Method and system for vessel identification and monitoring based on static CT enhanced scans

Abstract

This invention discloses a method and system for identifying and monitoring blood vessels based on static CT-enhanced scans. The method includes the steps of: acquiring subtraction images of the entire vascular region of a patient to be monitored; equally dividing each subtraction image into a plurality of region blocks of a predetermined size and performing image processing on the subtraction images so that the positions of the region blocks in each subtraction image correspond one-to-one; calculating the average and standard deviation of each region block in each subtraction image to calculate the P value of the region block; arranging the P values ​​of the same region block in each subtraction image in chronological order to plot a P value change curve for the region block; and plotting a contrast agent concentration change curve for the region block based on the P value change curve to determine the time when the contrast agent reaches its peak. This method accurately determines the location and change trend of the blood vessel to be monitored, thereby avoiding a situation where the ROI region position of the blood vessel to be monitored, circled by a physician, deviates from the actual blood vessel, resulting in inaccurate monitored vascular CT values ​​and missing the time when the contrast agent reaches its peak.

Description

[Technical Field]

[0001] The present invention relates to a blood vessel identification and monitoring method based on static CT enhanced scanning, and a blood vessel identification and monitoring system for implementing the blood vessel identification and monitoring method, which belongs to the technical field of medical imaging. [Background technology]

[0002] Enhanced scanning increases the density difference between diseased tissue and adjacent normal tissue, improving the incidence of lesions. When performing enhanced scanning, there are individual differences between patients, and the time at which the contrast agent in the monitored blood vessels reaches its peak varies. Therefore, if physicians directly set the peak time based on their experience, they may miss the optimal time for three-phase scanning. To achieve the peak time for the contrast agent in the monitored blood vessels, a small amount of enhanced scanning mode must be used.

[0003] The CT scanning process using a small amount of enhanced scanning for vascular monitoring involves first performing a cross-sectional scan, then the physician circles the ROI (region of interest) of the blood vessel to be monitored on the cross-sectional image, injects a small amount of contrast agent into the patient, monitors the time-dependent change in the concentration of the blood vessel to be examined, and determines the time when the contrast agent reaches its peak. The physician then sets the time for the three-phase scan according to the time when the peak is reached in the first small amount of scan, injects a second small amount of contrast agent into the patient, and completes the subsequent three-phase scan. If the ROI region of the blood vessel to be monitored circled by the physician is not located in the actual blood vessel, the change in the contrast agent in the blood vessel to be monitored will be inaccurate, and the resulting curve will naturally not properly reflect the time-dependent change in the contrast agent concentration. Summary of the Invention [Problem to be solved by the invention]

[0004] The main technical problem to be solved by the present invention is to provide a method for blood vessel identification and monitoring based on static CT enhanced scanning.

[0005] Another technical problem to be solved by the present invention is to provide a blood vessel identification and monitoring system based on static CT enhanced scanning.

[0006] To achieve the above technical objectives, the present invention adopts the following technical solutions.

[0007] According to a first aspect of an embodiment of the present invention, there is provided a method for vessel identification and monitoring based on static CT enhanced scanning, the method comprising: acquiring subtraction images of the entire vascular region of the patient being monitored; a step of equally dividing each subtraction image into a plurality of region blocks of a predetermined size, and performing image processing on the subtraction images so that the positions of the region blocks in each subtraction image correspond one-to-one; calculating a mean value and a standard deviation for each of the region blocks of each of the subtraction images, and calculating a P value for the region block; a step of arranging the P values ​​of the same region block in each subtraction image in chronological order and plotting a change curve of the P value of the region block; and a step of plotting a change curve of the contrast agent concentration in the region block based on the change curve of the P value in the region block, and determining the time when the contrast agent reaches its peak.

[0008] Preferably, the step of acquiring subtraction images of the entire vascular region of the patient to be monitored specifically includes: projecting the entire vascular region of the patient to be monitored while the patient is injected with a small amount of contrast agent; acquiring images of the entire area at predetermined intervals within a predetermined time period; The method includes a step of subtracting the first image of the entire region from the second image of the entire region obtained to obtain a first subtraction image, a step of subtracting the first image of the entire region from the third image of the entire region obtained to obtain a second subtraction image, a step of subtracting the first image of the entire region from the fourth image of the entire region obtained to obtain a third subtraction image, and so on, to obtain a final subtraction image; Here, the first subtraction image to the last subtraction image are combined to form a set of subtraction images.

[0009] Preferably, the predetermined size of the region block is 16*16 pixels so as to match the diameter of the blood vessel to be monitored.

[0010] Preferably, the step of calculating the mean value and standard deviation for each of the region blocks of each of the subtraction images and calculating the P value of the region block specifically includes: calculating the mean value μ of the domain block according to the following formula: JPEG2025537425000002.jpg31157 calculating the standard deviation б of the region block according to the following formula: JPEG2025537425000003.jpg29127 includes calculating a P value of the region block according to the mean value μ and standard deviation б based on the following formula: JPEG2025537425000004.jpg57169

[0011] Preferably, the step of plotting a change curve of the concentration of the contrast agent in the region block based on the change curve of the P value of the region block and determining the time when the contrast agent reaches its peak specifically includes: Obtaining a concentration change trend of the contrast agent by monitoring a change in the average value of the region block according to a change curve of the P value of the region block; drawing a concentration change curve of the contrast agent based on the concentration change tendency of the contrast agent; The method includes a step of acquiring the time corresponding to when the concentration of the contrast agent reaches a peak value, i.e., the time when the concentration of the contrast agent reaches its peak, based on the concentration change curve of the contrast agent.

[0012] Preferably, the method further includes the step of stopping the CT scan of the patient when the concentration of the contrast agent starts to decrease from its peak value based on the concentration change curve of the contrast agent.

[0013] According to a second aspect of an embodiment of the present invention, there is provided a blood vessel identification and monitoring system based on static CT enhanced scanning, the blood vessel identification and monitoring system comprising: an image acquisition unit for acquiring subtraction images of the blood vessels of the patient to be monitored; an image processing unit connected to the image acquisition unit, for performing image processing on the subtraction images to equally divide each subtraction image into a plurality of region blocks, all of which have a predetermined size, and the positions of the region blocks in each subtraction image correspond one-to-one; a calculation unit, connected to the image processing unit, for calculating a P value for a region block of the processed subtraction image; An editing unit is connected to the calculation unit and determines the time when the contrast agent reaches its peak by plotting a concentration change curve of the contrast agent in the region block. [Effects of the Invention]

[0014] Compared with the prior art, the present invention has the following technical advantages: 1. The position and change trend of the blood vessel to be monitored can be accurately determined, which avoids the situation where the ROI region position of the blood vessel to be monitored circled by the physician deviates from the actual blood vessel, resulting in inaccurate monitored vascular CT values, which cannot properly reflect the change curve of CT values ​​over time, and the time when the contrast agent reaches its peak being missed. 2. By observing the contrast agent concentration curve and terminating the CT scan at any time if a downward trend is observed, it is possible to avoid unnecessary exposure of the patient to X-rays and reduce the amount of radiation the patient is exposed to. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a flowchart of a method for vessel identification and monitoring based on static CT-enhanced scanning provided by a first embodiment of the present invention; [Figure 2] FIG. 2 is a schematic diagram showing a structure in which a subtraction image is divided into region blocks in the first embodiment of the present invention. [Figure 3] FIG. 2 is a diagram illustrating the structure of a blood vessel identification and monitoring system based on static CT-enhanced scanning provided by a second embodiment of the present invention. [Figure 4] FIG. 10 is a diagram illustrating the structure of a blood vessel identification and monitoring system based on static CT-enhanced scanning provided by a third embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0016] The technical contents of the present invention will be described in detail and specifically below in combination with the accompanying drawings and specific embodiments. <First Example>

[0017] First, it should be noted that the blood vessel identification and monitoring method provided by the embodiment of the present invention is mainly aimed at two-phase scanning, which means that after the first injection of a small amount of contrast agent into the patient, the time when the contrast agent reaches its peak can be accurately determined to avoid missing the optimal scan time when performing three-phase scanning.

[0018] As shown in FIG. 1, a first embodiment of the present invention provides a method for vessel identification and monitoring based on static CT enhanced scanning, which specifically includes steps S1 to S5.

[0019] S1: Acquire an image. Specifically, steps S11 to S13 are included. S11: With a small amount of contrast agent injected into the patient, the entire vascular region of the patient to be monitored is projected.

[0020] In this embodiment, what is monitored is not the ROI region of the blood vessel to be monitored that the doctor has circled on the tomogram, but the entire region of the blood vessel to be monitored, thereby ensuring the comprehensiveness of the monitoring results.

[0021] S12: Images of the entire region are acquired at predetermined intervals within a predetermined time period. Specifically, in this embodiment, an image of the entire region is acquired every 250 ms, and a total of 51 images of the entire region are acquired.

[0022] S13: A subtraction image is obtained. Specifically, the first subtraction image is obtained by subtracting the first overall image from the second overall image, the second subtraction image is obtained by subtracting the first overall image from the third overall image, and so on until the final subtraction image is obtained. Thus, 50 subtraction images can be obtained from 51 overall images, and these 50 subtraction images together constitute a set of subtraction images.

[0023] S2: Process the image. Specifically, in this embodiment, after acquiring 50 subtraction images in step S1, each subtraction image is divided equally into a plurality of region blocks of a predetermined size, and image processing is performed on each subtraction image so that the positions of the region blocks in the 50 subtraction images correspond one-to-one.

[0024] As shown in FIG. 2, in this embodiment, each subtraction image includes m*n (m and n are both positive integers, and the same applies below) pixel blocks. By dividing the m*n pixel blocks, multiple region blocks 101 (i.e., shown as black regions in FIG. 2) are formed, and each region block 101 includes a*a pixel blocks. Since the size of each subtraction image is the same, the number of divided region blocks 101 is also the same. Therefore, the positions of the region blocks in the 50 subtraction images correspond one-to-one.

[0025] In one embodiment of the present invention, the region block 101 preferably includes 16*16 pixel blocks, each pixel block being approximately 0.265 mm in size, which is comparable to the diameter of the blood vessel to be monitored, and thus can match the blood vessel to be monitored, thereby improving the monitoring effect. It is understood that in other embodiments, the size of the region block 101 can be adaptively adjusted as needed.

[0026] S3: Calculate the P value for each region block in each subtraction image.

[0027] In this embodiment, image processing is performed on each subtraction image to divide it into multiple region blocks 101, and then a P value must be calculated for each region block 101. If a contrast agent appears in a region block 101 in the subtraction image, the P value of this region block 101 indicates significance, and this region block 101 can be accurately determined as the location of the contrast agent. Conversely, if a contrast agent does not appear in a region block in the subtraction image, the P value of this region block 101 does not indicate significance.

[0028] In this embodiment, it is necessary to calculate P values ​​for multiple region blocks 101 in each subtraction image, and it can be understood that whether the P value of a region block 101 indicates significance must be determined by comparing it with the P value of the region block at the same position in the previous subtraction image. Therefore, the P value at the same position will have 50 values ​​as time changes, and thus a curve can be drawn, and the change in significance will appear at the position of the contrast agent.

[0029] Here, the step of calculating the P value of the region block 101 specifically includes steps S31 to S33: S31: Calculate the average value μ of the region block 101 based on the formula (1); JPEG2025537425000005.jpg15138S32: Calculate the standard deviation б of the region block 101 according to formula (2); JPEG2025537425000006.jpg17135S33: Calculating the P value of the region block 101 according to the mean value μ and the standard deviation б based on the formula (3); JPEG2025537425000007.jpg13130, where M and N represent the number of pixels in the image, and H i、j represents the value of the (i, j) pixel point, μ0 represents the mean value at time t0, σ0 represents the standard deviation at time t0, i.e., the mean value and standard deviation of the first image, and μ n is t n It represents the average value at a time, that is, the average value of the (n-1)th image.

[0030] S4: The change curve of the P value of the region block 101 is plotted. Specifically, based on step S3, the P values ​​of multiple region blocks in each subtraction image are calculated, and then the P values ​​of the same region blocks in each subtraction image are arranged in chronological order to determine which region block 101's P value represents significance and which region block 101's P value does not represent significance, thereby obtaining the change process of the P values ​​and drawing the change curve of the P values ​​of the region blocks.

[0031] S5: Determine the time to peak contrast. Specifically, steps S51 to S53: S51: To obtain the concentration change trend of the contrast agent, monitor the change in the average value of the region block according to the change curve of the P value of the region block; S52: Drawing a contrast agent concentration change curve based on the concentration change tendency of the contrast agent; S53: A step of acquiring the time corresponding to when the concentration of the contrast agent reaches its peak value, that is, the time when the concentration of the contrast agent reaches its peak, based on the concentration change curve of the contrast agent, is included.

[0032] Therefore, the blood vessel identification and monitoring method provided by the embodiment of the present invention can accurately determine the location and change trend of the blood vessel to be monitored, and can avoid a situation where the position of the ROI region of the blood vessel to be monitored circled by the physician deviates from the original blood vessel, resulting in inaccurate CT values ​​of the blood vessel to be monitored, which cannot properly reflect the change curve of CT values ​​over time and misses the time when the contrast agent reaches its peak. Furthermore, in this embodiment, the physician can observe the change curve of the contrast agent concentration and terminate the CT scan at any time if a downward trend is observed, thereby avoiding unnecessary X-ray exposure to the patient and reducing the radiation dose to which the patient is exposed. <Second Example>

[0033] As shown in FIG. 3 , based on the above-mentioned first embodiment, the second embodiment of the present invention further provides a static CT-enhanced scan-based vascular identification and monitoring system, which includes at least an image acquisition unit 10, an image processing unit 20, a calculation unit 30 and an editing unit 40.

[0034] Specifically, the image acquisition unit 10 acquires a set of subtraction images of the patient's blood vessels to be monitored. The image processing unit 20, connected to the image acquisition unit 10, performs image processing on the set of subtraction images, equally dividing each subtraction image into a plurality of region blocks of a predetermined size, with the positions of the region blocks in each subtraction image corresponding to one another. The calculation unit 30, connected to the image processing unit 20, calculates P values ​​for the region blocks of the processed subtraction images. The editing unit 40, connected to the calculation unit 30, plots the contrast agent concentration change curves of the region blocks to determine the peak time of the contrast agent. <Third Example>

[0035] As shown in Fig. 4, based on the above-mentioned first embodiment, a third embodiment of the present invention further provides a blood vessel identification and monitoring system based on static CT-enhanced scanning, comprising one or more processors 21 and a memory 22. Here, the memory 22 is coupled to the processor 21 and is used to store one or more programs. When the one or more programs are executed by the one or more processors 21, the one or more processors 21 implement the blood vessel identification and monitoring method in the above-mentioned first embodiment.

[0036] The processor 21 is used to control the overall operation of the monitoring system to complete all or part of the steps of the above-described vascular identification and monitoring method. The processor 21 may be a central processing unit (CPU), a graphics processor (GPU), a field programmable logic gate array (FPGA), an application-specific integrated circuit (ASIC), a digital signal processing (DSP) chip, etc. The memory 22 is used to store various types of data to support the operation of the monitoring system. Such data may include, for example, instructions for any application or method used to operate the monitoring system, as well as application-related data. The memory 22 may be implemented by any type of volatile or non-volatile storage device, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, or a combination thereof.

[0037] In an exemplary embodiment, the monitoring system may be specifically implemented by a computer chip or entity, or by a product having certain functionality for performing the above-described vascular identification and monitoring method and achieving technical results consistent with the above-described method. A typical example is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, an in-vehicle human-computer interaction device, a mobile phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0038] In another exemplary embodiment, the present invention further provides a computer-readable storage medium including program instructions that, when executed by a processor, implement the steps of the blood vessel identification and monitoring method in any one of the above-described embodiments. For example, the computer-readable storage medium may be the above-described memory including program instructions, and the above-described program instructions, when executed by a processor of a monitoring system, can complete the above-described blood vessel identification and monitoring method and achieve technical effects consistent with the above-described method.

[0039] The above is a detailed description of the method and system for vessel identification and monitoring based on static CT enhanced scanning provided by the present invention. Any obvious modifications made to the present invention without departing from the essential content of the present invention by those skilled in the art will constitute infringement of the patent right of the present invention and will incur corresponding legal liability.

Claims

1. 1. A method for vessel identification and monitoring based on static CT enhanced scanning, comprising: acquiring subtraction images of the entire vascular region of the patient being monitored; a step of equally dividing each subtraction image into a plurality of region blocks of a predetermined size, and performing image processing on the subtraction images so that the positions of the region blocks in each subtraction image correspond one-to-one; calculating a mean value and a standard deviation for each of the region blocks of each of the subtraction images, and calculating a P value for the region block; a step of arranging the P values ​​of the same region block in each subtraction image in chronological order and plotting a change curve of the P value of the region block; A blood vessel identification and monitoring method, comprising the steps of: drawing a contrast agent concentration change curve for the region block based on the P value change curve for the region block; and determining the time at which the contrast agent reaches its peak.

2. The step of acquiring a subtraction image of the entire vascular region of the patient to be monitored specifically includes: projecting the entire vascular region of the patient to be monitored while the patient is injected with a small amount of contrast agent; acquiring images of the entire area at predetermined intervals within a predetermined time period; the step of subtracting the first image of the entire region from the second image of the entire region obtained to obtain a first subtraction image; the step of subtracting the first image of the entire region from the third image of the entire region obtained to obtain a second subtraction image; and the step of sequentially analogizing in this manner to obtain a final subtraction image; 2. The blood vessel identification and monitoring method according to claim 1, wherein the first subtraction image to the last subtraction image are combined to form a set of subtraction images.

3. 2. The method of claim 1, wherein the predetermined size of the region block is 16*16 pixels so as to match the diameter of the blood vessel to be monitored.

4. The step of calculating the average value and standard deviation for each of the region blocks of each of the subtraction images and calculating the P value of the region block specifically includes: calculating the mean value μ of the domain block according to the following formula: calculating the standard deviation б of the region block according to the following formula: and calculating a P value for the region block according to the mean value μ and standard deviation β based on the following formula: Here, M and N represent the number of pixels in the image, and H ｉ、ｊ represents the value of the (i, j) pixel point, and μ ０ is ０ represents the average value of the time, and σ ０ is ０ represents the standard deviation of the time, i.e., the mean value and standard deviation of the first image, and μ n is ｎ The blood vessel identification and monitoring method according to claim 1, wherein the average value at a time, that is, the average value of the (n-1)th image, is expressed.

5. The step of plotting a change curve of the contrast agent concentration of the region block based on the change curve of the P value of the region block and determining the time to reach the peak of the contrast agent specifically includes: Obtaining a concentration change trend of the contrast agent by monitoring a change in the average value of the region block according to a change curve of the P value of the region block; drawing a concentration change curve of the contrast agent based on the concentration change tendency of the contrast agent; The blood vessel identification and monitoring method according to claim 1, further comprising a step of acquiring a time corresponding to when the concentration of the contrast agent reaches a peak value, i.e., a time when the concentration of the contrast agent reaches its peak, based on a concentration change curve of the contrast agent.

6. The blood vessel identification and monitoring method of claim 1, further comprising the step of stopping CT scanning of the patient when the concentration of the contrast agent begins to decrease from a peak value based on the concentration change curve of the contrast agent.

7. 1. A vessel identification and monitoring system based on static CT enhanced scanning, comprising: an image acquisition unit for acquiring subtraction images of the blood vessels of the patient to be monitored; an image processing unit connected to the image acquisition unit, for performing image processing on the subtraction images to equally divide each subtraction image into a plurality of region blocks, all of which have a predetermined size, and the positions of the region blocks in each subtraction image correspond one-to-one; a calculation unit, connected to the image processing unit, for calculating a P value for a region block of the processed subtraction image; A blood vessel identification and monitoring system, comprising an editing unit connected to the calculation unit, for determining the time when the contrast agent reaches its peak by plotting a concentration change curve of the contrast agent in the region block.

8. Specifically, the step of acquiring a subtraction image of the blood vessel of the patient to be monitored includes: projecting the entire vascular region of the patient to be monitored while a small amount of contrast agent is injected into the patient; acquiring images of the entire area at predetermined intervals within a predetermined time period; the step of subtracting the first image of the entire region from the second image of the entire region obtained to obtain a first subtraction image; the step of subtracting the first image of the entire region from the third image of the entire region obtained to obtain a second subtraction image; and the step of sequentially analogizing in this manner to obtain a final subtraction image; 8. The blood vessel identification and monitoring system according to claim 7, wherein the first subtraction image to the last subtraction image are combined to form a set of subtraction images.

9. The step of calculating a P value for a region block of the processed subtraction image specifically includes: calculating the mean value μ of the domain block according to the following formula: calculating the standard deviation б of the region block according to the following formula: and calculating a P value for the region block according to the mean value μ and standard deviation β based on the following formula: Here, M and N represent the number of pixels in the image, and H ｉ、ｊ represents the value of the (i, j) pixel point, and μ ０ is ０ represents the average value of the time, and σ ０ is ０ represents the standard deviation of the time, i.e., the mean value and standard deviation of the first image, and μ n is ｎ The blood vessel identification and monitoring system according to claim 8, wherein the average value at a time, that is, the average value of the (n-1)th image, is represented.

10. The step of determining the time to reach the peak of the contrast agent by plotting the concentration change curve of the contrast agent in the region block specifically includes: Obtaining a concentration change trend of the contrast agent by monitoring a change in the average value of the region block according to a change curve of the P value of the region block; drawing a concentration change curve of the contrast agent based on the concentration change tendency of the contrast agent; The blood vessel identification and monitoring system according to claim 9, further comprising a step of acquiring a time corresponding to when the concentration of the contrast agent reaches a peak value, i.e., a time when the contrast agent reaches its peak, based on a concentration change curve of the contrast agent.

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