Vascular image analysis method and device based on super-resolution radiography and storage medium

Abstract

The embodiment of the invention provides a blood vessel image analysis method and device based on super-resolution radiography and a storage medium. The method comprises the following steps: acquiring a super-resolution blood vessel image to be analyzed; determining a first capillary region and a second capillary region from the super-resolution blood vessel image, wherein the first capillary region and the second capillary region are respectively partial regions of the super-resolution blood vessel image; and determining a blood perfusion ratio of the first capillary region to the second capillary region, and outputting the blood perfusion ratio. According to the technical scheme, the accuracy of quantitative analysis of the microvessels can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ultrasonic imaging, in particular to a blood vessel image analysis method and device based on super-resolution contrast and a storage medium. BACKGROUND

[0002] Microvessels include capillaries, arterioles and venules, etc. Normal microvessels have good forked branches and ordered structure. When the metabolism and function of tissues and organs are abnormal, the microvessels will change to a certain extent. Through quantitative analysis of the morphological and microflow hemodynamic parameters of the microvessels, the disease nature can be identified, the progress can be monitored, and the curative effect can be quantitatively evaluated, thus having important value.

[0003] As a new technology capable of observing lesions and their tissues in real time and dynamically, ultrasonic contrast plays an increasingly important role in disease diagnosis, and is becoming an important examination method for clinically evaluating microvessels. However, due to the diffraction limit of the conventional ultrasonic contrast in the clinic, the accuracy of quantitative analysis of microvessels is not high. SUMMARY

[0004] Embodiments of the present application provide a blood vessel image analysis method and device based on super-resolution contrast and a storage medium, aiming to improve the accuracy of quantitative analysis of microvessels.

[0005] In a first aspect, embodiments of the present application provide a blood vessel image analysis method based on super-resolution contrast, comprising:

[0006] obtaining a super-resolution blood vessel image to be analyzed;

[0007] determining a first microvessel region and a second microvessel region from the super-resolution blood vessel image, each of the first microvessel region and the second microvessel region being a partial region of the super-resolution blood vessel image;

[0008] determining a blood perfusion ratio of the first microvessel region and the second microvessel region, and outputting the blood perfusion ratio.

[0009] In a second aspect, embodiments of the present application also provide a blood vessel image analysis method based on super-resolution contrast, comprising:

[0010] obtaining a super-resolution blood vessel image to be analyzed;

[0011] based on a mode selection operation on the super-resolution blood vessel image, selecting a quantitative analysis mode of the super-resolution blood vessel image, the quantitative analysis mode being capable of performing quantitative analysis on microvessels in the super-resolution blood vessel image;

[0012] determine a first microvessel region and a second microvessel region from the super-resolution blood vessel image based on a region division operation triggered under the quantification analysis mode;

[0013] determine a blood perfusion parameter of the first microvessel region and the second microvessel region, and output the blood perfusion parameter.

[0014] In a third aspect, an embodiment of the present application further provides an image analysis device, which comprises a processor, a memory, a computer program stored in the memory and executable by the processor, and a data bus for realizing connection communication between the processor and the memory, wherein the computer program, when executed by the processor, realizes any one of the blood vessel image analysis methods provided by the embodiments of the present application.

[0015] In a fourth aspect, an embodiment of the present application further provides a storage medium for computer readable storage, characterized in that the storage medium stores one or more programs, and the one or more programs are executable by one or more processors to realize any one of the blood vessel image analysis methods provided by the embodiments of the present application.

[0016] The embodiments of the present application provide a blood vessel image analysis method, device and storage medium based on super-resolution contrast, which determines a first microvessel region and a second microvessel region from a super-resolution blood vessel image, determines a blood perfusion ratio of the first microvessel region and the second microvessel region, and outputs the blood perfusion ratio. The embodiments of the present application can determine the blood perfusion ratio of the first microvessel region and the second microvessel region by using the super-resolution blood vessel image obtained by the super-resolution contrast technology, so as to compare and analyze the blood perfusion capacity of the microvessels in the first microvessel region and the second microvessel region. Since the super-resolution blood vessel image has high resolution and good effect of displaying microvessel structure details, the accuracy of the blood perfusion ratio is high, thereby greatly improving the accuracy of the quantification analysis of the microvessels. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 A contrast schematic diagram of the super-resolution blood vessel image provided by the embodiments of the present application is shown in the following figure;

[0018] Figure 2 A step flowchart of the blood vessel image analysis method based on super-resolution contrast provided by the embodiments of the present application is shown in the following figure;

[0019] Figure 3 A schematic diagram of the super-resolution blood vessel image provided by the embodiments of the present application is shown in the following figure;

[0020] Figure 4 Another schematic diagram of the super-resolution blood vessel image provided by the embodiments of the present application is shown in the following figure;

[0021] Figure 5 Another schematic diagram of the super-resolution blood vessel image provided by the embodiment of the present application;

[0022] Figure 6 A schematic diagram of the blood perfusion heat map provided by the embodiment of the present application;

[0023] Figure 7 A schematic diagram of the step flow of another blood vessel image analysis method based on super-resolution contrast provided by the embodiment of the present application;

[0024] Figure 8 A schematic block diagram of an image analysis device provided by the embodiment of the present application. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0026] The flowchart shown in the drawings is only an example and does not necessarily include all the contents and operations / steps, nor does it necessarily be executed in the described order. For example, some operations / steps can be further decomposed, combined or partially merged, so the actual execution order can be changed according to the actual situation.

[0027] It should be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and the appended claims of the present application, unless otherwise clear from the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0028] Microcirculation refers to the blood circulation between arterioles and venules in the vascular network, which is both the terminal part of the circulatory system and an important component of organs. Generally, the blood flow of microcirculation is adapted to the metabolic level of human tissues and organs, maintaining normal life activities and metabolism of the human body. When the metabolism and function of tissues and organs are abnormal, microcirculation will change to a certain extent, so microcirculation is closely related to the occurrence and development of diseases, and has important physiological, pathological, pharmacological and clinical significance, and has important value for early diagnosis and treatment of various diseases. However, due to the diffraction limit of ultrasound, the ability of conventional clinical ultrasound contrast to display microvascular structure details is limited.

[0029] As Figure 1As shown, normal microvessels 10 are mainly composed of capillaries, arterioles and venules, etc., and have good forked branches and ordered structure. In contrast, tumor vessels 20 lack ordered hierarchical structure, and exhibit features of dilation, cystic and uneven diameter in spatial distribution, with chaotic blood flow direction, reduced microflow velocity, and lower overall perfusion rate than normal tissue. In addition, changes in blood perfusion often precede morphological changes, and the total perfusion rate (blood flow rate per unit volume) of many tumors is lower than that of normal tissue. After reasonable treatment, the vascular system can be restored to a relatively normal state. For example, by inhibiting pro-angiogenic factors, pruning of immature blood vessels, reduction of vascular density, diameter and degree of curvature, and reconstruction of the vascular system into a normal vascular network, the blood perfusion in tumor vessels is significantly enhanced.

[0030] Therefore, by quantitatively analyzing the morphological and microflow hemodynamic parameters of microvessels, the scientific research value of microangiography can be explored, such as identification of lesion nature, progress monitoring, and quantitative evaluation of therapeutic effect. However, due to the diffraction limit of conventional clinical ultrasound contrast, the accuracy of quantitative analysis of microvessels is not high.

[0031] Based on this, the embodiments of the present application provide a blood vessel image analysis method based on super-resolution contrast, a device and a storage medium. The blood vessel image analysis method can be applied to an image analysis device, which can be a mobile phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant, a wearable device, and the like.

[0032] Among them, super-resolution contrast imaging (SR-CEUS) is a new type of imaging method with ultra-high spatial resolution. By borrowing the principle of fluorescence microscopic positioning technology in optical super-resolution imaging, the motion trajectory of isolated microbubbles is tracked to construct a blood vessel image with a spatial scale of microns.

[0033] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. In the case of no conflict, the embodiments described below and the features in the embodiments can be combined with each other.

[0034] Please refer to Figure 2 , Figure 2 A step flowchart of a blood vessel image analysis method based on super-resolution contrast provided by the embodiments of the present application is shown.

[0035] As shown in Figure 2 , the blood vessel image analysis method includes steps S101 to S103.

[0036] Step S101, acquiring a super-resolution blood vessel image to be analyzed.

[0037] The super-resolution blood vessel image includes micro-vessels of super-high resolution imaging, and the micro-vessels mainly include capillaries, micro-arteries and micro-veins.

[0038] It should be noted that the super-resolution blood vessel image generated based on the super-resolution contrast technology has high time resolution, can better track the motion trajectory of the contrast agent micro-bubbles, capture complete perfusion details and more abundant image information, and more accurately show the lesion blood vessel morphology and blood perfusion path.

[0039] In the embodiment of the present application, the user can select the probe and the examination mode to determine the micro-vessel region to be observed; then start the contrast mode of the device, inject an appropriate amount of contrast agent into the body, and perform real-time or continuous imaging on the imaging target in the contrast mode; the data acquisition function is called through the device panel or the touch screen button to obtain multiple frames of original image data for imaging processing; after the data acquisition is completed, the system can process the acquired original image data to obtain a super-resolution blood vessel image.

[0040] In the embodiment of the present application, after the user selects the probe and the examination mode, the user can set the acquisition range of the original image data according to the needs, and the acquisition range includes a spatial range and a time range. The spatial range refers to the image region range of the acquired data, and the default spatial range of the acquired image is the entire image region. The time range refers to the acquisition duration. If the time range is not set, the user can decide the timing of ending the acquisition by himself / herself, or the acquisition can be automatically ended according to the micro-bubble concentration or density.

[0041] In the embodiment of the present application, the position of the center of mass of the flowing contrast micro-bubbles in the micro-vessel is located and tracked, and a micro-vessel image with a "microscopic" effect is drawn after a period of accumulation and superposition, so as to break through the original ultrasonic wave diffraction limit and achieve the purpose of super-resolution imaging of micron-level micro-vessels and their blood flow information, thereby realizing super-high resolution imaging of the micro-vessel.

[0042] In the embodiment of the present application, multiple frames of super-resolution blood vessel images are obtained; and one frame of super-resolution blood vessel image is selected from the multiple frames of super-resolution blood vessel images as a super-resolution blood vessel image to be analyzed. The super-resolution blood vessel image is a blood vessel image with a spatial scale in the micron level, and the blood vessel image includes capillaries, micro-arteries and micro-veins. The super-resolution blood vessel image to be analyzed can be manually selected by the user or automatically selected by the device, for example, randomly selected or sequentially selected.

[0043] Step S102: Determine the first microvascular region and the second microvascular region from the super-resolution vascular image. The first microvascular region and the second microvascular region are each a part of the super-resolution vascular image.

[0044] Both the first and second microvascular regions include microvessels imaged at ultra-high resolution. The shapes and areas of the first and second microvascular regions may be the same or different; shapes may include, for example, circles, ellipses, rectangles, polygons, and irregular shapes. The first and second microvascular regions can be automatically identified by the device or manually defined by the user.

[0045] The first and second microvascular regions are each partial regions of a super-resolution vascular image. They can be arranged adjacently or spaced apart. The intersection of the first and second microvascular regions can be an empty set. When the first and second microvascular regions are arranged adjacently, they can combine to form a complete pattern, such as a circle or ellipse.

[0046] In this embodiment, a region of interest (ROI) is identified in a super-resolution vascular image. The central region of the ROI is defined as a first microvascular region, and the edge regions of the ROI excluding the central region are defined as second microvascular regions. It should be noted that the ROI can consist of a central region and edge regions. The ROI can be automatically identified by the device. For example, the ROI may be a microvascular region exhibiting dilation, cystic appearance, and uneven diameter in spatial distribution. By setting corresponding microvascular parameters, the ROI can be accurately identified from the super-resolution vascular image.

[0047] It should be noted that after identifying the region of interest (ROI) in the super-resolution vascular image, it is necessary to determine the central region of the ROI. This central region can be determined based on the centroid or geometric center of the ROI, or it can be determined by combining the set area and area percentage of the ROI. The set area and area percentage can be flexibly set according to the actual situation. For example, the central region can be determined with the centroid of the ROI as the center and the area percentage being 50% of the ROI area, while the other 50% area is the edge region.

[0048] For example, such as Figure 3 As shown, a region of interest 110 is identified in the super-resolution vascular image 100. The central region of the region of interest 110 is defined as the first microvascular region 111, and the edge regions of the region of interest 110 other than the central region are defined as the second microvascular region 112. The areas of the first microvascular region 111 and the second microvascular region 112 are both 50% of the area of ​​the region of interest 110.

[0049] In an embodiment, after identifying the region of interest in the super-resolution blood vessel image, and after generating the first microvessel region or the second microvessel region, the size of the region of interest, the first microvessel region or the second microvessel region can be adjusted based on the user's adjustment operation, including shrinkage adjustment and expansion adjustment.

[0050] In the embodiments of the present application, the first microvessel region and the second microvessel region are determined from the super-resolution blood vessel image based on the region division operation on the super-resolution blood vessel image. It should be noted that the first microvessel region and the second microvessel region can be determined by the user's region division operation on the super-resolution blood vessel image. Based on the region division operation on the super-resolution blood vessel image, the first microvessel region and the second microvessel region to be compared and analyzed can be accurately determined from the super-resolution blood vessel image according to actual conditions, thereby improving the accuracy of the quantitative analysis of the microvessels.

[0051] In an embodiment, the first microvessel region and the second microvessel region are determined from the super-resolution blood vessel image based on the region division operation on the super-resolution blood vessel image, including: determining the first region boundary based on the first region determination operation on the super-resolution blood vessel image; determining the second region boundary according to the first region boundary, the second region boundary being located inside the first region boundary; determining the image region inside the second region boundary as the first microvessel region, and determining the image region between the first region boundary and the second region boundary as the second microvessel region.

[0052] The first region determination operation can be the delineation determination operation of the region of interest in the super-resolution blood vessel image by the user, and the delineation operation tool can support multiple shapes, such as tracing, circle, ellipse, rectangle, etc. The second region boundary can be generated based on the first region boundary, such as the second region boundary being located inside the first region boundary. The second region boundary can be automatically popped up after determining the first region boundary, or can be delineated by the user inside the first region boundary.

[0053] For example, the image region area inside the second region boundary is set to be half of the image region area inside the first region boundary, that is, the second region boundary occupying half of the area can be generated inside the first region boundary, so the areas of the first microvessel region and the second microvessel region are equal. On this basis, the user can adjust the size range of the first region boundary or the second region boundary, thereby adjusting the first microvessel region and the second microvessel region.

[0054] Understandably, the image region within the boundary of the second region is the central region of the super-resolution vascular image, and the image region between the boundary of the first region and the boundary of the second region is the edge region of the super-resolution vascular image. By defining the central region as the first microvascular region and the edge region as the second microvascular region, it is possible to achieve quantitative comparison of microvessels in the central and edge regions, which is helpful for identifying the nature of lesions and monitoring lesion progression.

[0055] For example, such as Figure 4 As shown, based on the user's delineation operation on the super-resolution blood vessel image 100 (first region determination operation), the first region boundary 121 is determined. After determining the first region boundary 121, the second region boundary 122 located inside the first region boundary 121 is automatically popped up; after adjusting the second region boundary 122, the image region within the second region boundary 122 is determined as the first microvascular region 111, and the image region between the first region boundary 121 and the second region boundary 122 is determined as the second microvascular region 112.

[0056] In this embodiment, the sizes of the first region boundary and the second region boundary are adjustable, supporting both shrinking and expansion. The adjustment can be based on area size, pixel size, or area ratio. This area ratio can be the ratio of the area occupied by the first microvascular region to the area occupied by the second microvascular region. When the adjustment is based on area ratio, the sizes of the first and second region boundaries can be adjusted simultaneously, such as shrinking or expanding simultaneously. When the adjustment is based on area size or pixel size, the sizes of the first and second region boundaries can be adjusted independently.

[0057] In this embodiment, the vascular image analysis method further includes: adjusting the boundary of the first region based on the adjustment operation of the first region boundary; updating the second microvascular region according to the adjusted first region boundary; and updating the blood perfusion ratio of the first microvascular region and the second microvascular region. It should be noted that after adjusting the first region boundary, it is necessary to update the second microvascular region (the image region between the first region boundary and the second region boundary) and update the blood perfusion ratio of the first microvascular region and the second microvascular region, thereby enabling convenient adjustment of the first microvascular region and re-determining the quantitative analysis results for microvessels.

[0058] For example, such as Figure 4As shown, the user activates the first region boundary 121, and adjusts the size of the first region boundary 121 based on the adjustment operation on the first region boundary 121, and then determines the image region between the adjusted first region boundary 121 and the second region boundary 122 as a new second microvessel region 112, and updates the blood perfusion ratios of the first microvessel region 111 and the second microvessel region 112.

[0059] In the embodiment of the present application, the blood vessel image analysis method further comprises: adjusting the second region boundary based on the adjustment operation on the second region boundary; updating the first microvessel region and the second microvessel region according to the adjusted second region boundary, and updating the blood perfusion ratios of the first microvessel region and the second microvessel region.

[0060] It should be noted that after adjusting the second region boundary, the first microvessel region and the second microvessel region need to be updated, and the blood perfusion ratios of the first microvessel region and the second microvessel region need to be updated, so that the first microvessel region and the second microvessel region can be conveniently adjusted, and the quantitative analysis result of the microvessel can be re-determined. During the adjustment process, the areas of the first microvessel region and the second microvessel region can be displayed in real time, so as to facilitate the user to observe and operate.

[0061] For example, as shown in FIG. 6, the user activates the second region boundary 122, and adjusts the size of the second region boundary 122 based on the adjustment operation on the second region boundary 122, and then determines the image region within the adjusted second region boundary 122 as a new first microvessel region 111, and determines the image region between the first region boundary 121 and the adjusted second region boundary 122 as a new second microvessel region 112, and updates the blood perfusion ratios of the first microvessel region 111 and the second microvessel region 112. Figure 4 In the embodiment of the present application, after updating the first microvessel region and the second microvessel region according to the adjusted second region boundary, the method further comprises: outputting the areas of the updated first microvessel region and the second microvessel region; or outputting the microbubble densities of the updated first microvessel region and the second microvessel region.

[0062] It should be noted that after updating the first microvessel region and the second microvessel region, the areas of the updated first microvessel region and the second microvessel region can be outputted, or the microbubble densities of the updated first microvessel region and the second microvessel region can be outputted, so that the user can observe the updated areas or microbubble densities in a timely manner, thereby facilitating the user to operate.

[0063]

[0064] ​In an embodiment, the determining the first microvessel region and the second microvessel region from the super-resolution blood vessel image based on the region division operation on the super-resolution blood vessel image comprises: determining the third region boundary based on the second region determination operation on the super-resolution blood vessel image, and determining the image region within the third region boundary as the first microvessel region; and determining the fourth region boundary based on the third region determination operation on the super-resolution blood vessel image, and determining the image region within the fourth region boundary as the second microvessel region.

[0065] The second region determination operation and the third region determination operation can be a user's delineation determination operation on different regions of interest in the super-resolution blood vessel image. The delineation operation tool can support multiple shapes, such as a pen, a circle, an ellipse, a rectangle, etc. The third region boundary and the fourth region boundary can use the same or different delineation operation tools. That is, the third region boundary and the fourth region boundary can be independently generated, and the shapes and sizes of the third region boundary and the fourth region boundary can be the same or different. On this basis, the user can adjust the size range of the third region boundary or the fourth region boundary, thereby adjusting the first microvessel region and the second microvessel region.

[0066] It can be understood that the image region within the third region boundary is the first microvessel region of the super-resolution blood vessel image, and the image region within the fourth region boundary is the second microvessel region of the super-resolution blood vessel image. The first microvessel region and the second microvessel region are respectively the target region and the reference region freely delineated by the user. Through the microvessel quantification comparison of the target region and the reference region, it is helpful for the identification of lesion properties and the monitoring of lesion progression.

[0067] As shown in FIG. 1, the first microvessel region 111 and the second microvessel region 112 are respectively the target region and the reference region freely delineated by the user. Figure 5 As shown in FIG. 1, the first microvessel region 111 and the second microvessel region 112 are respectively the target region and the reference region freely delineated by the user.

[0068] In the embodiment of the present application, the determining the fourth region boundary based on the third region determination operation on the super-resolution blood vessel image comprises: displaying a preset region boundary, the preset region boundary being determined according to the shape and size of the third region boundary; adjusting the position of the preset region boundary according to the position determination operation on the preset region boundary, and determining the preset region boundary after the position adjustment as the fourth region boundary.

[0069] The fourth region boundary can be generated based on the third region boundary. For example, after the third region boundary is determined, a preset region boundary can be automatically popped up. The preset region boundary can have the same shape and size as the third region boundary, or can be different. The user can perform a position determination operation, such as moving, on the preset region boundary, to adjust the position of the preset region boundary, and determine the preset region boundary after the position adjustment as the fourth region boundary.

[0070] For example, as shown in FIG. 12, after the third region boundary 123 is outlined and the first microvessel region 111 is determined, a preset region boundary can be obtained by copying the first microvessel region 111 in the same size and shape. The preset region boundary can be adjusted in size and dragged to a target position as the fourth region boundary 124. The image region in the fourth region boundary 124 is determined as the second microvessel region 112. Figure 5

[0071] In the embodiments of the present application, the third region boundary and the fourth region boundary can be adjusted in size, position, and shape. The size, position, and shape of the third region boundary and the fourth region boundary can be independently adjusted. That is, the adjustment of the third region boundary and the fourth region boundary includes size adjustment, position adjustment, and shape adjustment.

[0072] In the embodiments of the present application, the blood vessel image analysis method further includes: adjusting the third region boundary or the fourth region boundary based on an adjustment operation on the third region boundary or the fourth region boundary; updating the first microvessel region or the second microvessel region according to the adjusted third region boundary or fourth region boundary, and updating the blood perfusion ratio of the first microvessel region and the second microvessel region.

[0073] It should be noted that after the third region boundary is adjusted, the first microvessel region needs to be updated, and the blood perfusion ratio of the first microvessel region and the second microvessel region needs to be updated, so that the first microvessel region can be conveniently adjusted and the quantitative analysis result of the microvessel is re-determined. After the fourth region boundary is adjusted, the second microvessel region also needs to be updated, and the blood perfusion ratio of the first microvessel region and the second microvessel region needs to be updated, so that the second microvessel region can be conveniently adjusted and the quantitative analysis result of the microvessel is re-determined.

[0074] For example, the user activates the third region boundary, and adjusts the size, shape, or position of the third region boundary based on an adjustment operation on the third region boundary, and determines the image region in the adjusted third region boundary as a new first microvessel region. For example, the user activates the fourth region boundary, and adjusts the size, shape, or position of the fourth region boundary based on an adjustment operation on the fourth region boundary, and determines the image region in the adjusted fourth region boundary as a new second microvessel region.​

[0075] In the embodiment of the present application, the blood vessel image analysis method further comprises: adjusting the third region boundary and the fourth region boundary based on the adjusting operation on the third region boundary and the fourth region boundary; updating the first microvessel region and the second microvessel region according to the adjusted third region boundary and the fourth region boundary, and updating the blood perfusion ratio of the first microvessel region and the second microvessel region, so that the first microvessel region and the second microvessel region can be conveniently adjusted, and the quantitative analysis result of the microvessel is re-determined.

[0076] For example, as shown in FIG. 12, the user activates the third region boundary 123, adjusts the size, shape or position of the third region boundary 123 based on the adjusting operation on the third region boundary 123, and determines the image region in the adjusted third region boundary 123 as the new first microvessel region 111. In addition, the user activates the fourth region boundary 124, adjusts the size, shape or position of the fourth region boundary 124 based on the adjusting operation on the fourth region boundary 124, and determines the image region in the adjusted fourth region boundary 124 as the new second microvessel region 112. Figure 5

[0077] In step S103, the blood perfusion ratio of the first microvessel region and the second microvessel region is determined, and the blood perfusion ratio is output.

[0078] The blood perfusion ratio is used to represent the difference in blood perfusion capacity of the first microvessel region and the second microvessel region. The blood perfusion ratio can be determined based on the blood perfusion index of the first microvessel region and the second microvessel region. By outputting the blood perfusion ratio, the quantitative analysis result of the microvessel can be determined. Since the resolution of the super-resolution blood vessel image is high, the effect of displaying the microvessel structure details is good, and therefore the accuracy of the blood perfusion ratio is high, thereby greatly improving the accuracy of the quantitative analysis of the microvessel.

[0079] In the embodiment of the present application, the first blood perfusion index of the first microvessel region and the second blood perfusion index of the second microvessel region are obtained; and the blood perfusion ratio of the first microvessel region and the second microvessel region is determined according to the first blood perfusion index and the second blood perfusion index.

[0080] The first blood perfusion index is used to represent the blood perfusion capacity of the first microvessel region, and the second blood perfusion index is used to represent the blood perfusion capacity of the second microvessel region. The higher the first blood perfusion index or the second blood perfusion index, the stronger the blood perfusion capacity of the corresponding first microvessel region or the second microvessel region. The lower the first blood perfusion index or the second blood perfusion index, the weaker the blood perfusion capacity of the corresponding first microvessel region or the second microvessel region.

[0081] ​It should be noted that according to the blood perfusion ratio of the first microvascular region and the second microvascular region, the blood perfusion capacity of the microvessels in the first microvascular region and the second microvascular region can be compared and analyzed, so that the accuracy of the quantitative analysis of the microvessels can be improved.

[0082] In the embodiment of the present application, the super-resolution blood vessel image can be microhemodynamic imaging, that is, the super-resolution blood vessel image is generated by tracking the microbubble motion trajectory and estimating the moving speed and direction of the microblood flow, and the super-resolution blood vessel image also includes a blood flow speed map or a blood flow direction map.

[0083] Wherein, the blood perfusion index (Perfusion Index, PI) is defined as the product of the average blood flow speed and the area in the microvascular region, which can reflect the blood perfusion capacity. For example, Wherein, is the average blood flow speed in the microvascular region, and area is the area.

[0084] That is, the first blood perfusion index is determined according to the product of the area and the average blood flow speed of the first microvascular region, and the second blood perfusion index is determined according to the product of the area and the average blood flow speed of the second microvascular region. For example, Wherein, PI1 is the first blood perfusion index, is the average blood flow speed of the first microvascular region, and area1 is the area of the first microvascular region. PI2 is the second blood perfusion index, is the average blood flow speed of the second microvascular region, and area2 is the area of the second microvascular region.

[0085] In the embodiment of the present application, the super-resolution blood vessel image can be microhemodynamic imaging, that is, the super-resolution blood vessel image is generated by tracking the microbubble motion trajectory and estimating the moving speed and direction of the microblood flow, and the super-resolution blood vessel image also includes a blood flow speed map or a blood flow direction map.

[0086] Wherein, the blood perfusion index (Perfusion Index, PI) is defined as the product of the average blood flow speed and the area in the microvascular region, which can reflect the blood perfusion capacity. For example, Wherein, is the average blood flow speed in the microvascular region, and VD is the microbubble density, which is used to represent the proportion of the microbubble region in the microvascular region.

[0087] That is, the first blood perfusion index is determined according to the product of the microbubble density and the average blood flow speed of the first microvascular region, and the second blood perfusion index is determined according to the product of the microbubble density and the average blood flow speed of the second microvascular region. For example, Among them, PI-1 is the first blood perfusion index. VD1 represents the average blood flow velocity in the first microvascular region, and VD2 represents the microbubble density in the first microvascular region. PI-2 represents the second blood perfusion index. VD2 represents the average blood flow velocity in the second microvascular region, and VD2 represents the microbubble density in the second microvascular region.

[0088] In this embodiment, the blood perfusion ratio at vascular-related locations can be further quantified based on the blood perfusion index. The blood perfusion ratio can describe the changes in blood perfusion capacity between the first and second microvascular regions. The blood perfusion ratio is helpful for analyzing the monitoring of lesion progression, quantitative evaluation of treatment efficacy, and identification of the nature of the disease, and is of particular research significance for diffuse lesions and liver failure.

[0089] The perfusion index ratio (PIR) is defined as the ratio of the first perfusion index to the second perfusion index. For example, Wherein, PI-1 is the first blood flow perfusion index, and PI-2 is the second blood flow perfusion index. Similarly, the ratio of the second blood flow perfusion index to the first blood flow perfusion index can also be obtained, i.e.

[0090] In other words, the blood perfusion ratio is determined based on the ratio of the first blood perfusion index to the second blood perfusion index, for example, Alternatively, the perfusion ratio can be determined based on the ratio of the second perfusion index to the first perfusion index. For example,

[0091] For example, such as Figures 3 to 5 As shown, the blood perfusion ratio can be the ratio of the first blood perfusion index of the first microvascular region 111 to the second blood perfusion index of the second microvascular region 112, or the blood perfusion ratio can be the ratio of the second blood perfusion index of the second microvascular region 112 to the first blood perfusion index of the first microvascular region 111.

[0092] In this embodiment of the application, when outputting the blood perfusion index, other related parameters may also be output, such as the area of ​​the first microvascular region, the area of ​​the second microvascular region, the total area of ​​the first microvascular region and the second microvascular region, the first blood perfusion index of the first microvascular region, the second blood perfusion index of the second microvascular region, and the total blood perfusion index of the first microvascular region and the second microvascular region.

[0093] In this embodiment, based on the output setting operation of area parameters, at least one area parameter is controlled to be output or stopped; wherein, the area parameters include: the area of ​​the first microvascular region, the area of ​​the second microvascular region, and the total area of ​​the first and second microvascular regions. It should be noted that the output setting operation of area parameters supports the selection of displaying or hiding the area parameters, improving the flexibility of data output.

[0094] In this embodiment, based on the output setting operation of the blood perfusion index, at least one blood perfusion index is controlled to be output or stopped; wherein, the blood perfusion index includes: a first blood perfusion index of a first microvascular region, a second blood perfusion index of a second microvascular region, and a total blood perfusion index of the first and second microvascular regions. It should be noted that the output setting operation of the blood perfusion index supports the selection of displaying or hiding the blood perfusion index, improving the flexibility of data output.

[0095] In this embodiment of the application, the vascular image analysis method further includes: dividing the first microvascular region and the second microvascular region into blocks to obtain multiple block regions; determining the blood perfusion index of each block region based on the sliding window algorithm; determining the block color of each block region based on the blood perfusion index of each block region; generating a blood perfusion heat map based on the block color of each block region, and outputting the blood perfusion heat map.

[0096] It should be noted that by calculating the blood perfusion index of multiple segmented regions and generating and outputting a blood perfusion heatmap, the differences in blood perfusion capacity between different segmented regions can be visually observed. The blood perfusion index can be divided into multiple score ranges, with different score ranges corresponding to different region colors.

[0097] For example, such as Figure 6 As shown, the perfusion heatmap 200 is divided into 5x5 windows, and the perfusion index is calculated for each window by sliding with a window step size of 2. The darker the color of the corresponding block in the perfusion heatmap 200, the higher the perfusion index value of the corresponding area. Conversely, the lighter the color of the corresponding block in the perfusion heatmap 200, the lower the perfusion index value of the corresponding area.

[0098] In this embodiment of the application, the blood perfusion heatmap marks the regional boundaries of the first microvascular region and the second microvascular region; the vascular image analysis method further includes: updating the first microvascular region and the second microvascular region based on the adjustment operation of the regional boundaries, and updating the blood perfusion ratio of the first microvascular region and the second microvascular region.

[0099] It should be noted that after the blood perfusion thermal map is output, the region boundary of the first microvessel region or the second microvessel region in the blood perfusion thermal map can be adjusted, for example, expanded and shrunk, so as to update the first microvessel region and the second microvessel region, and update the blood perfusion ratios of the first microvessel region and the second microvessel region, so that the second microvessel region can be conveniently adjusted, and the quantitative analysis result of the microvessel is re-determined.

[0100] As shown in the example of FIG. 2, the blood perfusion thermal map 200 is marked with the region boundary 121 of the first microvessel region and the region boundary 122 of the second microvessel region. Based on the adjustment operation on the region boundary 121 or the region boundary 122, the first microvessel region and the second microvessel region are updated, and the blood perfusion ratios of the first microvessel region and the second microvessel region are updated. Figure 6

[0101] In the embodiment of the present application, the blood perfusion thermal map is marked with the region boundary of the first microvessel region and the region boundary of the second microvessel region; the blood vessel image analysis method further includes: based on the display setting operation on the region boundary, controlling the region boundary to be displayed or hidden.

[0102] It should be noted that the region boundary of the first microvessel region or the second microvessel region in the blood perfusion thermal map can be displayed and set, such as controlling the region boundary of the first microvessel region or the second microvessel region to be displayed or hidden, so as to improve the operation convenience.

[0103] As shown in the example of FIG. 2, the blood perfusion thermal map 200 is marked with the region boundary 121 of the first microvessel region and the region boundary 122 of the second microvessel region. Based on the display setting operation on the region boundary 121 or the region boundary 122, the region boundary 121 or the region boundary 122 is controlled to be displayed or hidden. Figure 6 In the embodiment of the present application, the blood vessel image analysis method further includes: based on the triggered saving operation, saving the target parameter. Or, based on the triggered export operation, exporting the target parameter. Wherein, the target parameter includes at least one of the following: the area of the first microvessel region, the area of the second microvessel region, the total area of the first microvessel region and the second microvessel region, the first blood perfusion index of the first microvessel region, the second blood perfusion index of the second microvessel region, the total blood perfusion index of the first microvessel region and the second microvessel region, the blood perfusion ratio of the first microvessel region to the second microvessel region, and the blood perfusion thermal map.

[0104]

[0105] ​​The vascular image analysis method provided in the above embodiments determines a first microvascular region and a second microvascular region from a super-resolution vascular image, thereby determining the blood perfusion ratio between the first and second microvascular regions and outputting the blood perfusion ratio. This application embodiment can utilize super-resolution vascular images obtained through super-resolution angiography to determine the blood perfusion ratio between the first and second microvascular regions, facilitating a comparative analysis of the blood perfusion capacity of microvessels in the first and second microvascular regions. Because the super-resolution vascular image has high resolution and effectively displays the details of microvascular structures, the obtained blood perfusion ratio is accurate, thus greatly improving the accuracy of quantitative analysis of microvessels.

[0106] Please refer to Figure 7 , Figure 7 This is a flowchart illustrating the steps of another vascular image analysis method provided in an embodiment of this application.

[0107] like Figure 7 As shown, the vascular image analysis method includes steps S201 to S204.

[0108] Step S201: Obtain the super-resolution blood vessel image to be analyzed.

[0109] The super-resolution vascular image to be analyzed can be one or more. When there are multiple super-resolution vascular images, they can be acquired sequentially. The super-resolution vascular image to be analyzed is obtained by super-resolution imaging of the microvascular region to be observed using super-resolution angiography.

[0110] In this embodiment, multiple frames of super-resolution vascular images are acquired; one frame of super-resolution vascular image is selected from the multiple frames as the super-resolution vascular image to be analyzed. The super-resolution vascular image is a vascular image with a spatial scale at the micrometer level, including capillaries, arterioles, and venules.

[0111] Step S202: Based on the mode selection operation of the super-resolution vascular image, select the quantization analysis mode of the super-resolution vascular image. In the quantization analysis mode, the microvessels in the super-resolution vascular image can be quantified and analyzed.

[0112] The mode selection operation is used to choose the quantization analysis mode for the super-resolution vascular image. The quantization analysis mode can be preset according to the actual situation. Different quantization analysis modes can perform different methods of quantification analysis on microvessels in the super-resolution vascular image.

[0113] In the embodiment of the present application, the quantitative analysis mode includes a double-ring analysis mode, in which the first microvessel region and the second microvessel region can be constructed into a double-ring structure in a containing relationship for quantitative analysis. That is, the first microvessel region and the second microvessel region are constructed into a double-ring structure in a containing relationship means that the second microvessel region is located inside the first microvessel region, or the first microvessel region is located inside the second microvessel region. Quantitative analysis of the first microvessel region and the second microvessel region based on the double-ring structure can realize quantitative comparison of microvessels in the central region and the edge region, which is helpful for identification of lesion properties and monitoring of lesion progression.

[0114] It should be noted that in the double-ring analysis mode, the size of the first microvessel region and the second microvessel region is adjustable, supporting shrinkage and expansion. The adjustment mode can be based on area size adjustment, pixel size adjustment, or area proportion adjustment. When the adjustment mode is based on area proportion adjustment, the size of the first microvessel region and the second microvessel region can be adjusted simultaneously, such as simultaneous shrinkage or simultaneous expansion. When the adjustment mode is based on area size adjustment or pixel size adjustment, the size of the first microvessel region and the second microvessel region can be independently adjusted.

[0115] In the embodiment of the present application, the quantitative analysis mode includes a free analysis mode, in which the first microvessel region and the second microvessel region can be constructed into any structure for quantitative analysis. That is, the first microvessel region and the second microvessel region are constructed into any structure means that the first microvessel region and the second microvessel region can be independently constructed, and the shape and size of the first microvessel region and the second microvessel region can be the same or different. Quantitative analysis of the first microvessel region and the second microvessel region based on any structure can realize quantitative comparison of microvessels in the target region and the reference region, which is helpful for identification of lesion properties and monitoring of lesion progression.

[0116] It should be noted that in the free analysis mode, the size, position, and shape of the first microvessel region and the second microvessel region are adjustable. The size, position, and shape of the first microvessel region and the second microvessel region can be independently adjusted. That is, the adjustment mode of the first microvessel region and the second microvessel region includes size adjustment, position adjustment, and shape adjustment.

[0117] In step S203, the first microvessel region and the second microvessel region are determined from the super-resolution blood vessel image based on the region division operation triggered in the quantitative analysis mode.

[0118] It should be noted that the first and second microvascular regions can be determined by the user's region segmentation operation on the super-resolution vascular image. Based on the region segmentation operation of the super-resolution vascular image in the quantitative analysis mode, the first and second microvascular regions to be compared and analyzed can be accurately determined from the super-resolution vascular image according to the actual situation, thereby improving the accuracy of the quantitative analysis of microvessels.

[0119] In this embodiment, the quantification analysis mode includes a dual-ring analysis mode; based on the region division operation triggered under the quantification analysis mode, determining the first microvascular region and the second microvascular region from the super-resolution vascular image includes: determining the boundary of the first region based on the first region determination operation of the super-resolution vascular image; determining the boundary of the second region according to the boundary of the first region; the boundary of the second region is located inside the boundary of the first region; determining the image region within the boundary of the second region as the first microvascular region, and determining the image region between the boundary of the first region and the boundary of the second region as the second microvascular region.

[0120] The first region determination operation can be a user-defined delineation of a region of interest in a super-resolution vascular image. The delineation tool supports various shapes, such as tracing, circles, ellipses, and rectangles. The second region boundary can be generated based on the first region boundary, such as the second region boundary being located inside the first region boundary. This second region boundary can either pop up automatically after the first region boundary is determined, or it can be drawn by the user within the first region boundary. Based on this, the user can adjust the size range of either the first or second region boundary to adjust the first and second microvascular regions.

[0121] Understandably, the image region within the boundary of the second region is the central region of the super-resolution vascular image, and the image region between the boundary of the first region and the boundary of the second region is the edge region of the super-resolution vascular image. By defining the central region as the first microvascular region and the edge region as the second microvascular region, it is possible to achieve quantitative comparison of microvessels in the central and edge regions, which is helpful for identifying the nature of lesions and monitoring lesion progression.

[0122] For example, such as Figure 4 As shown, based on the user's first delineation operation (first region determination operation) on the super-resolution blood vessel image 100, a first region boundary 121 is determined. Based on the user's second delineation operation on the super-resolution blood vessel image 100, a second region boundary 122 is generated within the first region boundary 121. After adjusting the second region boundary 122, the image region within the second region boundary 122 is determined as the first microvascular region 111, and the image region between the first region boundary 121 and the second region boundary 122 is determined as the second microvascular region 112.

[0123] In an embodiment, the size of the first region boundary and the second region boundary is adjustable, supporting inward shrinking and expansion. The adjustment manner can be based on area size adjustment, pixel size adjustment, or area proportion adjustment. The area proportion can be the proportion of the area occupied by the first microvessel region and the second microvessel region. When the adjustment manner is based on area proportion adjustment, the size of the first region boundary and the second region boundary can be adjusted simultaneously, such as simultaneously shrinking or simultaneously expanding. When the adjustment manner is area size adjustment or pixel size adjustment, the size of the first region boundary and the second region boundary can be independently adjusted.

[0124] In an embodiment, the blood vessel image analysis method further comprises: adjusting the second region boundary based on the adjustment operation on the second region boundary; updating the first microvessel region and the second microvessel region according to the adjusted second region boundary, and updating the blood perfusion parameters of the first microvessel region and the second microvessel region.

[0125] It should be noted that after adjusting the first region boundary, the first microvessel region needs to be updated, and the blood perfusion parameters of the first microvessel region and the second microvessel region need to be updated, so that the first microvessel region can be conveniently adjusted and the quantitative analysis result of the microvessel can be re-determined.

[0126] In an embodiment, the blood vessel image analysis method further comprises: adjusting the second region boundary based on the adjustment operation on the second region boundary; updating the first microvessel region and the second microvessel region according to the adjusted second region boundary, and updating the blood perfusion parameters of the first microvessel region and the second microvessel region.

[0127] It should be noted that after adjusting the second region boundary, the first microvessel region and the second microvessel region need to be updated, and the blood perfusion parameters of the first microvessel region and the second microvessel region need to be updated, so that the first microvessel region and the second microvessel region can be conveniently adjusted, and the quantitative analysis result of the microvessel can be re-determined. During the adjustment process, the areas of the first microvessel region and the second microvessel region can be displayed in real time, thereby facilitating user operation.

[0128] In an embodiment, after updating the first microvessel region and the second microvessel region according to the adjusted second region boundary, the method further comprises: outputting the areas of the updated first microvessel region and the second microvessel region; or outputting the microbubble densities of the updated first microvessel region and the second microvessel region.

[0129] It should be noted that after the first microvessel region and the second microvessel region are updated, the area of the updated first microvessel region and the second microvessel region can be output, or the microbubble density of the updated first microvessel region and the second microvessel region can be output, so that the user can observe the updated area or microbubble density and other parameters in a timely manner, thereby facilitating user operation.

[0130] In the embodiment of the present application, the quantitative analysis mode includes a free analysis mode; based on the region division operation triggered in the quantitative analysis mode, the first microvessel region and the second microvessel region are determined from the super-resolution blood vessel image, including: based on the second region determination operation on the super-resolution blood vessel image, the third region boundary is determined, and the image region within the third region boundary is determined as the first microvessel region; and based on the third region determination operation on the super-resolution blood vessel image, the fourth region boundary is determined, and the image region within the fourth region boundary is determined as the second microvessel region.

[0131] Wherein, the second region determination operation and the third region determination operation can be a user's delineation determination operation on different regions of interest in the super-resolution blood vessel image. Wherein, the delineation operation tool can support multiple shapes, such as tracing, circle, ellipse, rectangle, etc., and the third region boundary and the fourth region boundary can use the same or different delineation operation tools. That is, the third region boundary and the fourth region boundary can be independently generated, and the shape and size of the third region boundary and the fourth region boundary can be the same or different. On this basis, the user can adjust the size range of the third region boundary or the fourth region boundary, thereby adjusting the first microvessel region and the second microvessel region.

[0132] It can be understood that the image region within the third region boundary is the first microvessel region of the super-resolution blood vessel image, and the image region within the fourth region boundary is the second microvessel region of the super-resolution blood vessel image. The first microvessel region and the second microvessel region are respectively the target region and the reference region freely delineated by the user, and through the microvessel quantification comparison of the target region and the reference region, it is helpful for the identification of lesion properties and the monitoring of lesion progression.

[0133] As shown in Figure 5 Based on the user's delineation operation (second region determination operation) on the super-resolution blood vessel image 100, the third region boundary 123 is determined, and the image region within the third region boundary 123 is determined as the first microvessel region 111. Based on the user's delineation operation (third region determination operation) on the super-resolution blood vessel image 100, the fourth region boundary 124 is determined, and the image region within the fourth region boundary 124 is determined as the second microvessel region 112.

[0134] In one embodiment, determining the boundary of a fourth region based on a third region determination operation of a super-resolution vascular image includes: displaying a preset region boundary, the preset region boundary being determined according to the shape and size of the third region boundary; adjusting the position of the preset region boundary according to a position determination operation of the preset region boundary, and determining the adjusted preset region boundary as the fourth region boundary.

[0135] The fourth region boundary can be generated based on the third region boundary. For example, after determining the third region boundary, a preset region boundary can automatically pop up. This preset region boundary can have the same shape and size as the third region boundary, or it can be different. Users can perform position determination operations such as moving the preset region boundary to adjust its position, and then define the adjusted preset region boundary as the fourth region boundary.

[0136] It should be noted that the size, position, and shape of the third and fourth region boundaries are adjustable. The size, position, and shape of the third and fourth region boundaries can be adjusted independently. In other words, the adjustment methods for the third and fourth region boundaries include size adjustment, position adjustment, and shape adjustment.

[0137] For example, such as Figure 5 As shown, after outlining the third region boundary 123 and determining the first microvascular region 111, the preset region boundary can be obtained by copying the same size and shape based on the first microvascular region 111. The size of the preset region boundary is adjusted and dragged to the target position as the fourth region boundary 124, and the image region within the fourth region boundary 124 is determined as the second microvascular region 112.

[0138] In one embodiment, the vascular image analysis method further includes: adjusting the boundary of the third region or the boundary of the fourth region based on the adjustment operation of the boundary of the third region or the boundary of the fourth region; updating the first microvascular region or the second microvascular region according to the adjusted boundary of the third region or the boundary of the fourth region, and updating the blood perfusion parameters of the first microvascular region and the second microvascular region.

[0139] It should be noted that after adjusting the boundary of the third region, it is necessary to update the blood perfusion parameters of the first microvascular region, as well as the first and second microvascular regions. This allows for convenient adjustment of the first microvascular region and a re-determination of the quantitative analysis results for microvessels. Similarly, after adjusting the boundary of the fourth region, it is necessary to update the second microvascular region, as well as the blood perfusion parameters of the first and second microvascular regions. This allows for convenient adjustment of the second microvascular region and a re-determination of the quantitative analysis results for microvessels.

[0140] In step S204, a blood perfusion parameter of the first microvascular region and the second microvascular region is determined, and the blood perfusion parameter is output.

[0141] In the embodiments of the present application, the blood perfusion parameter includes at least one of the following: a first blood perfusion index of the first microvascular region, a second blood perfusion index of the second microvascular region, a total blood perfusion index of the first microvascular region and the second microvascular region, and a blood perfusion ratio of the first microvascular region and the second microvascular region.

[0142] The blood perfusion index can reflect the blood perfusion capacity or the activity of the microvessels. The blood perfusion ratio is used to represent the difference in blood perfusion capacity between the first microvascular region and the second microvascular region. The blood perfusion ratio can be determined based on the blood perfusion indexes of the first microvascular region and the second microvascular region. By outputting the blood perfusion ratio, the quantitative analysis result of the microvessels can be determined. Since the resolution of the super-resolution blood vessel image is high, the effect of displaying the microvascular structure details is good, and therefore the accuracy of the blood perfusion ratio is high, thereby greatly improving the accuracy of the quantitative analysis of the microvessels.

[0143] In the embodiments of the present application, the super-resolution blood vessel image can be a microhemodynamic imaging, that is, the super-resolution blood vessel image is generated by tracking the microbubble motion trajectory and estimating the moving speed and direction of the microblood flow. The super-resolution blood vessel image also includes a blood flow speed map or a blood flow direction map.

[0144] The blood perfusion index (Perfusion Index, PI) is defined as the product of the average blood flow speed and the area in the microvascular region, and can reflect the blood perfusion capacity. For example, wherein, is the average blood flow speed in the microvascular region, and area is the area.

[0145] That is, the first blood perfusion index is determined according to the product of the area and the average blood flow speed of the first microvascular region, and the second blood perfusion index is determined according to the product of the area and the average blood flow speed of the second microvascular region. For example, wherein, PI1 is the first blood perfusion index, is the average blood flow speed of the first microvascular region, and area1 is the area of the first microvascular region. PI2 is the second blood perfusion index, is the average blood flow speed of the second microvascular region, and area2 is the area of the second microvascular region.

[0146] In the embodiments of the present application, the super-resolution blood vessel image can be microvascular morphology imaging, that is, the super-resolution blood vessel image is generated by tracking the accumulation of microbubbles and estimating the blood flow state, and the super-resolution blood vessel image can also be referred to as a blood flow density map.

[0147] wherein a perfusion index (PI) is defined as the product of the average blood flow velocity and the microbubble density in the microvascular region, reflecting the activity of the microvessels. For example, wherein, is the average blood flow velocity in the microvascular region, and VD is the microbubble density, which is used to represent the proportion of the microbubble region to the microvascular region.

[0148] That is, the first perfusion index is determined according to the product of the microbubble density and the average blood flow velocity of the first microvascular region, and the second perfusion index is determined according to the product of the microbubble density and the average blood flow velocity of the second microvascular region. For example, wherein PI-1 is the first perfusion index, is the average blood flow velocity of the first microvascular region, and VD1 is the microbubble density of the first microvascular region. PI-2 is the second perfusion index, is the average blood flow velocity of the second microvascular region, and VD2 is the microbubble density of the second microvascular region.

[0149] In the embodiments of the present application, the perfusion index can be used to further quantify the perfusion ratio of the blood flow at the blood vessel related position. The perfusion ratio can describe the change of the perfusion capacity of the first microvascular region and the second microvascular region. The perfusion ratio is helpful for analyzing the monitoring of lesion progression, the quantitative evaluation of curative effect, the identification of nature, etc., and has important research significance for diffuse lesions, liver failure, etc.

[0150] wherein a perfusion index ratio (PIR) is defined as the ratio of the first perfusion index to the second perfusion index. For example, wherein PI-1 is the first perfusion index, and PI-2 is the second perfusion index. Similarly, the ratio of the second perfusion index to the first perfusion index can also be obtained, that is,

[0151] That is, the perfusion ratio is determined according to the ratio of the first perfusion index to the second perfusion index, for example, Alternatively, the perfusion ratio is determined according to the ratio of the second perfusion index to the first perfusion index. For example,

[0152] In the embodiments of the present application, when the blood perfusion index is output, other related parameters can also be output, such as the area of the first microvessel region, the area of the second microvessel region, the total area of the first microvessel region and the second microvessel region, the first blood perfusion index of the first microvessel region, the second blood perfusion index of the second microvessel region, and the total blood perfusion index of the first microvessel region and the second microvessel region.

[0153] In the embodiments of the present application, based on the output setting operation of the area parameter, at least one area parameter is controlled to be output or stopped from being output; wherein the area parameter includes: the area of the first microvessel region, the area of the second microvessel region, and the total area of the first microvessel region and the second microvessel region. It should be noted that through the output setting operation of the area parameter, the selection of output display or hiding of the area parameter is supported, and the flexibility of data output is improved.

[0154] In the embodiments of the present application, based on the output setting operation of the blood perfusion index, at least one blood perfusion index is controlled to be output or stopped from being output; wherein the blood perfusion index includes: the first blood perfusion index of the first microvessel region, the second blood perfusion index of the second microvessel region, and the total blood perfusion index of the first microvessel region and the second microvessel region. It should be noted that through the output setting operation of the blood perfusion index, the selection of output display or hiding of the blood perfusion index is supported, and the flexibility of data output is improved.

[0155] In the embodiments of the present application, the blood vessel image analysis method further includes: performing block processing on the first microvessel region and the second microvessel region to obtain a plurality of block regions; determining the blood perfusion index of each block region based on a sliding window algorithm; determining the block color of each block region based on the blood perfusion index of each block region; generating a blood perfusion heat map according to the block color of each block region, and outputting the blood perfusion heat map.

[0156] It should be noted that by calculating the blood perfusion index of a plurality of block regions through block processing, a blood perfusion heat map is generated and output, and the differences in blood perfusion capacity of different block regions can be observed intuitively. The blood perfusion index can be divided into a plurality of score segments, and different score segments correspond to different block colors. For example, the block size can be set to a 5*5 window, and the window step is 2, and the blood perfusion index under each window is calculated by sliding. The larger the value of the blood perfusion index, the deeper the corresponding block color. The smaller the value of the blood perfusion index of the block region, the lighter the corresponding block color.

[0157] In this embodiment of the application, the blood perfusion heatmap marks the regional boundaries of the first microvascular region and the second microvascular region; the vascular image analysis method further includes: updating the first microvascular region and the second microvascular region based on the adjustment operation of the regional boundaries, and updating the blood perfusion parameters of the first microvascular region and the second microvascular region.

[0158] It should be noted that after outputting the blood perfusion heatmap, the regional boundaries of the first or second microvascular region in the blood perfusion heatmap can be adjusted, such as by expanding or shrinking, thereby updating the first and second microvascular regions, as well as updating the blood perfusion ratio of the first and second microvascular regions. This allows for convenient adjustment of the second microvascular region and redetering the quantitative analysis results for microvessels.

[0159] For example, such as Figure 6 As shown, the blood perfusion heatmap 200 is marked with the region boundary 121 of the first microvascular region and the region boundary 122 of the second microvascular region. Based on the adjustment operation of the region boundary 121 or the region boundary 122, the first microvascular region and the second microvascular region are updated, and the blood perfusion ratio of the first microvascular region and the second microvascular region is updated.

[0160] In this embodiment of the application, the blood perfusion heat map marks the boundary between the first microvascular region and the second microvascular region; the vascular image analysis method further includes: controlling the display or hiding of the boundary based on the display setting operation of the boundary.

[0161] It should be noted that the display settings for the boundaries of the first or second microvascular region in the blood perfusion heatmap can be configured, such as controlling the display or hiding of the boundaries of the first or second microvascular region, thereby improving operational convenience.

[0162] For example, such as Figure 6 As shown, the blood perfusion heatmap 200 is marked with the region boundary 121 of the first microvascular region and the region boundary 122 of the second microvascular region. Based on the display setting operation of region boundary 121 or region boundary 122, the region boundary 121 or region boundary 122 is controlled to be displayed or hidden.

[0163] In this embodiment, the vascular image analysis method further includes: saving target parameters based on a triggered save operation; or exporting target parameters based on a triggered export operation. The target parameters include at least one of the following: the area of ​​a first microvascular region, the area of ​​a second microvascular region, the total area of ​​the first and second microvascular regions, a first blood perfusion index of the first microvascular region, a second blood perfusion index of the second microvascular region, the total blood perfusion index of the first and second microvascular regions, the blood perfusion ratio of the first and second microvascular regions, and a blood perfusion heatmap.

[0164] The vascular image analysis method provided in the above embodiments acquires a super-resolution vascular image to be analyzed; based on a mode selection operation on the super-resolution vascular image, a quantitative analysis mode for the super-resolution vascular image is selected, which enables quantitative analysis of microvessels in the super-resolution vascular image; based on a region segmentation operation triggered in the quantitative analysis mode, a first microvessel region and a second microvessel region are determined from the super-resolution vascular image; blood perfusion parameters of the first microvessel region and the second microvessel region are determined and output. This embodiment of the application can utilize super-resolution vascular images obtained by super-resolution angiography to determine the blood perfusion parameters of the first microvessel region and the second microvessel region, facilitating a comparative analysis of the blood perfusion capacity of microvessels in the first and second microvessel regions. Because the super-resolution vascular image has high resolution and displays microvascular structural details well, the obtained blood perfusion parameters are more accurate, thereby greatly improving the accuracy of the quantitative analysis of microvessels.

[0165] Please see Figure 8 , Figure 8 This is a schematic block diagram of an image analysis device provided in an embodiment of this application.

[0166] like Figure 8 As shown, the image analysis device 300 includes a processor 301 and a memory 302, which are connected by a bus 303, such as an I2C (Inter-integrated Circuit) bus.

[0167] Specifically, the processor 301 is configured to provide computing and control capabilities to support the operation of the entire image analysis apparatus. The processor 301 can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0168] Specifically, the memory 302 can be a Flash chip, a read-only memory (ROM) disk, an optical disk, a U disk or a mobile hard disk, etc.

[0169] Those skilled in the art can understand that, Figure 8 The structure shown in the figure is only a block diagram of part of the structure related to the embodiments of the present application, and does not constitute a limitation on the image analysis apparatus to which the embodiments of the present application are applied. The specific image analysis apparatus can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0170] The processor is configured to run a computer program stored in the memory, and implement any one of the blood vessel image analysis methods provided by the embodiments of the present application when the computer program is executed.

[0171] In the embodiments of the present application, the processor is configured to run a computer program stored in the memory, and implement the following steps when the computer program is executed:

[0172] obtain a super-resolution blood vessel image to be analyzed;

[0173] determine a first microvessel region and a second microvessel region from the super-resolution blood vessel image, the first microvessel region and the second microvessel region each being a partial region of the super-resolution blood vessel image;

[0174] determine a blood perfusion ratio of the first microvessel region and the second microvessel region, and output the blood perfusion ratio.

[0175] In the embodiments of the present application, the processor is configured to run a computer program stored in the memory, and implement the following steps when the computer program is executed:

[0176] obtaining a super-resolution blood vessel image to be analyzed;

[0177] based on a mode selection operation on the super-resolution blood vessel image, selecting a quantitative analysis mode of the super-resolution blood vessel image, in which the microvessels in the super-resolution blood vessel image can be quantitatively analyzed;

[0178] based on a region division operation triggered in the quantitative analysis mode, determining a first microvessel region and a second microvessel region from the super-resolution blood vessel image;

[0179] determining blood perfusion parameters of the first microvessel region and the second microvessel region, and outputting the blood perfusion parameters.

[0180] It should be noted that, for the convenience and brevity of description, the specific working process of the image analysis device described above can be clearly understood by those skilled in the art, and the corresponding process in the foregoing blood vessel image analysis method embodiments can be referred to, which will not be described here.

[0181] The embodiments of the present application also provide a storage medium for computer readable storage, the storage medium storing one or more programs, which can be executed by one or more processors to implement the steps of any blood vessel image analysis method provided by the embodiments of the present application.

[0182] The storage medium can be an internal storage unit of the image analysis device, such as a hard disk or a memory of the image analysis device. The storage medium can also be an external storage device of the image analysis device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc.

[0183] Those skilled in the art can understand that all or some of the steps in the method disclosed above, the functions of the modules / units in the system and the device can be implemented as software, firmware, hardware or a combination thereof. In the hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component can have multiple functions, or one function or step can be performed by several physical components in cooperation. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer readable medium, which can include computer storage media (or non-transitory media) and communication media (or transitory media).

[0184] As is well known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term "modulated data signal" means a signal that has one or more of its characteristics changed or set in a manner so as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media.

[0185] The above-mentioned sequence numbers of the embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments. The above description is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method of blood vessel image analysis based on super-resolution contrast, characterized by, The method comprises: acquiring a super-resolution blood vessel image to be analyzed; determining a first microvessel region and a second microvessel region from the super-resolution blood vessel image, each of the first microvessel region and the second microvessel region being a partial region of the super-resolution blood vessel image; determining a blood perfusion ratio of the first microvessel region and the second microvessel region, and outputting the blood perfusion ratio.

2. The blood vessel image analysis method according to claim 1, characterized by, The determination of the blood perfusion ratio of the first microvessel region and the second microvessel region comprises: acquiring a first blood perfusion index of the first microvessel region and a second blood perfusion index of the second microvessel region; determining the blood perfusion ratio of the first microvessel region and the second microvessel region according to the first blood perfusion index and the second blood perfusion index.

3. The blood vessel image analysis method according to claim 2, characterized by, The first blood perfusion index is determined according to the product of the area and the average blood flow velocity of the first microvessel region, and the second blood perfusion index is determined according to the product of the area and the average blood flow velocity of the second microvessel region.

4. The blood vessel image analysis method according to claim 2, characterized by, The first blood perfusion index is determined according to the product of the microbubble density and the average blood flow velocity of the first microvessel region, and the second blood perfusion index is determined according to the product of the microbubble density and the average blood flow velocity of the second microvessel region.

5. The blood vessel image analysis method according to claim 2, characterized by, The blood perfusion ratio is determined according to the ratio of the first blood perfusion index to the second blood perfusion index; or The blood perfusion ratio is determined according to the ratio of the second blood perfusion index to the first blood perfusion index.

6. The blood vessel image analysis method according to claim 2, characterized by, The method further comprises: controlling at least one blood perfusion index to be output or stopped to be output based on the output setting operation of the blood perfusion index, wherein the blood perfusion index comprises: a first blood perfusion index of the first microvessel region, a second blood perfusion index of the second microvessel region, and a total blood perfusion index of the first microvessel region and the second microvessel region.

7. The blood vessel image analysis method according to any one of claims 1 to 6, characterized by, The determination of the first microvessel region and the second microvessel region from the super-resolution blood vessel image comprises: determining the first microvessel region and the second microvessel region from the super-resolution blood vessel image based on a region division operation of the super-resolution blood vessel image; or identifying a region of interest in the super-resolution blood vessel image, determining a central region of the region of interest as the first microvessel region, and determining an edge region of the region of interest other than the central region as the second microvessel region.

8. The blood vessel image analysis method according to claim 7, characterized by, The determination of the first microvessel region and the second microvessel region from the super-resolution blood vessel image based on the region division operation of the super-resolution blood vessel image comprises: determining a first region boundary based on a first region determination operation of the super-resolution blood vessel image; determining a second region boundary inside the first region boundary according to the first region boundary; determining an image region inside the second region boundary as the first microvessel region, and determining an image region between the first region boundary and the second region boundary as the second microvessel region.

9. The blood vessel image analysis method according to claim 8, characterized by, The method further comprises: adjusting the second region boundary based on an adjustment operation of the second region boundary; updating the first microvascular region and the second microvascular region according to the adjusted second region boundary, and updating blood perfusion ratios of the first microvascular region and the second microvascular region.

10. The blood vessel image analysis method according to claim 9, characterized by, after the updating the first microvascular region and the second microvascular region according to the adjusted second region boundary, the method further comprises: outputting areas of the updated first microvascular region and the second microvascular region; or outputting microbubble densities of the updated first microvascular region and the second microvascular region.

11. The blood vessel image analysis method according to claim 7, characterized by, the determining the first microvascular region and the second microvascular region from the super-resolution blood vessel image based on the region division operation on the super-resolution blood vessel image comprises: determining a third region boundary based on a second region determination operation on the super-resolution blood vessel image, and determining an image region within the third region boundary as the first microvascular region; and determining a fourth region boundary based on a third region determination operation on the super-resolution blood vessel image, and determining an image region within the fourth region boundary as the second microvascular region.

12. The blood vessel image analysis method according to claim 11, characterized by, the determining the fourth region boundary based on the third region determination operation on the super-resolution blood vessel image comprises: displaying a preset region boundary, the preset region boundary being determined according to a shape and a size of the third region boundary; adjusting a position of the preset region boundary according to a position determination operation on the preset region boundary, and determining the preset region boundary after the position adjustment as the fourth region boundary.

13. The blood vessel image analysis method according to claim 11, characterized by, the method further comprises: adjusting the third region boundary or the fourth region boundary based on an adjustment operation on the third region boundary or the fourth region boundary; updating the first microvascular region or the second microvascular region according to the adjusted third region boundary or the fourth region boundary, and updating blood perfusion ratios of the first microvascular region and the second microvascular region.

14. The blood vessel image analysis method according to any one of claims 1 to 6, characterized by, the method further comprises: performing block processing on the first microvascular region and the second microvascular region to obtain a plurality of block regions; determining a blood perfusion index of each of the block regions based on a sliding window algorithm; determining a block color of each of the block regions based on the blood perfusion index of each of the block regions; generating a blood perfusion heat map according to the block color of each of the block regions, and outputting the blood perfusion heat map.

15. The blood vessel image analysis method according to claim 14, characterized by, the blood perfusion heat map is marked with region boundaries of the first microvascular region and the second microvascular region; the method further comprises: updating the first microvascular region and the second microvascular region based on an adjustment operation on the region boundaries, and updating blood perfusion ratios of the first microvascular region and the second microvascular region; or controlling the region boundaries to be displayed or hidden based on a display setting operation on the region boundaries.

16. A method of blood vessel image analysis based on super-resolution contrast, characterized by, the method comprises: obtaining a super-resolution blood vessel image to be analyzed; selecting a quantitative analysis mode of the super-resolution blood vessel image based on a mode selection operation on the super-resolution blood vessel image, the quantitative analysis mode being capable of performing quantitative analysis on microvessels in the super-resolution blood vessel image; determine, from the super-resolution blood vessel image, a first microvessel region and a second microvessel region based on a region division operation triggered in the quantitative analysis mode; determine blood perfusion parameters of the first microvessel region and the second microvessel region, and output the blood perfusion parameters.

17. The blood vessel image analysis method according to claim 16, characterized by, The quantitative analysis mode includes a double-ring analysis mode, in which the first microvessel region and the second microvessel region can be constructed into a double-ring structure in a containing relationship for quantitative analysis; or The quantitative analysis mode includes a free analysis mode, in which the first microvessel region and the second microvessel region can be respectively constructed into an arbitrary structure for quantitative analysis.

18. The blood vessel image analysis method according to claim 17, characterized by, The quantitative analysis mode includes a double-ring analysis mode; and determining, from the super-resolution blood vessel image, a first microvessel region and a second microvessel region based on a region division operation triggered in the quantitative analysis mode includes: determining a first region boundary based on a first region determination operation on the super-resolution blood vessel image; determining a second region boundary inside the first region boundary according to the first region boundary; determining an image region inside the second region boundary as the first microvessel region, and determining an image region between the first region boundary and the second region boundary as the second microvessel region.

19. The blood vessel image analysis method according to claim 18, characterized by, The method further includes: adjusting the second region boundary based on an adjustment operation on the second region boundary; updating the first microvessel region and the second microvessel region according to the adjusted second region boundary, and updating blood perfusion parameters of the first microvessel region and the second microvessel region.

20. The blood vessel image analysis method according to claim 19, characterized by, After updating the first microvessel region and the second microvessel region according to the adjusted second region boundary, the method further includes: outputting an area of the updated first microvessel region and the second microvessel region; or outputting microbubble density of the updated first microvessel region and the second microvessel region.

21. The blood vessel image analysis method according to claim 17, wherein, The quantitative analysis mode includes a free analysis mode; and determining, from the super-resolution blood vessel image, a first microvessel region and a second microvessel region based on a region division operation triggered in the quantitative analysis mode includes: determining a third region boundary based on a second region determination operation on the super-resolution blood vessel image, and determining an image region inside the third region boundary as the first microvessel region; and determining a fourth region boundary based on a third region determination operation on the super-resolution blood vessel image, and determining an image region inside the fourth region boundary as the second microvessel region.

22. The blood vessel image analysis method according to claim 21, characterized by, The method further includes: displaying a preset region boundary, the preset region boundary being determined according to a shape and a size of the third region boundary; adjusting a position of the preset region boundary according to a position determination operation on the preset region boundary, and determining the preset region boundary after the position adjustment as the fourth region boundary.

23. The blood vessel image analysis method according to claim 21, wherein, The method further includes: adjust the third region boundary or the fourth region boundary based on an adjustment operation on the third region boundary or the fourth region boundary; update the first microvessel region or the second microvessel region according to the adjusted third region boundary or the fourth region boundary, and update blood perfusion parameters of the first microvessel region and the second microvessel region.

24. The blood vessel image analysis method according to any one of claims 16-23, characterized by, The method further comprises: performing block processing on the first microvessel region and the second microvessel region to obtain a plurality of block regions; determine a blood perfusion index of each of the block regions based on a sliding window algorithm; determine a block color of each of the block regions based on the blood perfusion index of each of the block regions; generate a blood perfusion heat map according to the block color of each of the block regions, and output the blood perfusion heat map.

25. The blood vessel image analysis method according to claim 24, characterized by, The blood perfusion heat map is marked with region boundaries of the first microvessel region and the second microvessel region; the method further comprises: update the first microvessel region and the second microvessel region, and update blood perfusion parameters of the first microvessel region and the second microvessel region based on an adjustment operation on the region boundaries; or control the region boundaries to be displayed or hidden based on a display setting operation on the region boundaries.

26. The blood vessel image analysis method according to claims 16-23, characterized by, The blood perfusion parameters include at least one of a first blood perfusion index of the first microvessel region, a second blood perfusion index of the second microvessel region, a total blood perfusion index of the first microvessel region and the second microvessel region, and a blood perfusion ratio of the first microvessel region and the second microvessel region.

27. The blood vessel image analysis method according to claim 26, wherein, The first blood perfusion index is determined according to a product of an area of the first microvessel region and an average blood flow velocity, and the second blood perfusion index is determined according to a product of an area of the second microvessel region and an average blood flow velocity.

28. The blood vessel image analysis method according to claim 26, wherein, The first blood perfusion index is determined according to a product of a microbubble density of the first microvessel region and an average blood flow velocity, and the second blood perfusion index is determined according to a product of a microbubble density of the second microvessel region and an average blood flow velocity.

29. An image analysis apparatus, characterized by The image analysis device comprises a processor, a memory, a computer program stored on the memory and executable by the processor, and a data bus for realizing connection communication between the processor and the memory, wherein the computer program, when executed by the processor, realizes the blood vessel image analysis method according to any one of claims 1 to 28.

30. A storage medium for computer-readable storage, comprising: The storage medium stores one or more programs executable by one or more processors to realize the blood vessel image analysis method according to any one of claims 1 to 28.

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