Intracranial artery stenosis functional evaluation method, device, equipment and storage medium

Abstract

The invention discloses an intracranial artery stenosis functional evaluation method, device and equipment and a storage medium, and the method comprises the steps: processing an obtained intracranial artery angiography image, obtaining a two-dimensional center line and a two-dimensional contour line of a target blood vessel, and determining the three-dimensional diameter of the target blood vessel; determining the three-dimensional length of the target blood vessel according to the gray value distribution on the two-dimensional center line of the target blood vessel; image coordinates of a starting point and an ending point of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and finally the average blood flow velocity in the target blood vessel is obtained; and based on the three-dimensional diameter, the three-dimensional length and the average blood flow velocity of the target blood vessel, completing intracranial artery stenosis functional evaluation. According to the method, the three-dimensional length of the target blood vessel is directly calculated from the gray value distribution on the two-dimensional center line in a more concise mode, the complex three-dimensional reconstruction step is avoided, the calculation process is simplified, and meanwhile the evaluation precision and reliability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical image processing, and in particular to a method, device, equipment and storage medium for functional evaluation of intracranial artery stenosis. Background Art

[0002] In recent years, the incidence of cerebrovascular diseases in clinical practice in my country has increased year by year, among which atherosclerotic stenosis accounts for the largest proportion of all cerebrovascular diseases in the world. The treatment options for such diseases are still controversial in current clinical practice. Usually, the diagnosis and treatment process will determine the subsequent use of drug therapy or interventional therapy strategies based on the degree of stenosis of the intracranial artery. However, the results of several large-scale clinical studies in recent years have shown that even for patients with a high degree of intracranial artery stenosis, interventional therapy does not show a significant prognostic advantage over drug therapy. This reveals that there are great limitations in formulating treatment plans based solely on morphological characteristics.

[0003] In view of the above challenges, it is particularly important to explore more accurate evaluation methods. Therefore, in dealing with the problem of intracranial artery stenosis, functional evaluation methods in the field of coronary artery stenosis are gradually introduced. For example, Chinese patent CN116616804A proposes a method for obtaining evaluation parameters of intracranial artery stenosis, which analyzes multiple frames of intracranial angiography images, automatically segments the target blood vessels using a deep learning model and reconstructs its three-dimensional model, and then automatically determines the flow time of the contrast agent by counting frames. Finally, a number of evaluation parameters including the average blood flow velocity are calculated by combining the three-dimensional model and the flow time to achieve functional evaluation of intracranial artery stenosis. CN116616804A adopts a functional evaluation method, which reduces manual intervention and improves the accuracy and repeatability of the evaluation. Nevertheless, intracranial blood vessels, due to their complex network structure, small diameter and fine branches, pose significant challenges to the three-dimensional reconstruction in the aforementioned functional evaluation. In order to ensure accuracy, accurate projection correction coefficients must be used to compensate for the errors caused by single-angle projection, which increases computational complexity and uncertainty. Summary of the invention

[0004] Based on this, the present invention aims at the above-mentioned technical problem and provides a method, device, equipment and storage medium for functional evaluation of intracranial artery stenosis.

[0005] In one aspect, the present invention provides a method for functional assessment of intracranial artery stenosis, the method comprising: Processing the acquired intracranial artery angiography images to obtain the two-dimensional center line and two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel; According to the gray value distribution on the two-dimensional centerline of the target blood vessel, the two-dimensional centerline of the target blood vessel is divided into multiple two-dimensional centerline segments, and based on the two-dimensional length and average gray value of each two-dimensional centerline segment and combined with preset reference parameters, the three-dimensional length of each two-dimensional centerline segment is calculated, and finally the three-dimensional lengths of all two-dimensional centerline segments are integrated to determine the three-dimensional length of the target blood vessel; The image coordinates of the starting point and the ending point of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and the time-density curves corresponding to the starting point and the ending point of the target blood vessel are generated in combination with the intracranial arterial angiography images to obtain the time required for the contrast agent to flow through the entire target blood vessel, and then the average blood flow velocity in the target blood vessel is obtained in combination with the three-dimensional length of the target blood vessel; Functional assessment of intracranial artery stenosis is completed based on the three-dimensional diameter, three-dimensional length and average blood flow velocity of the target vessel.

[0006] In one embodiment, determining the three-dimensional length of the target blood vessel according to the gray value distribution on the two-dimensional center line of the target blood vessel comprises: The two-dimensional centerline of the target blood vessel is discretized into a plurality of two-dimensional centerline segments, and the two-dimensional lengths and average grayscale values ​​of the two-dimensional centerline segments are calculated, and the maximum value of the average grayscale value is defined as the reference grayscale value, and the corresponding two-dimensional length is defined as the reference two-dimensional length, which is used as the preset reference parameter; The reference length is calculated based on the reference two-dimensional length and the projection parameters stored in the intracranial artery angiography image data; According to the two-dimensional length and the average gray value of the two-dimensional centerline segment, combined with the reference two-dimensional length, the reference length and the reference gray value, the three-dimensional length corresponding to the two-dimensional centerline segment is calculated; The three-dimensional lengths corresponding to all two-dimensional centerline segments are summed to obtain the three-dimensional length of the target blood vessel.

[0007] In one embodiment, the three-dimensional length corresponding to the two-dimensional centerline segment is calculated based on the two-dimensional length and the average gray value of the two-dimensional centerline segment, combined with the reference two-dimensional length, the reference length and the reference gray value, including: According to the two-dimensional length of the two-dimensional centerline segment and the reference two-dimensional length, a correction coefficient of the projection length of the two-dimensional centerline segment is calculated; The projection reduction correction coefficient of the two-dimensional centerline segment is calculated according to the average gray value and the reference gray value of the two-dimensional centerline segment; The three-dimensional length corresponding to the two-dimensional centerline segment is calculated based on the projection length correction factor, the projection reduction correction factor and the reference length.

[0008] In one embodiment, the calculation of the projection reduction correction coefficient of the two-dimensional centerline segment according to the average grayscale value and the reference grayscale value of the two-dimensional centerline segment includes: The contrast agent concentration change of the two-dimensional centerline segment is calculated according to the average gray value of the two-dimensional centerline segment and the background gray value; The contrast agent concentration change reference value is calculated according to the reference gray value and the background gray value; According to the contrast agent concentration change of the two-dimensional centerline segment and the contrast agent concentration change reference value, the projection reduction correction coefficient of the two-dimensional centerline segment is calculated.

[0009] In one embodiment, the processing of the acquired intracranial artery angiography image to obtain a two-dimensional centerline and a two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel includes: Process the acquired intracranial artery angiography images and select the frame with the clearest blood vessel development as the key frame; Use the pre-trained AI model to segment the target blood vessel on the key frame to obtain a target blood vessel segmentation binary image, where the target blood vessel is one of the MCA, ICA, BA or VA; The erosion algorithm is used to refine the target blood vessel segmentation binary image, extract the two-dimensional center line and two-dimensional contour line of the target blood vessel, and determine the three-dimensional diameter of the target blood vessel based on the two-dimensional center line and contour line of the target blood vessel.

[0010] In one embodiment, determining the three-dimensional diameter of the target blood vessel according to the two-dimensional center line and contour line of the target blood vessel comprises: According to the distance between each discrete point on the two-dimensional center line and the contour line, the two-dimensional diameter on the two-dimensional center line is obtained; The three-dimensional diameter of the target blood vessel is obtained according to the two-dimensional diameter and the projection parameters stored in the intracranial artery angiography image data.

[0011] In one embodiment, generating a time-density curve corresponding to the starting point and the ending point of the target blood vessel includes: Establish an n*n sampling area with the image coordinates of the starting point and the ending point of the target blood vessel as the center; On the intracranial artery angiography images, the average grayscale value in the sampling area is calculated frame by frame to generate the time-grayscale curve corresponding to the starting point and the ending point of the target blood vessel; According to the time-grayscale curve, the background grayscale value before the contrast agent flows into the target blood vessel is calculated, the time-grayscale curve is translated downward by the size of the background grayscale value, and then flipped upward with the zero axis as the symmetry axis to obtain the time-density curve.

[0012] In another aspect, the present invention provides a functional assessment device for intracranial arterial stenosis, the device comprising: A three-dimensional diameter determination module is used to process the acquired intracranial artery angiography image to obtain a two-dimensional center line and a two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel; A three-dimensional length determination module is used to divide the two-dimensional centerline of the target blood vessel into multiple two-dimensional centerline segments according to the grayscale value distribution on the two-dimensional centerline of the target blood vessel, calculate the three-dimensional length of each two-dimensional centerline segment based on the two-dimensional length and average grayscale value of each two-dimensional centerline segment and in combination with preset reference parameters, and finally integrate the three-dimensional lengths of all two-dimensional centerline segments to determine the three-dimensional length of the target blood vessel; The blood flow velocity calculation module is used to determine the image coordinates of the starting point and the ending point of the target blood vessel according to the two-dimensional center line of the target blood vessel, and generate the time-density curve corresponding to the starting point and the ending point of the target blood vessel in combination with the intracranial arterial angiography image, so as to obtain the time required for the contrast agent to flow through the entire target blood vessel, and then obtain the average blood flow velocity in the target blood vessel in combination with the three-dimensional length of the target blood vessel; The evaluation module is used to complete the functional evaluation of intracranial artery stenosis based on the three-dimensional diameter, three-dimensional length and average blood flow velocity of the target blood vessel.

[0013] In another aspect, the present invention provides a computer device, comprising a memory and a processor, wherein when the processor executes the computer program, the following steps are implemented: Processing the acquired intracranial artery angiography images to obtain the two-dimensional center line and two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel; According to the gray value distribution on the two-dimensional centerline of the target blood vessel, the two-dimensional centerline of the target blood vessel is divided into multiple two-dimensional centerline segments, and based on the two-dimensional length and average gray value of each two-dimensional centerline segment and combined with preset reference parameters, the three-dimensional length of each two-dimensional centerline segment is calculated, and finally the three-dimensional lengths of all two-dimensional centerline segments are integrated to determine the three-dimensional length of the target blood vessel; The image coordinates of the starting point and the ending point of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and the time-density curves corresponding to the starting point and the ending point of the target blood vessel are generated in combination with the intracranial arterial angiography images to obtain the time required for the contrast agent to flow through the entire target blood vessel, and then the average blood flow velocity in the target blood vessel is obtained in combination with the three-dimensional length of the target blood vessel; Functional assessment of intracranial artery stenosis is completed based on the three-dimensional diameter, three-dimensional length and average blood flow velocity of the target vessel.

[0014] In another aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented: Processing the acquired intracranial artery angiography images to obtain the two-dimensional center line and two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel; According to the gray value distribution on the two-dimensional centerline of the target blood vessel, the two-dimensional centerline of the target blood vessel is divided into multiple two-dimensional centerline segments, and based on the two-dimensional length and average gray value of each two-dimensional centerline segment and combined with preset reference parameters, the three-dimensional length of each two-dimensional centerline segment is calculated, and finally the three-dimensional lengths of all two-dimensional centerline segments are integrated to determine the three-dimensional length of the target blood vessel; The image coordinates of the starting point and the ending point of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and the time-density curves corresponding to the starting point and the ending point of the target blood vessel are generated in combination with the intracranial arterial angiography images to obtain the time required for the contrast agent to flow through the entire target blood vessel, and then the average blood flow velocity in the target blood vessel is obtained in combination with the three-dimensional length of the target blood vessel; Functional assessment of intracranial artery stenosis is completed based on the three-dimensional diameter, three-dimensional length and average blood flow velocity of the target vessel.

[0015] Compared with the prior art, the present invention aims to calculate the three-dimensional length of the target blood vessel directly from the grayscale value distribution on the two-dimensional centerline in a simpler way. This method avoids the complicated three-dimensional reconstruction steps, simplifies the calculation process, and improves the evaluation accuracy and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The figure is a logic block diagram of a functional evaluation method for intracranial artery stenosis in one embodiment.

[0017] Figure 2 The figure is a flow chart of a method for functional assessment of intracranial artery stenosis in one embodiment. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] like Figure 1 and Figure 2 As shown, a functional evaluation method for intracranial artery stenosis of the present invention comprises the following steps: Step S100, obtaining an intracranial artery angiography image, which is composed of a series of multi-frame angiography images at the same angiography angle.

[0020] Step S110, in the intracranial artery angiography image, select a frame of image with the clearest blood vessel development as a key frame, use a pre-trained AI model to segment the target blood vessel on the key frame, and obtain a target blood vessel segmentation binary image.

[0021] Step S120, applying a corrosion algorithm to refine the target blood vessel segmentation binary image, extracting the two-dimensional center line and two-dimensional contour line of the target blood vessel, determining the three-dimensional length of the target blood vessel according to the gray value distribution on the two-dimensional center line of the target blood vessel, and determining the three-dimensional diameter of the target blood vessel according to the two-dimensional center line and contour line.

[0022] Step S130, based on the two-dimensional center line of the target blood vessel, the image coordinates of the starting point and the ending point of the target blood vessel are determined, and the time-density curves corresponding to the starting point and the ending point of the target blood vessel are generated in combination with the intracranial arterial angiography image. The time when the contrast agent flows into the target blood vessel is obtained based on the time-density curve of the starting point of the target blood vessel, and the time when the contrast agent flows out of the target blood vessel is obtained based on the time-density curve corresponding to the ending point of the target blood vessel.

[0023] Step S140, based on the time for the contrast agent to flow into the target blood vessel and the time for the contrast agent to flow out of the target blood vessel, the time required for the contrast agent to flow through the entire target blood vessel is obtained, and combined with the three-dimensional length of the target blood vessel, the average blood flow velocity in the target blood vessel is obtained.

[0024] Step S150, obtaining functional evaluation parameters of intracranial artery stenosis according to the three-dimensional length, three-dimensional diameter and average blood flow velocity of the target blood vessel.

[0025] In step S100, the acquired intracranial arterial angiography image is image data captured at the same angiography angle, and is composed of a series of multi-frame images in time, covering the entire angiography process of contrast agent flowing into and out of the target blood vessel.

[0026] In one embodiment, the method provided by the present invention can achieve functional evaluation of intracranial artery stenosis by only importing one angiography image, without the need to use a pressure guidewire, thereby reducing trauma to the patient and saving medical costs.

[0027] In step S110, the target blood vessel is segmented on the key frame using a pre-trained AI model to obtain a target blood vessel segmentation binary image. This process can achieve a high degree of automation, avoid manual blood vessel boundary outlining, and has higher repeatability, providing strong support for subsequent analysis processes.

[0028] In one embodiment, the target blood vessel segmentation method comprises the following steps: The first AI model is used to perform category judgment on the key frame to determine the category of the intracranial artery displayed in the key frame, which includes anterior circulation artery, posterior circulation artery and non-intracranial artery.

[0029] The target blood vessel is segmented using the second AI model to obtain a target blood vessel segmentation binary image. The second AI model consists of two independent models, namely, anterior circulation segmentation model and posterior circulation segmentation model. The anterior circulation includes MCA and ICA, and the posterior circulation includes BA and VA.

[0030] In step S120, the target blood vessel segmentation binary image is refined by applying a corrosion algorithm to extract the two-dimensional center line and the two-dimensional contour line of the target blood vessel, and the three-dimensional length of the target blood vessel is determined according to the gray value distribution on the two-dimensional center line of the target blood vessel. The three-dimensional diameter of the target blood vessel is determined according to the two-dimensional center line and the contour line. This process realizes the acquisition of three-dimensional data of the target blood vessel, including three-dimensional diameter and three-dimensional length information, and provides essential morphological information for subsequent functional parameter calculations.

[0031] In one embodiment, determining the three-dimensional length of the target blood vessel according to the gray value distribution on the two-dimensional centerline of the target blood vessel includes: The two-dimensional centerline of the target blood vessel is discretized into multiple two-dimensional centerline segments, and the two-dimensional lengths and average grayscale values ​​of the two-dimensional centerline segments are calculated. The maximum value of the average grayscale value is defined as the reference grayscale value, and the corresponding two-dimensional length is defined as the reference two-dimensional length.

[0032] The reference length is calculated based on the reference two-dimensional length and projection parameters stored in the intracranial artery angiography image data.

[0033] According to the two-dimensional length and the average gray value of the two-dimensional centerline segment, combined with the reference two-dimensional length, the reference length and the reference gray value, the three-dimensional length corresponding to the two-dimensional centerline segment is calculated.

[0034] The three-dimensional lengths corresponding to all two-dimensional centerline segments are summed to obtain the three-dimensional length of the target blood vessel.

[0035] Specifically, the two-dimensional centerline of the target blood vessel is discretized into n two-dimensional centerline segments, and the two-dimensional length L of each two-dimensional centerline segment is calculated. 2D,i And the average gray value I i .

[0036] The maximum value among the average gray values ​​is recorded as the reference gray value I ref , the corresponding two-dimensional length is the reference two-dimensional length L 2D,ref .

[0037] The three-dimensional length corresponding to the reference two-dimensional length is called the reference length L. 3D,ref, according to the relationship between similar triangles in the projection principle, the calculation formula is: L 3D,ref = L 2D,ref * SOD / SID Among them, SOD is the distance between the patient and the radiation source, and SID is the distance between the imaging plane and the radiation source.

[0038] The three-dimensional length corresponding to the i-th two-dimensional centerline segment is L 3D,i First, the projection length correction coefficient is calculated according to the two-dimensional length of the two-dimensional centerline segment and the reference two-dimensional length, denoted as a, and the calculation method is: a = L 2D,i / L 2D,ref This parameter corrects for the unevenness of vascular dispersion; Secondly, according to the average gray value of the two-dimensional center line segment and the reference gray value, the projection reduction correction coefficient of the two-dimensional center line segment is calculated, denoted as b, and its calculation method is: b = (I B -I i ) / (I B -I ref ) Among them, I B is the background gray value, which corrects the uneven projection reduction caused by vascular distortion.

[0039] Finally, the calculation formula for the three-dimensional length corresponding to the i-th two-dimensional centerline segment is: L 3D,i = a* b* L 3D,ref The total three-dimensional length of the target blood vessel is denoted as L, and the calculation formula is: L = L 3D,1 + L 3D,2 + ... + L 3D,n In one embodiment, determining the three-dimensional diameter of the target blood vessel according to the two-dimensional center line and contour line of the target blood vessel includes: The two-dimensional diameter on the two-dimensional centerline is obtained according to the distance between each discrete point on the two-dimensional centerline and the contour line.

[0040] The three-dimensional diameter of the target blood vessel is obtained according to the two-dimensional diameter and the projection parameters stored in the intracranial artery angiography image data.

[0041] In step S130, the image coordinates of the starting point and the ending point of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and the time-density curves corresponding to the starting point and the ending point of the target blood vessel are generated in combination with the intracranial arterial angiography image. The time when the contrast agent flows into the target blood vessel is obtained according to the time-density curve of the starting point of the target blood vessel, and the time when the contrast agent flows out of the target blood vessel is obtained according to the time-density curve corresponding to the ending point of the target blood vessel. This step realizes the acquisition of the blood flow time in the target blood vessel, and the blood flow velocity information can be further obtained in combination with the three-dimensional length of the target blood vessel.

[0042] In one embodiment, the image coordinates of the starting point and the ending point of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and the time-density curves corresponding to the starting point and the ending point of the target blood vessel are generated in combination with the intracranial artery angiography image, including: With the image coordinates of the starting point and the ending point of the target blood vessel as the center, an n*n sampling area is established, and the size of n is adaptively adjusted according to the target blood vessel type and blood vessel diameter.

[0043] On the intracranial artery angiography images, the average grayscale value in the sampling area is calculated frame by frame to generate the time-grayscale curve corresponding to the starting point and the ending point of the target blood vessel.

[0044] According to the time-grayscale curve, the background grayscale value before the contrast agent flows into the target blood vessel is calculated, the time-grayscale curve is translated downward by the size of the background grayscale value, and then flipped upward with the zero axis as the symmetry axis to obtain the time-density curve.

[0045] In step S140, the time required for the contrast agent to flow through the entire target blood vessel is obtained based on the time when the contrast agent flows into the target blood vessel and the time when the contrast agent flows out of the target blood vessel, and the average blood flow velocity in the target blood vessel is obtained in combination with the three-dimensional length of the target blood vessel. This step realizes the calculation of the average blood flow velocity in the target blood vessel, providing essential blood flow status information for subsequent functional parameter calculations.

[0046] In one embodiment, the time when the contrast agent flows into the target blood vessel is t in , the time for the contrast agent to flow out of the target blood vessel is t out , the three-dimensional length of the target blood vessel is L, the volume of the target blood vessel is V, and the calculation formula of the blood flow state is: v = L / (t out -t in ), Q = V / (t out -t in ) Among them, v is the average blood flow velocity and Q is the average blood flow rate.

[0047] In step S150, functional evaluation parameters of intracranial artery stenosis are obtained according to the three-dimensional length, three-dimensional diameter and average blood flow velocity of the target blood vessel, and the functional evaluation parameters include: blood pressure gradient, blood flow fraction, etc. This step finally obtains the functional parameters of intracranial artery stenosis, which provides a further reference for ischemic evaluation of intracranial artery stenosis on the basis of morphological evaluation, and has potential clinical value.

[0048] In one embodiment, the target blood vessel can be subjected to hemodynamic simulation using morphological information such as the three-dimensional length and three-dimensional diameter of the target blood vessel and blood state information such as the average blood flow velocity and average blood flow. The core parameter of the hemodynamic simulation is the perfusion pressure loss in the target blood vessel, with emphasis on viscosity loss and expansion loss. Specifically, the calculation formula is: ΔP=α*v+β*v 2 Where ΔP is the pressure gradient in the target blood vessel, α is the viscosity loss coefficient, which is generated by the fluid viscosity of the blood itself and is related to the three-dimensional blood vessel diameter, etc., β is the expansion loss coefficient, which is generated by the vortex in the blood flow and is related to the degree of stenosis of the target blood vessel, etc., and v is the average blood flow velocity.

[0049] In one embodiment, the blood flow fraction in the target blood vessel is calculated as follows: FF = (Pa - ΔP) / Pa Wherein, FF is the target vessel blood flow fraction, Pa is the target vessel starting pressure, which can be obtained on a physiological monitor in the catheterization room, and ΔP is the target vessel pressure gradient, which can be obtained by the method in the previous embodiment.

[0050] In one embodiment, the method is implemented according to the following process steps.

[0051] An intracranial artery angiography image is obtained, which is composed of a series of multi-frame angiography images at the same angiography angle.

[0052] In the intracranial arterial angiography image, the frame with the clearest vascular development is selected as the key frame, and the pre-trained AI model is used to segment the target blood vessel on the key frame to obtain a target blood vessel segmentation binary image. The target blood vessel is one of the MCA, ICA, BA or VA.

[0053] The erosion algorithm is used to refine the target blood vessel segmentation binary image and extract the two-dimensional center line and two-dimensional contour line of the target blood vessel.

[0054] The three-dimensional length of the target blood vessel is determined according to the gray value distribution on the two-dimensional center line of the target blood vessel, and the three-dimensional diameter of the target blood vessel is determined according to the two-dimensional center line and the contour line.

[0055] The image coordinates of the starting point and the ending point of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and the time-density curves corresponding to the starting point and the ending point of the target blood vessel are generated in combination with the intracranial arterial angiography images.

[0056] The time when the contrast agent flows into the target blood vessel is obtained according to the time-density curve at the starting point of the target blood vessel, and the time when the contrast agent flows out of the target blood vessel is obtained according to the time-density curve corresponding to the ending point of the target blood vessel.

[0057] The time required for the contrast agent to flow through the entire target blood vessel is obtained based on the time it takes for the contrast agent to flow into the target blood vessel and the time it takes for the contrast agent to flow out of the target blood vessel. Combined with the three-dimensional length of the target blood vessel, the average blood flow velocity in the target blood vessel is obtained.

[0058] Functional assessment parameters of intracranial artery stenosis were obtained based on the three-dimensional length, three-dimensional diameter and average blood flow velocity of the target vessel.

[0059] It should be understood that although Figure 2 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0060] In one embodiment, the present invention provides a functional assessment device for intracranial artery stenosis, comprising: a three-dimensional diameter determination module, a three-dimensional length determination module, a blood flow velocity calculation module and an assessment module, wherein: The three-dimensional diameter determination module is used to process the acquired intracranial artery angiography images to obtain the two-dimensional center line and two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel.

[0061] The three-dimensional length determination module is used to divide the two-dimensional centerline of the target blood vessel into multiple two-dimensional centerline segments according to the grayscale value distribution on the two-dimensional centerline of the target blood vessel, calculate the three-dimensional length of each two-dimensional centerline segment based on the two-dimensional length and average grayscale value of each two-dimensional centerline segment and in combination with preset reference parameters, and finally integrate the three-dimensional lengths of all two-dimensional centerline segments to determine the three-dimensional length of the target blood vessel.

[0062] The blood flow velocity calculation module is used to determine the image coordinates of the starting point and the end point of the target blood vessel according to the two-dimensional center line of the target blood vessel, and generate the time-density curve corresponding to the starting point and the end point of the target blood vessel in combination with the intracranial arterial angiography image to obtain the time required for the contrast agent to flow through the entire target blood vessel, and then obtain the average blood flow velocity in the target blood vessel in combination with the three-dimensional length of the target blood vessel.

[0063] The evaluation module is used to complete the functional evaluation of intracranial artery stenosis based on the three-dimensional diameter, three-dimensional length and average blood flow velocity of the target blood vessel.

[0064] For the specific definition of the functional evaluation device for intracranial artery stenosis, please refer to the definition of the functional evaluation method for intracranial artery stenosis mentioned above, which will not be repeated here. Each module in the above-mentioned functional evaluation device for intracranial artery stenosis can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0065] In one embodiment, a computer device is provided, which may be a terminal, and includes a processor, a memory, a network interface, a display screen, and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a functional assessment method for intracranial artery stenosis is implemented. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball, or touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0066] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented: The acquired intracranial artery angiography images are processed to obtain the two-dimensional center line and two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel.

[0067] According to the grayscale value distribution on the two-dimensional centerline of the target blood vessel, the two-dimensional centerline of the target blood vessel is divided into multiple two-dimensional centerline segments. Based on the two-dimensional length and average grayscale value of each two-dimensional centerline segment and combined with preset reference parameters, the three-dimensional length of each two-dimensional centerline segment is calculated. Finally, the three-dimensional lengths of all two-dimensional centerline segments are integrated to determine the three-dimensional length of the target blood vessel.

[0068] The image coordinates of the starting and ending points of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and the time-density curves corresponding to the starting and ending points of the target blood vessel are generated in combination with the intracranial arterial angiography images to obtain the time required for the contrast agent to flow through the entire target blood vessel, and then the average blood flow velocity in the target blood vessel is obtained in combination with the three-dimensional length of the target blood vessel.

[0069] Functional assessment of intracranial artery stenosis is completed based on the three-dimensional diameter, three-dimensional length and average blood flow velocity of the target vessel.

[0070] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: The acquired intracranial artery angiography images are processed to obtain the two-dimensional center line and two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel.

[0071] According to the grayscale value distribution on the two-dimensional centerline of the target blood vessel, the two-dimensional centerline of the target blood vessel is divided into multiple two-dimensional centerline segments. Based on the two-dimensional length and average grayscale value of each two-dimensional centerline segment and combined with preset reference parameters, the three-dimensional length of each two-dimensional centerline segment is calculated. Finally, the three-dimensional lengths of all two-dimensional centerline segments are integrated to determine the three-dimensional length of the target blood vessel.

[0072] The image coordinates of the starting and ending points of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and the time-density curves corresponding to the starting and ending points of the target blood vessel are generated in combination with the intracranial arterial angiography images to obtain the time required for the contrast agent to flow through the entire target blood vessel, and then the average blood flow velocity in the target blood vessel is obtained in combination with the three-dimensional length of the target blood vessel.

[0073] Functional assessment of intracranial artery stenosis is completed based on the three-dimensional diameter, three-dimensional length and average blood flow velocity of the target vessel.

[0074] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0075] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0076] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A functional assessment method for intracranial artery stenosis, characterized in that: The method comprises: Processing the acquired intracranial artery angiography images to obtain the two-dimensional center line and two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel; According to the gray value distribution on the two-dimensional centerline of the target blood vessel, the two-dimensional centerline of the target blood vessel is divided into multiple two-dimensional centerline segments, and based on the two-dimensional length and average gray value of each two-dimensional centerline segment and combined with preset reference parameters, the three-dimensional length of each two-dimensional centerline segment is calculated, and finally the three-dimensional lengths of all two-dimensional centerline segments are integrated to determine the three-dimensional length of the target blood vessel; The image coordinates of the starting point and the ending point of the target blood vessel are determined according to the two-dimensional center line of the target blood vessel, and the time-density curves corresponding to the starting point and the ending point of the target blood vessel are generated in combination with the intracranial arterial angiography images to obtain the time required for the contrast agent to flow through the entire target blood vessel, and then the average blood flow velocity in the target blood vessel is obtained in combination with the three-dimensional length of the target blood vessel; Functional assessment of intracranial artery stenosis is completed based on the three-dimensional diameter, three-dimensional length and average blood flow velocity of the target vessel.

2. The functional assessment method for intracranial artery stenosis according to claim 1, characterized in that: Determining the three-dimensional length of the target blood vessel according to the gray value distribution on the two-dimensional center line of the target blood vessel includes: The two-dimensional centerline of the target blood vessel is discretized into a plurality of two-dimensional centerline segments, and the two-dimensional lengths and average grayscale values ​​of the two-dimensional centerline segments are calculated, and the maximum value of the average grayscale value is defined as the reference grayscale value, and the corresponding two-dimensional length is defined as the reference two-dimensional length, which is used as the preset reference parameter; The reference length is calculated based on the reference two-dimensional length and the projection parameters stored in the intracranial artery angiography image data; According to the two-dimensional length and the average gray value of the two-dimensional centerline segment, combined with the reference two-dimensional length, the reference length and the reference gray value, the three-dimensional length corresponding to the two-dimensional centerline segment is calculated; The three-dimensional lengths corresponding to all two-dimensional centerline segments are summed to obtain the three-dimensional length of the target blood vessel.

3. The functional assessment method for intracranial artery stenosis according to claim 2, characterized in that: The three-dimensional length corresponding to the two-dimensional centerline segment is calculated based on the two-dimensional length and the average gray value of the two-dimensional centerline segment, combined with the reference two-dimensional length, the reference length and the reference gray value, including: According to the two-dimensional length of the two-dimensional centerline segment and the reference two-dimensional length, a correction coefficient of the projection length of the two-dimensional centerline segment is calculated; The projection reduction correction coefficient of the two-dimensional centerline segment is calculated according to the average gray value and the reference gray value of the two-dimensional centerline segment; The three-dimensional length corresponding to the two-dimensional centerline segment is calculated based on the projection length correction factor, the projection reduction correction factor and the reference length.

4. The functional assessment method for intracranial artery stenosis according to claim 3, characterized in that: The projection reduction correction coefficient of the two-dimensional center line segment is calculated based on the average gray value and the reference gray value of the two-dimensional center line segment, including: The contrast agent concentration change of the two-dimensional centerline segment is calculated according to the average gray value of the two-dimensional centerline segment and the background gray value; The contrast agent concentration change reference value is calculated according to the reference gray value and the background gray value; The projection reduction correction coefficient of the two-dimensional centerline segment is calculated according to the contrast agent concentration change of the two-dimensional centerline segment and the contrast agent concentration change reference value.

5. The functional assessment method for intracranial artery stenosis according to claim 1, characterized in that: The step of processing the acquired intracranial artery angiography image to obtain a two-dimensional center line and a two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel includes: Process the acquired intracranial artery angiography images and select the frame with the clearest blood vessel development as the key frame; Use the pre-trained AI model to segment the target blood vessel on the key frame to obtain a target blood vessel segmentation binary image, where the target blood vessel is one of the MCA, ICA, BA or VA; The erosion algorithm is used to refine the target blood vessel segmentation binary image, extract the two-dimensional center line and two-dimensional contour line of the target blood vessel, and determine the three-dimensional diameter of the target blood vessel based on the two-dimensional center line and contour line of the target blood vessel.

6. The functional assessment method for intracranial artery stenosis according to claim 5, characterized in that: Determining the three-dimensional diameter of the target blood vessel according to the two-dimensional center line and contour line of the target blood vessel includes: According to the distance between each discrete point on the two-dimensional center line and the contour line, the two-dimensional diameter on the two-dimensional center line is obtained; The three-dimensional diameter of the target blood vessel is obtained according to the two-dimensional diameter and the projection parameters stored in the intracranial artery angiography image data.

7. The functional assessment method for intracranial artery stenosis according to claim 1, characterized in that: The generating of the time-density curve corresponding to the starting point and the ending point of the target blood vessel comprises: Establish an n*n sampling area with the image coordinates of the starting point and the ending point of the target blood vessel as the center; On the intracranial artery angiography images, the average grayscale value in the sampling area is calculated frame by frame to generate the time-grayscale curve corresponding to the starting point and the ending point of the target blood vessel; According to the time-grayscale curve, the background grayscale value before the contrast agent flows into the target blood vessel is calculated, the time-grayscale curve is translated downward by the size of the background grayscale value, and then flipped upward with the zero axis as the symmetry axis to obtain the time-density curve.

8. A functional assessment device for intracranial artery stenosis, characterized in that: The device comprises: A three-dimensional diameter determination module is used to process the acquired intracranial artery angiography image to obtain a two-dimensional center line and a two-dimensional contour line of the target blood vessel to determine the three-dimensional diameter of the target blood vessel; A three-dimensional length determination module is used to divide the two-dimensional centerline of the target blood vessel into multiple two-dimensional centerline segments according to the grayscale value distribution on the two-dimensional centerline of the target blood vessel, calculate the three-dimensional length of each two-dimensional centerline segment based on the two-dimensional length and average grayscale value of each two-dimensional centerline segment and in combination with preset reference parameters, and finally integrate the three-dimensional lengths of all two-dimensional centerline segments to determine the three-dimensional length of the target blood vessel; The blood flow velocity calculation module is used to determine the image coordinates of the starting point and the ending point of the target blood vessel according to the two-dimensional center line of the target blood vessel, and generate the time-density curve corresponding to the starting point and the ending point of the target blood vessel in combination with the intracranial arterial angiography image, so as to obtain the time required for the contrast agent to flow through the entire target blood vessel, and then obtain the average blood flow velocity in the target blood vessel in combination with the three-dimensional length of the target blood vessel; The evaluation module is used to complete the functional evaluation of intracranial artery stenosis based on the three-dimensional diameter, three-dimensional length and average blood flow velocity of the target blood vessel.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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