Medical image processing apparatus, medical image processing method, and storage medium

Abstract

A medical image processing apparatus according to an embodiment includes an acquisition unit, a derivation unit, and an analysis unit. The acquisition unit acquires a plurality of time-phase medical images of a brain with one of the left and right sides and the other of the brain of a subject as an affected side and the other as a healthy side. The derivation unit derives a feature quantity relating to collateral circulation in the brain of the subject on the basis of the acquired original medical image. The analysis unit analyzes the delay of the time phase of the affected side with respect to the time phase of the healthy side on the basis of the comparison results of the feature quantities of the affected side and the feature quantities of the healthy side for each of the plurality of time phases.

Description

Technical Field

[0001] The embodiments disclosed in this specification and the accompanying drawings relate to a medical image processing apparatus, a medical image processing method, and a storage medium. Background Art

[0002] As a technology for diagnosing cerebral infarction, for example, there is a technique that analyzes CT (Computed Tomography) images and quantitatively measures the status of collateral circulation. In this technique, quantitative indices of collateral circulation are calculated based on the vascular innervation areas and regions of interest analyzed using 4D-CTA (CT Angiography), and the calculated quantitative indices are used to diagnose cerebral infarction. Collateral circulation is the newly formed circulation vessels that compensate for the deterioration of blood flow when stenosis or blockage occurs.

[0003] Another technique involves dividing the brain into hemispheres and using CT images of the side showing symptoms of cerebral infarction (hereinafter referred to as the affected side) and the side without symptoms (hereinafter referred to as the healthy side). This technique counts the number of pixels in the blood vessel-filled area on both the affected and healthy sides, and calculates the ratio of the total blood vessel filling volume on the affected and healthy sides (hereinafter referred to as the left-right ratio) to provide a quantitative indicator of collateral circulation. Summary of the Invention

[0004] Problems to be solved by the invention:

[0005] 4D-CTA has the advantage of being able to perform detailed analysis, including blood flow arrival time delays. However, acquiring CT images requires approximately 20 scans per minute, which has drawbacks such as increased imaging time and radiation exposure.

[0006] In contrast, techniques that determine the left-right ratio offer the advantage of being able to perform analysis with a single imaging session. However, while this utilizes information on the proportion of blood vessels present, the arrival time of blood flow between the affected and healthy sides varies, resulting in inadequate analysis and difficulty accurately assessing pathological conditions such as collateral circulation.

[0007] The embodiment disclosed in this specification and the accompanying drawings aims to solve the problem of enabling high-precision evaluation of disease symptoms. However, the problems to be solved by the embodiment disclosed in this specification and the accompanying drawings are not limited to the above-mentioned problems. Other problems can also be identified as problems corresponding to the effects of the various components shown in the embodiments described later.

[0008] Means used to solve the problem:

[0009] A medical image processing apparatus according to an embodiment includes an acquisition unit, a derivation unit, and an analysis unit. The acquisition unit uses one of the left and right sides of a subject's brain as an affected side and the other side as a healthy side to acquire medical images of the brain in multiple time phases. The derivation unit derives feature quantities related to collateral circulation in the subject's brain based on the acquired original medical images. The analysis unit analyzes the time phase delay of the affected side relative to the healthy side based on a comparison result of the feature quantities of the affected side and the healthy side in each of the multiple time phases. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 This is a block diagram showing an example of the configuration of the in-hospital system 1 according to the first embodiment.

[0011] Figure 2 This is a block diagram showing an example of the configuration of the medical image processing apparatus 100 according to the first embodiment.

[0012] Figure 3 : is a flowchart showing an example of processing in the medical image processing apparatus 100 .

[0013] Figure 4 This is a diagram showing an example of temporal changes in the cumulative value of the number of blood vessel pixels on the affected side and the healthy side.

[0014] Figure 5 This is a diagram showing an example of temporal changes in the cumulative value of the number of blood vessel pixels on the affected side and the healthy side.

[0015] Figure 6 This is a diagram showing an example of temporal changes in the cumulative value of the number of blood vessel pixels on the affected side and the healthy side.

[0016] Figure 7 This is a diagram showing an example of an image showing a process of combining two time-phasor images.

[0017] Figure 8 This diagram shows an example of an image of a process in which images of one time phase quantity and two time phase quantity are combined.

[0018] Figure 9 This is a block diagram showing an example of the configuration of a medical image processing apparatus 200 according to the second embodiment.

[0019] Figure 10 This is a diagram showing an example of temporal changes in the cumulative value of the number of blood vessel pixels on the affected side and the healthy side. DETAILED DESCRIPTION

[0020] Hereinafter, a medical image processing apparatus, a medical image processing method, and a storage medium according to embodiments will be described with reference to the accompanying drawings.

[0021] For patients with cerebral infarction, the presence of collateral circulation is an indicator of the potential for tissue recovery, making its assessment important. In clinical settings, physicians visually assess the extent of collateral circulation based on vascular images visualized by CTA (CT Angiography) or MRA (Magnetic Resonance Angiography), for example, and use this information as a guide for determining treatment options.

[0022] Specifically, the infarcted side is compared with the opposite healthy side, and the proportion of blood vessels visible on the affected side relative to the healthy side is visually confirmed to qualitatively evaluate the state of collateral circulation. Alternatively, the degree of delay in blood flow arrival on the affected side relative to the healthy side is visually confirmed to qualitatively evaluate the state of collateral circulation.

[0023] However, these evaluations are qualitative, making it difficult for treating physicians to make consistent and rigorous judgments. Therefore, the medical image processing apparatus of the embodiment analyzes CT images and quantitatively measures the state of collateral circulation. Furthermore, the medical image processing apparatus of the embodiment calculates the left-right ratio of the affected side to the healthy side by taking into account the delay in blood flow arrival time (phase delay), enabling highly accurate evaluation of pathological conditions such as collateral circulation.

[0024] (First embodiment)

[0025] Figure 1 This is a block diagram showing an example of the configuration of an in-hospital system 1 according to the first embodiment. The in-hospital system 1 according to the first embodiment includes, for example, a hospital information system (HIS) 10, a radiology information system (RIS) 20, a medical image diagnostic apparatus (medical equipment) 30, a picture archiving and communication system (PACS) 40, and a medical image processing apparatus 100.

[0026] The HIS 10 is a computer system that supports hospital operations. Specifically, the HIS 10 includes various subsystems, such as an electronic medical record system, a medical billing system, a medical appointment system, a hospital admission system, and an admission and discharge management system.

[0027] The HIS 10 includes, for example, a computer such as a server device or a client terminal including a processor such as a CPU (Central Processing Unit), a memory such as a ROM (Read Only Memory) or a RAM (Random Access Memory), a display, an input interface, and a communication interface.

[0028] The user inputs or refers to patient-related information using the electronic medical record system included in the HIS 10. The user issues an image inspection order to the HIS 10. The HIS 10 forwards order information corresponding to the image inspection order to other systems such as the RIS 20.

[0029] The RIS20 is a computer system that supports the imaging diagnostic department. In addition to managing the appointments for imaging examination orders in collaboration with the HIS10, the RIS20 also coordinates appointment information with examination equipment and manages examination information. The RIS20 includes, for example, a computer such as a server device or client terminal equipped with a processor such as a CPU, memory such as ROM or RAM, a display, input interfaces, and communication interfaces.

[0030] The medical device 30 performs imaging (photography) according to imaging conditions (photography protocols) determined based on image inspection instructions, etc., for example. Examples of the medical device 30 include X-ray computed tomography devices, X-ray diagnostic devices, magnetic resonance imaging devices, ultrasonic diagnostic devices, nuclear medicine diagnostic devices, and the like. The medical device 30 generates medical images (original medical images) based on operations by users such as physicians (radiologists) or treating radiographers. In an embodiment, the medical device 30 is a CT device, and the original medical image is a four-dimensional CT image obtained by dynamically imaging the subject. The generated four-dimensional CT image is sent to the PACS 40. The medical device 30 is an example of a medical image generating device.

[0031] The PACS 40 is a computer system that receives four-dimensional CT images transmitted by medical equipment 30 or other external devices and stores them in a database. In response to requests from clients, the PACS 40 transmits (forwards) medical images such as four-dimensional CT images stored in the database. The PACS 40 comprises a server computer equipped with a processor such as a CPU, memory such as ROM or RAM, a display, an input interface, and a communication interface.

[0032] The configuration of the in-hospital system 1 is not limited to the above. The in-hospital system 1 may include, for example, a radiology report generating device. Furthermore, several elements of the in-hospital system 1 may be integrated. For example, the HIS 10 and the RIS 20 may be integrated into a single system.

[0033] The medical image processing apparatus 100 processes four-dimensional CT images from multiple time phases to provide information useful for physicians in diagnosing cerebral infarction in a subject. For example, the medical image processing apparatus 100 performs maximum intensity projection (MIP) processing on the four-dimensional CT images to generate maximum intensity projection images (hereinafter referred to as MIP images). For example, the medical image processing apparatus 100 determines a projection processing range (hereinafter referred to as the MIP range) within the four-dimensional CT images and performs MIP processing on the MIP range to generate the MIP images.

[0034] Figure 2 This is a block diagram showing an example of the configuration of a medical image processing apparatus 100 according to the first embodiment. The medical image processing apparatus 100 includes, for example, a communication interface 110, an input interface 120, a display 130, a processing circuit 140, and a memory 150. The communication interface 110, input interface 120, and display 130 in the medical image processing apparatus 100 are provided independently of the communication interface, input interface, and display included in the HIS 10, but they may be shared.

[0035] The communication interface 110 communicates with external devices such as the RIS 20, medical equipment 30, and PACS 40 via a network NW, such as a LAN (Local Area Network). The communication interface 110 includes, for example, a communication interface such as a NIC (Network Interface Card). The network NW may also include the Internet, a cellular network, a Wi-Fi network, a WAN (Wide Area Network), or the like, instead of or in addition to the LAN.

[0036] The input interface 120 receives various input operations from users such as medical practitioners, converts the received input operations into electrical signals, and outputs them to the processing circuit 140. For example, when a user performs an input operation, the input interface 120 generates information corresponding to the input operation. The input interface 120 outputs the generated information corresponding to the input operation to the processing circuit 140.

[0037] The input interface 120 includes, for example, a mouse, keyboard, trackball, switch, button, joystick, touch panel, etc. The input interface 120 may also be a user interface that receives voice input, such as a microphone. If the input interface 120 is a touch panel, the input interface 120 may also serve as the display function of the display 130.

[0038] In this specification, the term "input interface" is not limited to physical operating components such as a mouse and keyboard. For example, an input interface includes a signal processing circuit that receives an electrical signal corresponding to an input operation from an external input device provided separately from the device and outputs the electrical signal to a control circuit.

[0039] Display 130 displays various information. For example, it displays images generated by processing circuit 140 or a GUI (Graphical User Interface) for accepting various user input operations. For example, display 130 is an LCD (Liquid Crystal Display), a CRT (Cathode Ray Tube) display, or an organic EL (Electro Luminescence) display. Display 130 is an example of a display unit.

[0040] Processing circuit 140 includes, for example, an acquisition function 141, a determination function 142, a generation function 143, a derivation function 144, an analysis function 145, and a display control function 146. Processing circuit 140 implements these functions by, for example, a hardware processor (computer) executing a program stored in memory (storage circuit) 150.

[0041] A hardware processor refers to circuits such as a CPU, a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (such as a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), or a Field Programmable Gate Array (FPGA)).

[0042] Instead of storing the program in the memory 150, the program can be directly loaded into the circuit of the hardware processor. In this case, the hardware processor realizes its function by reading and executing the program loaded into the circuit. The above-mentioned program can also be pre-stored in the memory 150, or stored in a non-volatile storage medium such as a DVD or CD-ROM, and then installed into the drive device (not shown) of the medical image processing apparatus 100 via the non-volatile storage medium, thereby being installed from the non-volatile storage medium into the memory 150.

[0043] The hardware processor is not limited to a single circuit configuration; multiple independent circuits can be combined to form a single hardware processor to implement various functions. Alternatively, multiple components can be integrated into a single hardware processor to implement various functions. The hardware processor and memory in the medical image processing device 100 are designed to be independent of those in the HIS 10, but they can also be shared.

[0044] Memory 150 is implemented, for example, by semiconductor memory devices such as RAM and flash memory, a hard disk, or an optical disk. These nonvolatile storage media may also be implemented by other storage devices connected via a communication network, such as NAS (Network Attached Storage) or an external storage server. Memory 150 may also include nonvolatile storage media such as ROM (Read Only Memory) or registers.

[0045] Acquisition function 141 acquires medical images of the brain at multiple time phases, with one of the left and right sides of the subject's brain as the affected side and the other side as the healthy side. Acquisition function 141 is an example of an acquisition function. Acquisition function 141 acquires medical images provided by medical equipment 30 or PACS 40, for example. Acquisition function 141 is an example of an acquisition unit.

[0046] The determination function 142 determines the MIP range in the four-dimensional CT image. For example, the determination function 142 determines the MIP range for each of the affected and healthy sides of the four-dimensional CT image acquired by the acquisition function 141. The determination function 142 determines the MIP range based on information such as the location of the suspected infarction. The determination function 142 may use the entire brain area as the MIP range or a specific area within the brain as the MIP range.

[0047] The generation function 143 generates an MIP image as a medical image based on the four-dimensional CT image generated by the medical device 30. For example, the generation function 143 performs MIP processing on the MIP ranges determined by the determination function 142 for the affected side and the healthy side of the four-dimensional CT image, thereby generating a MIP image of the affected side and a MIP image of the healthy side as MIP images.

[0048] The generation function 143 generates MIP images for each of the four-dimensional CT images in multiple time phases. The generation function 143 further generates vascular images showing blood vessels including collateral circulation for each of the affected and healthy sides based on the generated MIP images. The generation function 143 is an example of a generation unit.

[0049] The derivation function 144 derives feature quantities related to collateral circulation in the subject's brain based on the MIP image generated by the generation function 143. For example, the derivation function 144 counts the number of pixels in the area filled with blood vessels (hereinafter referred to as the number of blood vessel pixels) in the MIP images of each of the affected and healthy sides of the brain, thereby calculating the total blood vessel filling volume in each of the affected and healthy sides of the brain. The derivation function 144 derives feature quantities based on the calculated total blood vessel filling volume. The derivation function 144 derives feature quantities for multiple time phases. The derivation function 144 is an example of a derivation unit.

[0050] Analysis function 145 compares characteristic quantities between the affected and healthy sides for each of the multiple time phases. Examples of characteristic quantities include the left-right inflow ratio, the left-right abundance ratio (left-right presence ratio), and the left-right outflow ratio. Based on the results of the comparison of characteristic quantities between the affected and healthy sides, analysis function 145 analyzes the time phase delay between the affected side and the healthy side. Analysis function 145 is an example of an analysis unit.

[0051] The left-right inflow ratio is the ratio of the amount of fluid (blood or contrast agent) flowing into blood vessels (including collateral circulation) on the affected side and the healthy side, respectively. The left-right abundance ratio is the ratio of the abundance (presence) of blood vessels on the affected side and the healthy side, respectively. The left-right outflow ratio is the ratio of the amount of fluid flowing out of blood vessels on the affected side and the healthy side, respectively.

[0052] The analysis function 145 determines the time phase delay between the affected side and the healthy side based on the relationship between a left-right ratio, such as the left-right inflow ratio, the left-right outflow ratio, or the left-right abundance ratio, and a predetermined threshold. For example, the analysis function 145 determines that a time phase delay exists when the left-right inflow ratio is less than a first threshold. For example, the analysis function 145 determines that a time phase delay exists when the left-right abundance ratio between different time phases is less than a second threshold. For example, the analysis function 145 determines that a time phase delay exists when the left-right outflow ratio is greater than or equal to a third threshold.

[0053] The analysis function 145 can also generate side-by-side fluid volume information by comparing fluid volume information at different time phases on the affected side and the healthy side, for example. The analysis function 145 can also determine a time phase delay related to fluid volume on the affected side relative to the healthy side based on the comparison results of the side-by-side fluid volume information (hereinafter referred to as the affected-side individual fluid volume information) and the side-by-side fluid volume information (hereinafter referred to as the healthy-side individual fluid volume information).

[0054] The display control function 146 displays various images on the display 130. For example, the display control function 146 displays delay information related to time phase delay, such as the four-dimensional CT image acquired by the acquisition function 141, the MIP image generated by the generation function 143, and the determination results of the analysis function 145, on the display 130. The display control function 146 is an example of a display control unit.

[0055] Next, the processing in the medical image processing apparatus 100 according to the first embodiment will be described. Figure 3 1 is a flowchart showing an example of processing in the medical image processing apparatus 100. First, the medical image processing apparatus 100 acquires four-dimensional CT images of a plurality of time phases stored in the PACS 40 in the acquisition function 141 (step S101).

[0056] Next, the determination function 142 determines the MIP range for each of the affected and healthy sides of the four-dimensional CT images in multiple time phases (step S103). When determining the MIP range, the determination function 142 may use, for example, the entire brain region (whole brain), the anterior cerebral artery region (ACA region), the middle cerebral artery region (MCA region), or the posterior cerebral artery region (PCA region) as the MIP range, or may use multiple or other ranges as the MIP range.

[0057] Next, the generation function 143 performs MIP processing on the MIP range in the 4D CT image determined by the determination function 142 and generates an MIP image (step S105). The generation function 143 generates MIP images for the MIP ranges of the affected and healthy sides in each of the 4D CT images in multiple time phases.

[0058] Next, the generation function 143 generates vascular images of the affected and healthy sides of the brain based on the generated MIP images (step S107). The generation function 143 also generates vascular images that represent the blood vessels within the MIP range of each of the affected and healthy sides in each of the MIP images of multiple time phases.

[0059] Next, the deriving function 144 and the analyzing function 145 analyze the left-right ratios of the affected and healthy sides (step S109). When analyzing the left-right ratios, the deriving function 144 derives feature quantities for each of the affected and healthy sides based on the MIP image generated by the generating function 143. For example, the deriving function 144 derives one of the left-right inflow ratio, the left-right abundance ratio, and the left-right outflow ratio as a feature quantity. The analysis of each of the left-right inflow ratio, the left-right abundance ratio, and the left-right outflow ratio will be described below.

[0060] The export function 144 substitutes the number of blood vessel pixels in multiple time phases into the following formula (1) to calculate the left-right inflow ratio Output (1) at a specific timing. The number of pixels ya1 in formula (1) is the number of blood vessel pixels on the affected side at time t1, which represents the total filling volume of the blood vessels in the affected hemisphere at time t1. The number of pixels ya1 can be expressed by the following formula (2), for example. Figure 4 In this case, the temporal change of the integrated value of the number of blood vessel pixels on the affected side and the healthy side is shown in the graph. Figure 4 This is a diagram showing an example of temporal changes in the cumulative value of the number of blood vessel pixels on the affected side and the healthy side.

[0061] [Formula 1]

[0062]

[0063] ya1: Number of blood vessel pixels on the affected side (time t1)

[0064] TimeMIP(ya1,ya2): cumulative value of the number of blood vessel pixels on the affected side (time t1, t2)

[0065] TimeMIP(ya1,ya2,ya3): cumulative value of the number of blood vessel pixels on the affected side (time t1, t2, t3)

[0066] yh1: Number of blood vessel pixels on the healthy side (time t1)

[0067] TimeMIP(yh1,yh2): Cumulative value of the number of blood vessel pixels on the healthy side (time t1, t2)

[0068] TimeMIP(yh1,yh2,yh3): Cumulative value of the number of blood vessel pixels on the healthy side (time t1, t2, t3)

[0069]

[0070] N v : Number of pixels in the hemisphere

[0071] m a :Hemisphere ɑ mask

[0072] t: time point

[0073] G(): density transformation function, such as normalization or thresholding

[0074] Alternatively, the derivation function 144 substitutes the number of blood vessel pixels in multiple time phases into the following formula (3) to calculate the left-right abundance ratio Output (2) at a specific timing. Figure 5 In this case, the temporal change of the integrated value of the number of blood vessel pixels on the affected side and the healthy side is shown in the graph. Figure 5This is a diagram showing an example of temporal changes in the cumulative value of the number of blood vessel pixels on the affected side and the healthy side.

[0075] [Formula 2]

[0076]

[0077] ya1: Number of blood vessel pixels on the affected side (time t1)

[0078] TimeMIP(ya1,ya3): cumulative value of the number of blood vessel pixels on the affected side (time t1, t3)

[0079] yh1: Number of blood vessel pixels on the healthy side (time t1)

[0080] TimeMIP(yh1,yh3): Cumulative value of the number of blood vessel pixels on the healthy side (time t1, t3)

[0081] Alternatively, the derivation function 144 substitutes the number of blood vessel pixels in multiple time phases into the following formula (4), thereby calculating the left-right outflow ratio Output (3) in multiple time phases. Figure 6 In this case, the temporal change of the integrated value of the number of blood vessel pixels on the affected side and the healthy side is shown in the graph. Figure 6 This is a diagram showing an example of temporal changes in the cumulative value of the number of blood vessel pixels on the affected side and the healthy side.

[0082] [Formula 3]

[0083]

[0084] ya1: Number of blood vessel pixels on the affected side (time t1)

[0085] TimeMIP(ya1,ya2): cumulative value of the number of blood vessel pixels on the affected side (time t1, t2)

[0086] TimeMIP(ya1,ya2,ya3): cumulative value of the number of blood vessel pixels on the affected side (time t1, t2, t3)

[0087] yh1: Number of blood vessel pixels on the healthy side (time t1)

[0088] TimeMIP(yh1,yh2): Cumulative value of the number of blood vessel pixels on the healthy side (time t1, t2)

[0089] TimeMIP(yh1,yh2,yh3): Cumulative value of the number of blood vessel pixels on the healthy side (time t1, t2, t3)

[0090] Next, the analysis function 145 analyzes the time phase delay of the affected side relative to the healthy side based on the left-right ratio derived by the derivation function 144. For example, when the derivation function 144 derives the left-right inflow ratio Output(1), the analysis function 145 compares the left-right inflow ratio Output(1) with a first threshold value (here, 0.5). The analysis function 145 determines that there is no time phase delay when Output(1) ≥ 0.5, and determines that there is a time phase delay when Output(1) < 0.5. The first threshold value may also be a value other than "0.5."

[0091] For example, when the export function 144 exports the left-right abundance ratio Output (2), the analysis function 145 compares the left-right abundance ratio Output (2) with the second threshold value (here, 0.5). Here, the left-right abundance ratio Output (2) is used to compare whether there is a delay between the first phase (= t1) and the third phase (= t3). When Output (2) ≥ 0.5, the analysis function 145 determines that there is no phase delay (α phase delay) between the first phase (= t1) and the third phase (= t3) as the comparison object, and when Output (2) < 0.5, it determines that there is a phase delay. The second threshold value may also be a value other than "0.5". The second threshold value is the same value as the first threshold value, but the second threshold value may also be different from the first threshold value.

[0092] For example, when the export function 144 exports the left-right outflow ratio Output (3), the analysis function 145 compares the left-right outflow ratio Output (3) with the third threshold value (here 0.5). When Output (3) ≥ 0.5, the analysis function 145 determines that the outflow amount of fluid from the collateral circulation during multiple time phases is the same on the affected side and the healthy side, and there is no phase delay. When Output (3) < 0.5, the analysis function 145 determines that the outflow amount of fluid from the collateral circulation during multiple time phases is less on the affected side than on the healthy side, and there is a phase delay. The third threshold value may also be a value other than "0.5". The third threshold value is the same value as the first threshold value, but the third threshold value may also be different from the first threshold value.

[0093] When the analysis function 145 completes the analysis of the left-right ratio, the display control function 146 displays the MIP image, blood vessel image, analysis results, etc. on the display 130. The display control function 146 appropriately displays the MIP image, blood vessel image, and analysis results, or may not display some or all of them.

[0094] For example, the generation function 143 may generate a combined MIP image of the n-th time phase and the (n+α)-th time phase, and the display control function 146 may display the generated combined MIP image on the display 130 . Figure 7This diagram illustrates an example of an image combining two time-phase images. For example, the generation function 143 may combine the MIP image of the first time phase (= t1) with the MIP image of the second time phase (= t2) to generate the combined MIP image TimeMIP(t1, t2), and the display control function 146 may display the generated combined MIP image TimeMIP(t1, t2) on the display 130.

[0095] Similarly, the generation function 143 may generate a combined MIP image combining the first and third time phases, or may generate a combined MIP image combining the second and third time phases. The generation function 143 may also generate a blood vessel image based on the combined MIP image, and the display control function 146 may cause the generated blood vessel image to be displayed on the display 130.

[0096] For example, the generation function 143 may combine one time phase quantity with a plurality of time phase quantities (for example, two time phase quantities) to generate an MIP image. Figure 8 This diagram illustrates an example of an image combining a single time phase image with two time phase images. For example, the generation function 143 may combine the MIP image of the first time phase (= t1) with two time phase images t1 and t2 of the second time phase (= t2) and the third time phase (= t3) to generate the combined MIP image TimeMIP(t1, (t2, t3)).

[0097] Similarly, the generation function 143 may generate a combined MIP image by combining the second phase with the two-phase images of the first and third phases, and may generate a combined MIP image by combining the third phase with the two-phase images of the first and third phases. The generation function 143 may further generate a blood vessel image based on the combined MIP image, and the display control function 146 may display the generated blood vessel image on the display 130. In this way, the medical image processing apparatus 100 ends. Figure 3 The processing shown.

[0098] In the first embodiment, the medical image processing apparatus 100 compares feature values of the affected and healthy sides, derived for each of multiple time phases, with a threshold value based on four-dimensional CT images captured by the medical device 30, to analyze the delay between the affected and healthy sides. This allows the user to accurately diagnose collateral circulation. Collateral circulation is a factor affecting patient prognosis, so feature values such as the left-right ratio can be used as indicators for treatment decisions.

[0099] (Second embodiment)

[0100] Next, a second embodiment will be described. Figure 9This is a block diagram showing an example of the configuration of a medical image processing apparatus 200 according to the second embodiment. The medical image processing apparatus 200 according to the second embodiment differs primarily from the medical image processing apparatus 100 according to the first embodiment in the configuration of the processing circuit 140. The following description of the second embodiment will focus on the differences from the first embodiment. In the following description, common elements are sometimes denoted by the same reference numerals, and their descriptions may be omitted.

[0101] The processing circuit 140 in the medical image processing apparatus 200 of the second embodiment includes an acquisition function 141, a determination function 142, a generation function 143, a derivation function 144, an analysis function 145, and a display control function 146, as well as an acceptance function 147. The remaining functions are common to the medical image processing apparatus 100 of the first embodiment.

[0102] The acceptance function 147 accepts the user's designation of the MIP range. For example, the acceptance function 147 accepts designation information sent from the input interface 120 by the user operating the input interface 120. The designation information is information that designates the MIP range in the four-dimensional CT image. The acceptance function 147 is an example of an acceptance unit.

[0103] The determination function 142 determines the MIP range in the four-dimensional CT image based on the designated information received by the acceptance function 147. To determine the MIP range, the determination function 142 divides the four-dimensional CT image acquired by the acquisition function 141 into the affected side and the healthy side. The determination function 142 may also determine the MIP range based on information other than the designated information received, such as information about the location of a suspected infarction. The determination function 142 is an example of a determination unit.

[0104] The medical image processing apparatus 200 of the second embodiment achieves the same functions and effects as the medical image processing apparatus 100 of the first embodiment. Furthermore, in the medical image processing apparatus 200 of the second embodiment, the acceptance function 147 accepts user designation of an MIP range. This allows for highly accurate diagnosis of cerebral infarction within the MIP range specified by the user. For example, the user can specify only the range of the MCA region where collateral circulation is particularly developed.

[0105] In each of the aforementioned embodiments, the derivation function 144 derived the left-right inflow ratio, left-right abundance ratio, and left-right outflow ratio as characteristic quantities for the affected and healthy sides. Alternatively, the derivation function 144 may generate a collateral circulation time ratio by comparing the abundance ratios of blood vessels at different time phases on the affected and healthy sides. Furthermore, the analysis function 145 may determine a time phase delay based on the derived collateral circulation time ratios for the affected and healthy sides.

[0106] The export function 144 substitutes the number of blood vessel pixels on the affected side in multiple time phases into the following formula (5), thereby calculating the collateral circulation time ratio Output (4) of the affected side as the collateral circulation time of the affected side. Figure 10 In this case, the temporal change of the integrated value of the number of blood vessel pixels on the affected side and the healthy side is shown in the graph. Figure 10 This is a diagram showing an example of temporal changes in the cumulative value of the number of blood vessel pixels on the affected side and the healthy side.

[0107] [Number 4]

[0108]

[0109] ya1: Number of blood vessel pixels on the affected side (time t1)

[0110] TimeMIP(ya1,ya3): cumulative value of the number of blood vessel pixels on the affected side (time t1, t3)

[0111] The analysis function 145 analyzes the time phase delay of the affected side relative to the healthy side based on the collateral circulation time ratio output (4) of the affected side derived by the derivation function 144. For example, by processing the collateral circulation time ratio output (4) of the affected side, which is the ratio of the number of blood vessel pixels in the first time phase to the cumulative value of the number of blood vessel pixels in the first and third time phases, with a certain threshold, the analysis function 145 can determine the amount of blood change per unit time. Alternatively, if the amount of blood change is, for example, below a predetermined threshold, it may be determined that a time phase delay exists.

[0112] In addition, in each of the above-mentioned embodiments, the analysis function 145 can also analyze the time delay based on the time change of the total filling volume on the affected side. The analysis function 145, for example, calculates the volume change Output (5) of the liquid (contrast agent or blood) in the brain as the time change of the total filling volume on the affected side through the following formula (6), and judges the time delay based on the volume change Output (5) of the liquid. In this case, for example, a threshold value, such as 25 mm, can be set for the change amount. 3 , and when the change Output(5) is below the threshold, it is determined that there is a phase delay.

[0113] [Number 5]

[0114]

[0115] ya1: Number of blood vessel pixels on the affected side (time t1)

[0116] TimeMIP(ya1,ya3): cumulative value of the number of blood vessel pixels on the affected side (time t1, t3)

[0117] According to at least one embodiment described above, the medical image processing device comprises: an acquisition unit, which acquires medical original images of multiple time phases of the brain by taking one of the left and right sides and the other side of the brain of the subject as the affected side and the other side as the healthy side; an export unit, which exports characteristic quantities related to the collateral circulation in the brain of the subject based on the acquired medical original images; and an analysis unit, which analyzes the time phase delay of the affected side relative to the healthy side based on a comparison result of the characteristic quantities of the affected side and the healthy side in each of the multiple time phases; thereby, the pathology can be evaluated with high precision.

[0118] While several embodiments have been described above, these embodiments are provided as examples and are not intended to limit the scope of the invention. These embodiments may be implemented in various other ways, and various omissions, substitutions, and modifications may be made without departing from the spirit of the invention. These embodiments and their variations are intended to be included within the scope and spirit of the invention and are encompassed by the invention set forth in the claims and their equivalents.

Claims

1. A medical image processing device, wherein: have: an acquisition unit that acquires original medical images of a plurality of time phases of the brain, with one of the left and right sides and the other side of the brain of the subject as the affected side and the other side as the healthy side; a deriving unit that derives a feature value related to collateral circulation in the brain of the subject based on the acquired original medical image; as well as The analyzing unit analyzes a time phase delay of the affected side relative to the healthy side based on a comparison result of the feature amounts of the affected side and the healthy side in each of the plurality of time phases.

2. The medical image processing apparatus according to claim 1, wherein: Also features: The display control unit causes the display unit to display delay information related to the determined delay of the time phase.

3. The medical image processing apparatus according to claim 1, wherein: The deriving unit derives a ratio of the amount of fluid flowing into the blood vessel on the affected side and the healthy side, respectively, in each of the plurality of time phases. The analyzing unit analyzes the delay in the time phase based on the ratio of the inflow amounts.

4. The medical image processing apparatus according to claim 1, wherein: The deriving unit derives the abundance ratio of the blood vessels in the affected side and the healthy side in each of the plurality of time phases. The analyzing unit analyzes the delay in the time phase based on the abundance ratio.

5. The medical image processing apparatus according to claim 1, wherein: The deriving unit derives a ratio of the outflow amount of the fluid flowing out of the blood vessel on the affected side and the healthy side in each of the plurality of time phases. The analyzing unit analyzes the time phase delay based on the ratio of the outflow amounts.

6. The medical image processing apparatus according to claim 3, wherein: The analyzing unit determines that there is a time phase delay when the ratio of the inflow amounts is smaller than a first threshold value.

7. The medical image processing apparatus according to claim 4, wherein: The analyzing unit determines that there is a delay in the time phase when the abundance ratio is smaller than a second threshold value.

8. The medical image processing apparatus according to claim 5, wherein: The analyzing unit determines that there is a time phase delay when the outflow rate ratio is equal to or greater than a third threshold value.

9. The medical image processing apparatus according to claim 1, wherein: The deriving unit derives the collateral circulation time ratio of the affected side obtained by comparing the abundance ratios of the blood vessels at different time phases in the affected side. The analyzing unit determines the delay of the time phase based on the ipsilateral collateral circulation time ratio.

10. The medical image processing apparatus according to claim 1, wherein: Also features: a generating unit, performing maximum intensity projection processing on the original medical image to generate a maximum intensity projection image, The deriving unit derives the feature amount based on the maximum intensity projection image.

11. The medical image processing apparatus according to claim 10, wherein: Also features: The determination unit determines a projection processing range to be subjected to the maximum intensity projection processing.

12. The medical image processing apparatus according to claim 11, wherein: Also features: The receiving unit receives a user's designation of the projection processing range.

13. The medical image processing apparatus according to claim 1, wherein: The analyzing unit analyzes the time phase delay based on the temporal change in the total filling volume of the blood vessels on the affected side.

14. The medical image processing apparatus according to claim 10, wherein: The generating unit generates a blood vessel image based on the maximum intensity projection image. The blood vessel images in different time phases are superimposed and displayed on a display unit.

15. The medical image processing apparatus according to claim 10, wherein: The maximum intensity projection image is an image including at least one of the entire brain region, the anterior cerebral artery region, the middle cerebral artery region, and the posterior cerebral artery region.

16. A medical image processing method, wherein: The computer performs the following steps: One of the left and right sides of the brain of the subject is defined as the affected side and the other side is defined as the healthy side, and original medical images of the brain at multiple time phases are acquired. deriving a feature value related to collateral circulation in the brain of the subject based on the acquired original medical image, Based on the comparison result of the characteristic amount between the affected side and the healthy side in each of the plurality of time phases, a time phase delay of the affected side relative to the healthy side is analyzed.

17. A storage medium storing a program, The program causes the computer to perform the following steps: One of the left and right sides of the brain of the subject is defined as the affected side and the other side is defined as the healthy side, and original medical images of the brain at multiple time phases are acquired. deriving a feature value related to collateral circulation in the brain of the subject based on the acquired original medical image, Based on the comparison result of the characteristic amount between the affected side and the healthy side in each of the plurality of time phases, a time phase delay of the affected side relative to the healthy side is analyzed.

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