generates projection data based on the X-ray detection results from the X-ray detector 17. The X-ray diagnostic device 1 also reconstructs volume data from the projection data collected by the X-ray detector 17, which is supported by the support device 19, while rotating around the subject P. The volume data is also called a three-dimensional volume image. The three-dimensional volume image is generated by reconstructing multiple projection data corresponding to multiple rotation angles using computed tomography (CT) technology. This reconstruction corresponds to the CBCT (Corn Beam Computed Tomography) function. Since each of the multiple projection data has signal values ​​from each of the multiple X-ray detection elements in the X-ray detector 17, it may also be called a projection dataset.

[0029] When the X-ray detector 17 is continuously irradiated with X-rays over a certain period of time, the sensitivity of the X-ray detector 17 in detecting X-rays in the irradiated area may change. In other words, a difference in X-ray detection sensitivity (sensitivity difference) may occur between the area that has been continuously irradiated with X-rays over a certain period of time (hereinafter referred to as the continuously irradiated area) and other areas that are not the continuously irradiated area.

[0030] When a three-dimensional volume image is reconstructed using projection data based on the detection results of X-ray detectors 17 with different sensitivities, artifacts such as ring artifacts appear in the three-dimensional volume image. Figure 2 shows an example of a three-dimensional volume image with ring artifacts. Figure 2(a) is a cross-sectional image of a plane perpendicular to the body axis of the subject. Figure 2(b) is a cross-sectional image of the coronal plane of the subject.

[0031] As shown in Figures 2(a) and (b), the 3D volume image exhibits cylindrical artifacts A1. Therefore, the X-ray diagnostic device 1 in this embodiment aims to suppress artifacts caused by sensitivity differences through the following functions.

[0032] The processing circuit 27, using the acquisition function 271, acquires multiple projection data corresponding to multiple rotation angles based on output signals from multiple X-ray detection elements in the X-ray detector 17, which rotates around the subject P on a rotation axis. As shown in Figure 1, in the CBCT function, the rotation axis of the X-ray detector 17, which rotates around the subject P, is parallel to the Y-axis, i.e., it corresponds to the body axis direction of the subject P. The acquisition function 271 associates multiple rotation angles with multiple projection data and stores them in the memory circuit 21. The processing circuit 27 that implements the acquisition function 271 corresponds to the acquisition unit.

[0033] The processing circuit 27, specifically the filter averaging function 272, applies a reconstruction filter to each of the multiple projection data. The reconstruction filter is, for example, a Ramp filter (a filter using the Ramp function) or a Shepp & Logan filter, used in the filtered back projection (FBP) method. Furthermore, the reconstruction filter has the effect of emphasizing the high-frequency components of the projection data in the reconstruction process that generates 3D volume data from multiple projection data. For example, the reconstruction filter corresponds to the same reconstruction function used in the reconstruction process executed by the reconstruction function 277 described later.

[0034] Furthermore, the reconstruction filter is not limited to the filter used in reconstruction using the FBP method, but may be a reconstruction filter used in any reconstruction method. The filter averaging function 272 to which the reconstruction filter is applied may also be called the filter processing unit.

[0035] By applying a reconstruction filter to each of the multiple projection data sets, regions with relatively high X-ray sensitivity (hereinafter referred to as high-sensitivity regions) are emphasized in each of the multiple projection data sets. For example, the projection data immediately before the reconstruction filter is applied is obtained by taking the logarithm of the result (I / I0) obtained by dividing the output signal (X-ray intensity) I transmitted through the subject P by the output signal acquired without the subject P (air output signal (X-ray intensity)) I0, and then adding a negative value (-log(I / I0)). In other words, the projection data immediately before the reconstruction filter is applied has been pre-processed by -log(I / I0). Therefore, areas with high pixel values ​​(high sensitivity) in the image before logarithmic transformation (log transformation) will have lower values ​​in the image after logarithmic transformation and will appear as black in the image. After the reconstruction filter is applied, the differences in X-ray sensitivity in each of the multiple X-ray detection elements in the X-ray detector 17 are emphasized in the multiple projection data sets collected by the acquisition function 271. The high-sensitivity region corresponds to the output signal from the X-ray detection element in the continuously irradiated area among the multiple X-ray detection elements. In other words, the high-sensitivity region corresponds to the area where the signal value becomes abnormally high compared to the output signal from the X-ray detection element in a different area from the continuously irradiated area due to the difference in sensitivity.

[0036] Furthermore, the filter averaging function 272 performs an averaging process on multiple projection data to which reconstruction filtering has been applied. That is, the filter averaging function 272 generates an averaged image by averaging multiple projection data to which reconstruction filtering has been applied. The averaged image generated based on multiple projection data before correction is called the first averaged image. Averaging is a process that averages the signals of each pixel based on the detection results of the same detection element in multiple projection data. Specifically, the filter averaging function 272 generates an averaged image by performing additive averaging on multiple projection data to which reconstruction filtering has been applied.

[0037] As a result, in multiple projection data, the signals of each pixel will have different values, but they are averaged out by the averaging process. The high-sensitivity region is generated by the sensitivity difference between the multiple X-ray detection elements of the X-ray detector 17, and therefore appears at the same position in the projection data. For this reason, the high-sensitivity region is emphasized by the averaging process, which equalizes the signal values. The processing circuit 27 that realizes the filter averaging function 272 corresponds to the filter averaging unit. Note that the processing content in the filter averaging function 272 may be divided into a filter function that applies a reconstruction filter and an averaging function that performs averaging processing. In this case, the processing circuit 27 that realizes the filter function corresponds to the filter unit, and the processing circuit 27 that realizes the averaging function corresponds to the averaging unit.

[0038] The region setting function 273 sets regions with relatively high X-ray sensitivity (high-sensitivity regions) in multiple X-ray detection elements based on the first averaged image. In other words, the region setting function 273 detects high-sensitivity regions based on the processing results of the averaging process performed on multiple projection data. The processing circuit 27 that implements the region setting function 273 corresponds to the region setting unit.

[0039] Figure 3 shows an example of the first averaged image ARI resulting from the averaging process. As shown in Figure 3, the region setting function 273 sets a search region E1 for the first averaged image ARI resulting from the averaging process. The search region E1 is the region for which the region setting function 273 searches for a range to define a high-sensitivity region (hereinafter referred to as the high-sensitivity range). In Figure 3, the search region E1 is set to include the central part of the first averaged image ARI, but is not limited to this.

[0040] Figure 4 shows an example of a profile showing the signal value (pixel value) of each pixel in the search region E1 shown in Figure 3. When the search region E1 includes the high-sensitivity range HSR, the signal value of each pixel in the high-sensitivity range HSR is relatively more sensitive (there is a sensitivity difference) compared to the signal value of areas outside the high-sensitivity range HSR. Specifically, the region setting function 273 performs edge detection processing or change point detection processing in the profile of the search region E1 of the first averaged image.

[0041] The edge detection process detects edges that indicate the boundary between the high-sensitivity range HSR and the region outside the high-sensitivity range HSR. The change point detection process treats the profile in Figure 4 as a single signal change (function) and detects change points where the high-sensitivity range HSR and the region outside the high-sensitivity range HSR switch. The region setting function 273 detects the high-sensitivity range HSR from the search region E1 by detecting boundaries and change points.

[0042] Next, the region setting function 273 sets a square with sides equal to the length of the high-sensitivity range HSR as the high-sensitivity region for each of the multiple projection data. The shape of the high-sensitivity region is not limited to a square, but may be any rectangle, circle, or ellipse, or it may match the shape of the aperture made by the X-ray diaphragm 15. For the sake of detail, the following explanation will assume that the shape of the high-sensitivity region is a square. In this case, the region setting function 273 sets the centroid of the square representing the high-sensitivity range HSR to the center of each of the multiple projection data. In addition, the region setting function 273 sets a high-sensitivity region for each of the multiple projection data so that the four sides of the square are parallel to each side of the multiple projection data.

[0043] The processing circuit 27 generates correction information corresponding to the high-sensitivity region using the correction information generation function 274. The correction information is a mask corresponding to the high-sensitivity region of each of the multiple projection data. To make the explanation more specific, the mask used when the signal value (pixel value) in the high-sensitivity region is increased for the first time will be called the first mask, and the mask used when the signal value (pixel value) in the high-sensitivity region is increased for the second time or later will be called the second mask. The first mask and the second mask have a magnification factor that is multiplied by each of the multiple pixel values ​​included in the high-sensitivity region of each of the multiple projection data. This magnification factor corresponds to the correction amount that corrects the multiple pixel values ​​included in the high-sensitivity region.

[0044] The correction amount in the first mask is called the first correction amount, and the correction amount in the second mask is called the second correction amount. The first correction amount has a value greater than 1 as a predetermined magnification. The predetermined magnification is a value greater than 1 and corresponds to a correction amount that increases the signal value (pixel value) in the high-sensitivity region. The predetermined magnification is a value such as 1.001 and is set in advance and stored in the memory circuit 21. The first mask is used in the first correction process for multiple projection data (hereinafter referred to as the first correction process). The magnification at the edge of the first mask may change from the center of the first mask toward the edge of the first mask so as to decrease from the predetermined magnification (first correction amount) toward 1.

[0045] The second correction amount has a value greater than 1 and less than the predetermined magnification. The second correction amount is reduced to approach 1 in accordance with the number of repetitions of the correction process by the correction function 275 described later. For example, the correction information generation function 274 determines the second correction amount for the next correction process based on the second correction amount in the previous correction process, according to the number of correction processes. The second mask is used in the second and subsequent correction processes (hereinafter referred to as the second correction process) for multiple projection data.

[0046] For example, the correction information generation function 274 determines the second correction amount by reducing the first correction amount by a predetermined amount for the second correction process performed following the first correction process. For the second and subsequent second correction processes (hereinafter referred to as the nth correction process (where n is a natural number greater than or equal to 3)), the correction information generation function 274 determines the second correction amount to be used in the nth correction process by reducing the second correction amount used in the (n-1)th correction process by a predetermined amount. The specific method for determining the second correction amount will be explained later.

[0047] Furthermore, the magnification of the edges of the second mask may vary from the center of the second mask toward the edges of the second mask, decreasing from the second correction amount to 1. The reduction of the first and second correction amounts can be represented, for example, using a sigmoid curve. Note that the reduction of the first and second correction amounts is not limited to a sigmoid curve, but may also be represented by a logistic curve, a Gudermannian function, or a general system of the sigmoid curve. The processing circuit 27 that realizes the correction information generation function 274 corresponds to the correction information generation unit.

[0048] Figure 5 shows an example of the position of the mask CM relative to the first averaged image ARI. As shown in Figure 5, the correction amount at the edges of the mask CM is reduced to approach 1 compared to the correction amount at the center of the mask CM. As shown in Figure 5, the area of ​​the mask CM relative to the first averaged image ARI corresponds to the high-sensitivity area. Using this mask CM, correction processing is performed on each of the multiple projection data so that the sensitivity difference is reduced (eliminated).

[0049] The processing circuit 27, using the correction function 275, performs correction processing multiple times with different correction amounts for the difference in X-ray sensitivity inside and outside the high-sensitivity region of each of the multiple projection data. For example, as a first correction process for the multiple projection data, the correction function 275 applies a first mask to the high-sensitivity region of each of the multiple projection data to generate multiple projection data after the first correction (hereinafter referred to as first corrected projection data). Specifically, in the first correction process, the correction function 275 generates multiple first corrected projection data by multiplying the pixel values ​​included in the high-sensitivity region of each of the multiple projection data by the first mask.

[0050] Furthermore, the correction function 275 generates multiple projection data after the second correction (hereinafter referred to as "second correction projection data") by applying the second mask to the high-sensitivity region of each of the multiple first correction projection data, in accordance with the judgment result of the judgment function 276 described later. Specifically, in the first second correction process, the correction function 275 generates multiple second correction projection data by multiplying the pixel values ​​included in the high-sensitivity region of each of the multiple first correction projection data by the second mask. Generally, in the nth correction process, the correction function 275 generates multiple second correction projection data by multiplying the pixel values ​​included in the high-sensitivity region of each of the multiple (n-1) correction projection data by the second mask in the nth correction process, in accordance with the judgment result of the judgment function 276. The processing circuit 27 that realizes the correction function 275 corresponds to the correction unit.

[0051] The processing circuit 27 generates a second averaged image after the first correction by applying a reconstruction filter to each of the first corrected projection data using the filter averaging function 272 and then averaging them. Alternatively, the filter averaging function 272 may generate a second averaged image after the second correction by applying a reconstruction filter to each of the second corrected projection data after the nth correction process and then averaging them.

[0052] The processing circuit 27, using the determination function 276, determines whether the sensitivity difference between the inside and outside of the high-sensitivity region has been eliminated based on the second averaged image. For example, the determination function 276 calculates the average of the pixel values ​​outside the high-sensitivity region in the second averaged image (hereinafter referred to as the first average). The determination function 276 also calculates the average of the pixel values ​​inside the high-sensitivity region in the second averaged image (hereinafter referred to as the second average). Next, the determination function 276 calculates the difference between the first average and the second average (hereinafter referred to as the average difference). Subsequently, the determination function 276 calculates the ratio of the average difference to the first average by dividing the average difference by the first average. The processing circuit 27 that implements the determination function 276 corresponds to the determination unit.

[0053] The determination function 276 compares the calculated ratio with a predetermined threshold. The predetermined threshold is set in advance and stored in the memory circuit 21. The predetermined threshold is, for example, zero. The determination function 276 determines whether or not the X-ray sensitivity difference has been eliminated by comparing the calculated ratio with the predetermined threshold. For example, if the calculated ratio reaches the predetermined threshold, the determination function 276 determines that the sensitivity difference has been eliminated. The determination of the elimination of the sensitivity difference is not limited to the above. For example, a function to minimize the sensitivity difference may be arbitrarily defined, and the elimination of the sensitivity difference may be determined by determining that the function has converged to its minimum value. Alternatively, the determination of the elimination of the sensitivity difference may be made using the least squares method with the calculated ratio and the predetermined threshold.

[0054] Furthermore, if the calculated ratio does not reach a predetermined threshold, the determination function 276 determines that the sensitivity difference has not been eliminated. For example, if it is determined that the sensitivity difference has not been eliminated after the first correction process, the correction information generation function 274 may determine a second correction amount based on the first correction amount and the ratio.

[0055] Specifically, since the ratio depends on the correction amount (magnification) in the correction process, the correction information generation function 274 may determine the second correction amount in the next correction process according to the change (derivative) of the ratio to the correction amount. For example, the correction information generation function 274 may determine the correction amount in the next correction process by subtracting the value obtained by multiplying the derivative by a coefficient from the correction amount in the current mask.

[0056] Figure 6 shows an example of a profile in the second averaged image AP. The region HSO shown in Figure 6 represents the region outside the high-sensitivity region. The judgment function 276 calculates the first average by calculating the average of multiple pixel values ​​contained in the region HSO outside the high-sensitivity region. The region HSI shown in Figure 6 represents the region inside the high-sensitivity region. The judgment function 276 calculates the second average by calculating the average of multiple pixel values ​​contained in the region HSO inside the high-sensitivity region.

[0057] The processing circuit 27, using the reconstruction function 277, performs a reconstruction process that includes the application of a reconstruction filter based on multiple projection data after the second correction. For example, the reconstruction function 277 applies a reconstruction filter to multiple second-corrected projection data related to the second averaged image, which is determined to have had its sensitivity difference eliminated after the correction process by the correction function 275. Next, the reconstruction function 277 performs a reconstruction process on the multiple second-corrected projection data to which the reconstruction filter has been applied. The reconstruction process is not limited to the FBP method and may be performed using any reconstruction method, such as iterative reconstruction. The reconstruction function 277 generates CT image data (also referred to as a 3D volume image, volume data, reconstructed image, or CBCT image) by performing the reconstruction process.

[0058] The overall configuration of the X-ray diagnostic apparatus 1 having the medical image processing device 100 according to the embodiment has been described above. Under this configuration, the X-ray diagnostic apparatus 1 having the medical image processing device 100 according to the embodiment performs a process to correct sensitivity differences in multiple projection data (hereinafter referred to as projection data correction process). The procedure for projection data correction process will be described below with reference to Figure 7.

[0059] Figure 7 is a flowchart illustrating an example of the projection data correction procedure. This projection data correction procedure explains, as an example, the process up to generating a reconstructed image using the corrected projection data. In the projection data correction procedure, it is assumed that rotational imaging has been performed on the subject P in advance. At this time, multiple projection data corresponding to multiple rotation angles around the subject P are stored in the memory circuit 21.

[0060] (Projection data correction processing) (Step S701) The processing circuit 27 acquires multiple projection data from the memory circuit 21 using the acquisition function 271. When rotational imaging is being performed on the subject P, the acquisition function 271 acquires multiple projection data corresponding to multiple rotation angles from the X-ray detector 17 based on the output signals from multiple X-ray detection elements in the X-ray detector 17, which rotates around the rotation axis around the subject P.

[0061] (Step S702) The processing circuit 27 applies a reconstruction filter to each of the multiple projection data using the filter averaging function 272.

[0062] (Step S703) The processing circuit 27 applies an averaging process to multiple projection data to which a reconstruction filter has been applied, using the filter averaging function 272. This causes the filter averaging function 272 to generate an averaged image. If the correction process has not yet been performed, the filter averaging function 272 generates a first averaged image. If the correction process has already been performed, the filter averaging function 272 generates a second averaged image.

[0063] (Step S704) If it is the first time the correction process is repeated (Yes in step S704), the process in step S705 is executed. If it is not the first time the correction process is repeated (No in step S704), the process in step S708 is executed. The determination in this step is performed, for example, by the determination function 276.

[0064] (Step S705) The processing circuit 27 uses the region setting function 273 to set high-sensitivity regions for each of the multiple projection data based on the first averaged image. Specifically, the region setting function 273 identifies high-sensitivity regions in the first averaged image using the profile of the search region E1 in the first averaged image. Then, the region setting function 273 sets high-sensitivity regions for each of the multiple projection data using the pixel positions in the identified high-sensitivity regions.

[0065] (Step S706) The processing circuit 27 generates a first mask corresponding to the high-sensitivity region as a correction mask using the correction information generation function 274. At this time, the correction information generation function 274 generates the first mask by reading a predetermined magnification from the memory circuit 21. The correction information generation function 274 may also change the magnification of the edge of the first mask so as to reduce it from a predetermined magnification (first correction amount) to 1 from the center of the first mask towards the edge of the first mask.

[0066] (Step S707) The processing circuit 27 uses a correction function 275 to apply a correction mask to multiple projection data to generate corrected projection data. For example, when the first correction process is performed, the correction function 275 generates multiple first corrected projection data by multiplying multiple pixel values ​​in the high-sensitivity region of the multiple projection data by the first mask. When the first second correction process is performed, the correction function 275 generates multiple second corrected projection data by multiplying multiple pixel values ​​in the high-sensitivity region of the multiple first corrected projection data by the second mask.

[0067] Furthermore, when the nth second correction process is performed, the correction function 275 generates the nth set of second correction projection data by multiplying the multiple pixel values ​​in the high-sensitivity region of the multiple second correction projection data generated by the (n-1)th second correction process by the second mask corresponding to the nth second correction process.

[0068] (Step S708) The processing circuit 27 evaluates the correction results in the high-sensitivity region for multiple corrected projection data using the judgment function 276. For example, the judgment function 276 calculates the first mean and the second mean in the second averaged image generated based on the most recent multiple corrected projection data. Next, the judgment function 276 uses the first mean and the second mean to calculate the ratio of the average difference to the first mean. Subsequently, the judgment function 276 compares the calculated ratio with a predetermined threshold to determine whether the sensitivity difference has been eliminated. The determination of whether the sensitivity difference has been eliminated corresponds to the evaluation of the correction results in the high-sensitivity region.

[0069] (Step S709) If the correction is complete (Yes in step S709), that is, if the sensitivity difference has been eliminated, the process in step S711 is executed. If the correction is not complete (No in step S709), that is, if the sensitivity difference has not been eliminated, the process in step S710 is executed.

[0070] (Step S710) The processing circuit 27 generates a second mask corresponding to the high-sensitivity region as a correction mask using the correction information generation function 274. For example, the correction information generation function 274 generates the second mask using a second correction amount that is greater than 1 and smaller than the correction amount (magnification) in the mask used in the previous correction process. The correction information generation function 274 may also change the magnification at the edges of the second mask so that it decreases from the second correction amount to 1 from the center of the second mask towards the edges of the second mask.

[0071] (Step S711) The processing circuit 27 applies a reconstruction filter to each of the multiple corrected projection data by the reconstruction function 277. Alternatively, the application of the reconstruction filter to each of the multiple corrected projection data may be performed by a filtering function.

[0072] (Step S712) The processing circuit 27 generates a reconstructed image based on multiple projection data to which a reconstruction filter has been applied, using the reconstruction function 277. The reconstruction function 277 stores the generated reconstructed image (volume data) in the storage circuit 21.

[0073] The medical image processing apparatus 100 and X-ray diagnostic apparatus 1 according to the embodiments described above acquire multiple projection data corresponding to multiple rotation angles based on output signals from multiple X-ray detection elements in an X-ray detector 17 that rotates around a rotation axis around a subject P, apply a reconstruction filter to each of the acquired multiple projection data, generate a first averaged image by averaging the multiple projection data to which the reconstruction filter has been applied, set a region (high-sensitivity region) in which the X-ray sensitivity is relatively high in the multiple X-ray detection elements based on the averaged first averaged image, perform a correction process for the difference in X-ray sensitivity inside and outside the region in each of the multiple projection data with different correction amounts multiple times, and perform a reconstruction process that includes the execution of a reconstruction filter based on the corrected multiple projection data.

[0074] For example, the medical image processing apparatus 100 and X-ray diagnostic apparatus 1 according to the embodiment generate a plurality of projection data by applying a first mask having a first correction amount that increases a plurality of pixel values ​​contained in that region of each of the plurality of projection data by a predetermined magnification greater than 1 as a first correction process for the plurality of projection data, to each region of the plurality of projection data, thereby generating a plurality of projection data after the first correction, and then, as a second correction process for the plurality of projection data, applying a second mask having a second correction amount that increases a plurality of pixel values ​​contained in that region by a value greater than 1 and less than a predetermined magnification to each region of the plurality of projection data after the first correction, thereby generating a plurality of projection data after the second correction, and then performing a reconstruction process that includes the execution of a reconstruction filter based on the plurality of projection data after the second correction.

[0075] Specifically, the medical image processing device 100 and X-ray diagnostic device 1 according to the embodiment generate a second averaged image after the first correction by applying a reconstruction filter to each of the multiple projection data after the first correction and then averaging them. Based on the second averaged image, it is determined whether or not the sensitivity difference inside and outside the set area has been eliminated. If the sensitivity difference has not been eliminated, a second correction process is performed, applying a second mask to each of the multiple projection data after the first correction to generate multiple projection data after the second correction.

[0076] Furthermore, the medical image processing device 100 and X-ray diagnostic device 1 according to the embodiment determine whether or not the X-ray sensitivity difference has been eliminated by comparing the ratio of the difference between the first average of pixel values ​​outside the high-sensitivity region in the second average image and the second average of pixel values ​​inside the high-sensitivity region with a predetermined value. In addition, in the medical image processing device 100 and X-ray diagnostic device 1 according to the embodiment, the second correction amount is determined based on the first correction amount and the ratio.

[0077] Figure 8 shows an example of the reconstructed image BC before correction, the overcorrected reconstructed image CE as a comparative example, and the reconstructed image EM generated by this embodiment. The ring artifact that occurred in the reconstructed image BC in Figure 8 is over-corrected and becomes too white in the comparative reconstructed image CE (TW). On the other hand, in the reconstructed image EM of the embodiment, the ring artifact is eliminated without overcorrection.

[0078] Figure 9 shows an example of the reconstructed image BC before correction, the reconstructed image CE as a comparative example, and the reconstructed image EM generated by this embodiment. The ring artifact that occurred in the reconstructed image BC in Figure 9 could not be fully corrected in the reconstructed image CE of the comparative example, and a black area remains (RB). On the other hand, in the reconstructed image EM of the embodiment, the ring artifact has been eliminated by appropriate correction.

[0079] Based on these findings, the medical image processing device 100 and X-ray diagnostic device 1 according to the embodiment can appropriately correct high-sensitivity regions that cause artifacts in each of the multiple projection data. For example, the medical image processing device 100 and X-ray diagnostic device 1 according to the embodiment can accurately and easily correct sensitivity differences without losing contrast between tissues, even when it is difficult to calculate or estimate the amount of correction due to the inclusion of complex human body structures in the high-sensitivity region.

[0080] Furthermore, in the medical image processing device 100 and X-ray diagnostic device 1 according to the embodiment, the edge of the first mask changes from a predetermined magnification to 1 from the center of the first mask toward the edge of the first mask, and the edge of the second mask changes from a small value toward 1 from the center of the second mask toward the edge of the second mask. As a result, the medical image processing device 100 and X-ray diagnostic device 1 can suppress abrupt changes in the signal at the edges of the high-sensitivity region in each of the multiple corrected projection data. Therefore, the medical image processing device 100 and X-ray diagnostic device 1 can further reduce artifacts in the reconstructed image.

[0081] Based on the above, the medical image processing device 100 and X-ray diagnostic device 1 according to the embodiment can correct (suppress) ring artifacts caused by sensitivity differences in the reconstructed image. As a result, the medical image processing device 100 and X-ray diagnostic device 1 according to the embodiment can generate CBCT images with reduced ring artifacts caused by the influence of X-ray sensitivity differences, and the degree of freedom in window settings when interpreting CBCT images can be increased. Therefore, the medical image processing device 100 and X-ray diagnostic device 1 according to the embodiment can reduce misrecognition by radiologists when interpreting CBCT images, and can provide users with images that are easy to observe.

[0082] (Examples of application) In this application example, the shape of the high-sensitivity region is set based on the first averaged image. The processing performed in this application example is carried out in step S705 of the projection data correction process shown in Figure 7.

[0083] The processing circuit 27, using the region setting function 273, averages multiple pixel values ​​along the rotation axis related to the rotation of the X-ray detector 17 within a predetermined range in the first averaged image. This allows the region setting function 273 to generate an average profile. The predetermined range is pre-set to include the center of the first averaged image. The predetermined range may also be set based on the length of the high-sensitivity range HSR. The predetermined range is defined as the search range for setting the shape of the high-sensitivity range (hereinafter referred to as the high-sensitivity search range).

[0084] Figure 10 shows an example of a predetermined range PA in the first averaged image ARI and the average profile APR calculated based on the predetermined range PA. As shown in Figure 10, the average profile APR is calculated by adding up the pixel values ​​in the predetermined range along the rotation axis (arrow). The average profile APR shown in Figure 10 serves as a reference for determining the shape of the high-sensitivity region. The locations where the signal value drops in the average profile APR shown in Figure 10 correspond to the edges of the high-sensitivity region, i.e., the boundaries of the high-sensitivity region, in the left-right direction of the first averaged image ARI.

[0085] Next, the region setting function 273 generates multiple profiles with multiple pixel values ​​along multiple directions that are perpendicular to the rotation axis and parallel to each other, within a predetermined range in the first averaged image. The multiple pixel values ​​along multiple parallel directions for the multiple profiles are included in each of the multiple search ranges perpendicular to the rotation axis. The region setting function 273 compares each of the multiple profiles with the average profile APR.

[0086] The above comparison is performed, for example, along the direction of the rotation axis, from one end (e.g., the upper or lower end) of the high-sensitivity search range to the other end. The comparison of each of the multiple profiles with the average profile APR is to determine whether each of the multiple profiles and the average profile APR are similar in shape. This determination can be performed using known statistical methods such as mutual information, so the explanation is omitted.

[0087] Figure 11 shows an example of the first averaged image ARI and two of the multiple profiles. As shown in Figure 11, the shape of the first profile PR1 in range ERE1 differs from the average profile APR. Therefore, range ERE1 does not correspond to the edge of the high-sensitivity region. On the other hand, as shown in Figure 11, the shape of the second profile PR1 in range ERE2 is similar to the average profile APR. Therefore, range ERE2 corresponds to the edge of the high-sensitivity region.

[0088] The region setting function 273 sets the edges of the high-sensitivity region, i.e., the boundaries of the high-sensitivity region, by comparing multiple profiles based on the average profile with the average profile. In this way, the region setting function 273 sets the shape of the high-sensitivity region.

[0089] The medical image processing device 100 and X-ray diagnostic device 1 according to the application example of the embodiment described above generate an average profile in a predetermined range by adding and averaging multiple pixel values ​​along a rotation axis in a predetermined range in the first averaged image, and set the edge of the high-sensitivity region by comparing each of the multiple profiles made of multiple pixel values ​​along multiple directions perpendicular to the rotation axis and parallel to each other in a predetermined range in the first averaged image with the average profile.

[0090] As a result, according to the medical image processing device 100 and X-ray diagnostic device 1 of the embodiment, even if a texture trajectory (for example, a trajectory relating to an object within the subject that becomes highly luminous) is generated in the left-right direction of the first averaged image ARI due to rotational imaging of the subject P, the upper and lower ends of the high-sensitivity region and / or the shape of the high-sensitivity region can be appropriately set. Therefore, according to the medical image processing device 100 and X-ray diagnostic device 1 of the embodiment, the sensitivity difference in each of the multiple projection data can be corrected with higher accuracy.

[0091] Based on these findings, the medical image processing device 100 and X-ray diagnostic device 1 according to the application example of the embodiment can generate CBCT images with more accurate reduction of ring artifacts caused by differences in X-ray sensitivity, and further expand the freedom of window settings in CBCT image interpretation. Therefore, the medical image processing device 100 and X-ray diagnostic device 1 according to the application example of the embodiment can further reduce misrecognition by radiologists during CBCT image interpretation and provide users with images that are easier to observe.

[0092] When the technical concept of this embodiment is realized by a medical image processing method, the medical image processing method includes: acquiring multiple projection data corresponding to multiple rotation angles based on output signals from multiple X-ray detection elements in an X-ray detector 17 that rotates around a rotation axis around a subject; applying a reconstruction filter to each of the multiple projection data; generating a first averaged image by averaging the multiple projection data to which the reconstruction filter has been applied; setting regions where the X-ray sensitivity is relatively high in the multiple X-ray detection elements based on the first averaged image; performing a correction process for the difference in sensitivity inside and outside the region in each of the multiple projection data multiple times with different correction amounts; and performing a reconstruction process, including the application of the reconstruction filter, based on the corrected multiple projection data. The processing procedure for projection data correction by the medical image processing method corresponds to the embodiment and is therefore omitted from the explanation. Furthermore, the effects of the medical image processing method are the same as those in the embodiment and application examples and are therefore omitted from the explanation.

[0093] When the technical concept in the embodiment is realized in a medical image processing program, the medical image processing program enables the computer to acquire multiple projection data corresponding to multiple rotation angles based on output signals from multiple X-ray detection elements in an X-ray detector 17 that rotates around a rotation axis around a subject, apply a reconstruction filter to each of the multiple projection data, generate a first averaged image by averaging the multiple projection data to which the reconstruction filter has been applied, set regions in the multiple X-ray detection elements where the X-ray sensitivity is relatively high based on the first averaged image, perform a correction process for the difference in sensitivity inside and outside the region in each of the multiple projection data multiple times with different correction amounts, and perform a reconstruction process, which involves the execution of the reconstruction filter, based on the corrected multiple projection data.

[0094] For example, projection data correction processing can be realized by installing a medical image processing program on a computer such as a medical image processing device and / or X-ray diagnostic device, and by loading the medical image processing program into memory. In this case, the program that can cause the computer to execute the projection data correction processing can also be stored and distributed on a storage medium such as a magnetic disk (hard disk, etc.), optical disk (CD-ROM, DVD, etc.), or semiconductor memory. Furthermore, the distribution of the medical image processing program is not limited to the above-mentioned media, and may also be distributed using telecommunications functions, such as downloading via the internet. The procedure and effects of the projection data correction processing realized by the medical image processing program are the same as those in the embodiments and application examples, so a description will be omitted.

[0095] According to at least the embodiments and application examples described above, artifacts caused by differences in the sensitivity of the X-ray detector 17 can be reduced.

[0096] While several embodiments have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These embodiments can be implemented in a variety of other forms, and various omissions, substitutions, modifications, and combinations of embodiments are possible without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents. [Explanation of Symbols]

[0097] 1. X-ray diagnostic equipment 3. Imaging Unit 5 berths 7 Drive Unit 9 Control section 11 X-ray high-voltage equipment 13 X-ray tube 17 X-ray detector 19 Support device 21 Memory circuit 23 Display section 25 Input Interfaces 27 Processing Circuit 51 Top plate 71 Imaging system movement drive unit 73 Top plate movement drive unit 231 displays 270 Image Processing Functions 271 Acquisition function 272 Filter Averaging Function 273 Area setting function 274 Correction Information Generation Function 275 Correction function 276 Judgment Function 277 Reconfiguration function A1 Cylindrical artifact E1 Search area P Subject

Claims

1. An acquisition unit that acquires multiple projection data corresponding to multiple rotation angles based on output signals from multiple X-ray detection elements in an X-ray detector that rotates around a rotation axis around the subject, A filter averaging unit generates a first averaged image by applying a reconstruction filter to each of the plurality of projection data and averaging the plurality of projection data to which the reconstruction filter has been applied. A region setting unit sets a region in which the X-ray sensitivity is relatively high in the plurality of X-ray detection elements based on the first averaged image, A correction unit performs a correction process for the difference in sensitivity between the inside and outside of the region in each of the plurality of projection data, multiple times with different correction amounts, A reconstruction unit that performs a reconstruction process, including the execution of the reconstruction filter, based on the corrected plurality of projection data, A medical image processing device equipped with [a specific feature].

2. The correction unit, As the first correction process for the plurality of projection data, a first mask having a first correction amount that increases a plurality of pixel values ​​included in the region of each of the plurality of projection data by a predetermined magnification greater than 1 is applied to the region of each of the plurality of projection data to generate the plurality of projection data after the first correction. As a second correction process for the plurality of projection data, a second mask having a second correction amount that increases the plurality of pixel values ​​included in the region by a value greater than 1 and smaller than the predetermined magnification is applied to each region of the plurality of projection data after the first correction, thereby generating the plurality of projection data after the second correction. The reconstruction unit performs a reconstruction process, which involves executing the reconstruction filter, based on the plurality of projection data after the second correction. The medical image processing apparatus according to claim 1.

3. The filter averaging unit generates a second averaged image after the first correction by applying the reconstruction filter to each of the multiple projection data after the first correction and then averaging them. The system further includes a determination unit that determines whether or not the sensitivity difference inside and outside the region has been eliminated based on the second averaged image, If the aforementioned sensitivity difference is not resolved, the correction unit, as the second correction process, applies the second mask to each of the multiple projection data after the first correction to generate the multiple projection data after the second correction. The medical image processing apparatus according to claim 2.

4. The edge of the first mask changes from the predetermined magnification to 1, from the center of the first mask toward the edge of the first mask. The edge of the second mask changes from the small value to 1, from the center of the second mask toward the edge of the second mask. The medical image processing apparatus according to claim 2.

5. The determination unit determines whether or not the sensitivity difference has been eliminated by comparing the ratio of the difference between the first average and the second average of pixel values ​​inside the region with respect to the first average of pixel values ​​outside the region in the second averaged image, and a predetermined value. The medical image processing apparatus according to claim 3.

6. The second correction amount is determined based on the first correction amount and the ratio. The medical image processing apparatus according to claim 5.

7. The aforementioned region setting unit is In the first averaged image, an average profile is generated in the predetermined range by adding and averaging multiple pixel values ​​along the rotation axis within a predetermined range. In the predetermined range of the first averaged image, the boundaries of the region are determined by comparing each of the multiple profiles, each of which consists of multiple pixel values ​​along multiple directions perpendicular to the rotation axis and parallel to each other, with the averaged profile. A medical image processing apparatus according to any one of claims 1 to 6.

8. An X-ray detector having multiple X-ray detection elements and rotating around the subject on a rotation axis, An acquisition unit that acquires multiple projection data corresponding to multiple rotation angles based on the output signals from the multiple X-ray detection elements, A filter averaging unit generates a first averaged image by applying a reconstruction filter to each of the plurality of projection data and averaging the plurality of projection data to which the reconstruction filter has been applied. A region setting unit sets a region in which the X-ray sensitivity is relatively high in the plurality of X-ray detection elements based on the first averaged image, A correction unit performs a correction process for the difference in sensitivity between the inside and outside of the region in each of the plurality of projection data, multiple times with different correction amounts, A reconstruction unit that performs a reconstruction process, including the execution of the reconstruction filter, based on the corrected plurality of projection data, An X-ray diagnostic device equipped with [specific features / features].

9. Based on the output signals from multiple X-ray detection elements in an X-ray detector that rotates around a rotation axis surrounding the subject, multiple projection data corresponding to multiple rotation angles are acquired. A reconstruction filter is applied to each of the aforementioned multiple projection data, and a first averaged image is generated by averaging the aforementioned multiple projection data to which the reconstruction filter has been applied. Based on the first averaged image, a region with relatively high X-ray sensitivity is set in the plurality of X-ray detection elements. For each of the aforementioned multiple projection data, the correction process for the difference in sensitivity between the inside and outside of the region is performed multiple times with different correction amounts. Based on the corrected plurality of projection data, a reconstruction process is performed, which involves executing the reconstruction filter. A medical image processing method comprising the following.

10. On the computer, Based on the output signals from multiple X-ray detection elements in an X-ray detector that rotates around a rotation axis surrounding the subject, multiple projection data corresponding to multiple rotation angles are acquired. A reconstruction filter is applied to each of the aforementioned multiple projection data, and a first averaged image is generated by averaging the aforementioned multiple projection data to which the reconstruction filter has been applied. Based on the first averaged image, a region with relatively high X-ray sensitivity is set in the plurality of X-ray detection elements. For each of the aforementioned multiple projection data, the correction process for the difference in sensitivity between the inside and outside of the region is performed multiple times with different correction amounts. Based on the corrected plurality of projection data, a reconstruction process is performed, which involves executing the reconstruction filter. A medical image processing program that makes this possible.

Images