WO2021208140A1

WO2021208140A1 - Vascular image processing method and system, computing device, and storage medium

Info

Publication number: WO2021208140A1
Application number: PCT/CN2020/087304
Authority: WO
Inventors: 涂圣贤; 李莹光; 余炜; 吴鹏; 赖琦彘; 陈树湛
Original assignee: 博动医学影像科技（上海）有限公司
Priority date: 2020-04-14
Filing date: 2020-04-27
Publication date: 2021-10-21
Also published as: JP2023514866A; CN111523538B; CN111523538A; JP7465361B2

Abstract

Disclosed are a vascular image processing method and system, a computing device and a storage medium. The method comprises the following steps: acquiring image data of a vascular segment of interest; acquiring blood flow parameters of the vascular segment of interest; testing and analyzing the image data of the vascular segment of interest to obtain reference information, wherein the reference information comprises lumen profile parameters and tunica media profile parameters of the vascular segment of interest; obtaining reference lumen information according to the tunica media profile parameters; and calculating a fractional flow reserve value of the vascular segment of interest according to the blood flow parameters, the reference information and the reference lumen information. By means of the method, the calculation of a vascular pressure difference can be more accurate.

Description

Method, system, computing device and storage medium for processing blood vessel image

Technical field

The present invention relates to the medical field, in particular to a method, system, computing device and storage medium for processing blood vessel images.

Background technique

Vascular stenosis will affect the blood supply of the myocardium. Coronary angiography can show the severity of coronary stenosis, but it cannot reflect the functional changes of the blood vessels. Vascular pressure difference refers to the pressure difference between the proximal end and the distal end of the blood vessel segment of interest, which can effectively reflect the blood supply function of the blood vessel.

However, the measurement of vascular pressure difference has always been a difficult point. Invasive and invasive pressure measurement of blood vessels through pressure sensors is not only a lot of work, but also has the risk of damaging blood vessels. The geometric model of the coronary system can be obtained by three-dimensional or two-dimensional quantitative coronary angiography. Then, the reconstructed geometric model of the coronary system is analyzed by computer fluid mechanics. Solving complex fluid mechanics equations requires a lot of calculations. There are also methods to treat the length and stenosis rate of coronary artery stenosis as fixed values, which will reduce the accuracy of the calculation results.

In the prior art, CN107115108A discloses a method for quickly calculating blood vessel pressure difference based on blood vessel images.

Summary of the invention

The applicant found that there is a problem of inaccuracy in calculating the blood vessel pressure difference based on the blood vessel image in the prior art. The applicant further discovered that this is because the prior art calculates the reference lumen based on the lumen profile parameters in the blood vessel, which results in the presence of certain features in the blood vessel, for example, when there is plaque between the lumen and the media. At this time, due to the compression of the plaque, the lumen has undergone a large deformation, and the obtained reference lumen deviates greatly from the ideal reference lumen, especially when there are plaques in the entire blood vessel, it is impossible to pass through the lumen. Obtaining an accurate reference lumen further leads to inaccurate calculation of the vascular pressure difference.

Therefore, how to solve the problem of the error in the calculation of the vascular pressure difference caused by the traditional lumen when plaque appears between the lumen and the media has become a new topic and a practical problem that needs to be solved urgently. For this reason, the applicant found through creative experiments and countless simulations that the concept of media contour parameters was introduced into the existing traditional calculation method and based on the media contour parameters instead of the lumen parameters in the prior art. To obtain the reference lumen information, through this innovative parameter introduction and calculation method, the ideal and accurate blood flow reserve value of the blood vessel segment of interest that meets the actual needs is obtained (the reason is that when there is plaque in the entire blood vessel When using the traditional calculation method, the proper or correct position of the actual lumen cannot be found to obtain an accurate reference lumen. However, the media contour parameters can be used to obtain an accurate reference lumen, such as the reduction of the media contour. After removing the thickness of the normal intima, it is the corresponding contour of the reference lumen). Therefore, the new technical solution proposed by the present invention overcomes the technical problem of inaccurate calculation of the vascular pressure difference in the prior art.

The purpose of the present invention is to provide a method for processing blood vessel images to solve the problem of inaccurate calculation of blood vessel pressure difference in the prior art.

In order to solve the above technical problems, an embodiment of the present invention discloses a method for processing blood vessel images, including the following steps: acquiring image data of the blood vessel segment of interest; acquiring the blood flow parameters of the blood vessel segment of interest; detecting and analyzing the blood vessel of interest Segment image data to obtain reference information, which includes the lumen contour parameters and media contour parameters of the blood vessel segment of interest; obtain reference lumen information according to the media contour parameters; calculate according to blood flow parameters, reference information and reference lumen information Obtain the blood flow reserve score value of the blood vessel segment of interest.

By adopting the above technical solution, the calculation of the vascular pressure difference can be more accurate.

Optionally, the step of obtaining reference lumen information according to the media contour parameter includes: obtaining the proximal normal frame and the distal normal frame according to the media contour parameter; calculating the reference lumen according to the proximal normal frame and the distal normal frame information.

Optionally, the step of obtaining reference lumen information according to media contour parameters includes: obtaining the normal intima thickness of the blood vessel segment of interest; obtaining reference lumen information according to the media contour parameters and the normal intima thickness.

Optionally, the reference information further includes the side branch vessel segment parameters of the blood vessel segment of interest. The side branch vessel segment parameters are calculated from the lumen contour parameters. The step of obtaining reference lumen information according to the media contour parameters includes: The contour parameter obtains the near-end normal frame and the far-end normal frame; according to the side branch blood vessel segment parameters, the near-end normal frame and the far-end normal frame, the reference lumen information is calculated.

Optionally, the reference information also includes side branch vessel segment parameters of the blood vessel segment of interest. The side branch vessel segment parameters are calculated from the lumen contour parameters. The step of obtaining reference lumen information according to the media contour parameters includes: according to the side branch The blood vessel segment parameter divides the blood vessel segment of interest into multiple sub-segments; the normal frame in each sub-segment is obtained according to the media contour parameter; the reference lumen information is obtained according to the normal frame in each sub-segment.

Optionally, the blood vessel image processing method further includes the following steps: calculating the calibration value at each side branch according to the reference lumen information and the side branch blood vessel segment parameters; displaying the chart of the blood vessel segment of interest according to the side branch blood vessel segment parameters Display each side support at the corresponding position of the chart; and/or display the cross-sectional profile of the side support and display the calibration value.

Optionally, the method for processing blood vessel images further includes the following steps: obtaining the blood vessel position of the blood vessel segment of interest; and correcting the blood flow reserve score value according to the blood vessel position.

Optionally, the reference information further includes the side branch blood vessel segment parameters of the blood vessel segment of interest. The side branch blood vessel segment parameters are calculated from the lumen contour parameters. The blood vessel image processing method further includes the following steps: obtaining the blood vessel of interest according to the position of the blood vessel The blood vessel type of the segment; when the blood vessel type is a bifurcation model: obtain the bifurcation node information of the blood vessel segment of interest according to the parameters of the side branch vessel segment; display the longitudinal section window of the blood vessel segment of interest; use different colors according to the bifurcation node information The main branch and branch of the vessel segment of interest are identified in the longitudinal section window.

Optionally, the step of acquiring image data of the blood vessel segment of interest includes: acquiring image data of the target blood vessel and corresponding acquisition parameters, the acquisition parameters including layer thickness and pixel size; reconstructing and displaying based on the image data and acquisition parameters of the target blood vessel The image of the target blood vessel; to obtain the image data of the selected blood vessel segment of interest in the image.

Optionally, the step of reconstructing and displaying the image of the target blood vessel according to the image data and acquisition parameters of the target blood vessel includes: re-sampling and re-ordering the image data of the target blood vessel; according to the re-ordered image data and acquisition of the target blood vessel The parameters reconstruct and display the image of the target blood vessel.

Optionally, the step of reconstructing and displaying the image of the target blood vessel according to the image data and acquisition parameters of the target blood vessel includes: reconstructing the image of the target blood vessel according to the image data and acquisition parameters of the target blood vessel; and registering the image of the target blood vessel to Correct the error in the acquisition process of the image data of the target blood vessel; display the registered image.

Optionally, the reference information further includes stent information, a method for processing blood vessel images, and further includes the following steps: acquiring stent parameters of the blood vessel segment of interest; detecting and rebuilding the stent according to the stent parameters, evaluating the stent to obtain the stent information, The stent information includes stent position and stent contour information; the longitudinal section window showing the blood vessel segment of interest; the stent is identified by pseudo-color bars in the longitudinal section window according to the stent information.

Optionally, the blood vessel image processing method further includes the following steps: quantify the first characteristic blood vessel segment whose stenosis rate is greater than the threshold value according to the reference lumen information and the reference information; display a chart of the blood vessel segment of interest; and mark the chart where the stenosis rate is located Set the first characteristic blood vessel segment of the interval.

Optionally, when the blood vessel segment of interest includes the second feature, the reference information further includes the second feature information, and the blood vessel image processing method further includes the following steps: reconstructing and displaying the blood vessel segment of interest and the second feature based on the reference information.

Optionally, the blood vessel image processing method further includes the following steps: displaying the longitudinal section contour and/or the cross-sectional contour of the blood vessel segment of interest according to the reference information; adjusting the longitudinal section contour and/or the cross-sectional contour; according to the adjusted longitudinal The section profile and/or the cross-sectional profile update the reference information, and/or the reference lumen information, and the blood flow reserve score value.

Optionally, the blood vessel image processing method further includes the following steps: displaying the blood flow reserve score value on the chart of the blood vessel segment of interest in a pseudo-color form; and/or displaying the chart of the blood vessel segment of interest and superimposing the simulated Retracement curve; and/or three-dimensional reconstruction of the vessel segment of interest, and display the vessel segment of interest after the three-dimensional reconstruction.

The embodiment of the present invention also discloses a blood vessel image processing system, including: an acquisition module for acquiring image data of the blood vessel segment of interest and blood flow parameters of the blood vessel segment of interest; an analysis module for detecting and analyzing the blood vessel of interest Segment image data to obtain reference information. The reference information includes the lumen contour parameters and media contour parameters of the blood vessel segment of interest; the calculation module includes a first calculation unit and a second calculation unit. The parameter obtains the reference lumen information, and the second calculation unit is used to calculate the blood flow reserve score value of the blood vessel segment of interest according to the blood flow parameter, the reference information and the reference lumen information.

By adopting the processing system of the above technical scheme, the calculation of the vascular pressure difference can be more accurate.

Optionally, the first calculation unit includes a normal frame extraction unit and a reference lumen calculation unit. The normal frame extraction unit is used to obtain the proximal normal frame and the distal normal frame according to the media contour parameters, and the reference lumen calculation unit is used to obtain The reference lumen information is calculated from the near-end normal frame and the far-end normal frame.

Optionally, the obtaining module is also used to obtain the normal intima thickness of the blood vessel segment of interest, and the first calculation unit obtains the reference lumen information according to the media contour parameter and the normal intima thickness.

Optionally, the reference information further includes the side branch blood vessel segment parameters of the blood vessel segment of interest, the side branch blood vessel segment parameters are calculated by the analysis module according to the lumen contour parameters, and the first calculation unit includes a normal frame extraction unit and a reference lumen calculation unit , The normal frame extraction unit is used to obtain the proximal normal frame and the distal normal frame according to the media contour parameters, and the reference lumen calculation unit is used to calculate the reference tube according to the side branch vessel segment parameters, the proximal normal frame and the distal normal frame. Cavity information.

Optionally, the reference information further includes the side branch blood vessel segment parameters of the blood vessel segment of interest, the side branch blood vessel segment parameters are calculated by the analysis module according to the lumen contour parameters, and the first calculation unit includes a normal frame extraction unit and a reference lumen calculation unit , The normal frame extraction unit is used to divide the blood vessel segment of interest into multiple sub-segments according to the side branch blood vessel segment parameters, and obtain the normal frame in each sub-segment according to the media contour parameters. The reference lumen calculation unit is used to calculate according to each sub-segment The normal frame inside gets the reference lumen information.

Optionally, the blood vessel image processing system further includes a first display module, and the calculation module further includes a third calculation unit. The third calculation unit is used to calculate the value of each side branch according to the reference lumen information and the side branch blood vessel segment parameters. Calibration value, the first display module is used to display the chart of the blood vessel segment of interest, and each side branch is displayed in the corresponding position of the chart according to the side branch blood vessel segment parameters, and/or the first display module is also used to display the side branch Cross-section profile and display calibration value.

Optionally, the blood vessel image processing system further includes a correction module, the acquisition module is also used to acquire the blood vessel position of the blood vessel segment of interest, and the correction module is used to correct the blood flow reserve score value of the blood vessel segment of interest according to the blood vessel position.

Optionally, the blood vessel image processing system further includes a second display module, the reference information also includes side branch blood vessel segment parameters of the blood vessel segment of interest, the side branch blood vessel segment parameters are calculated from the lumen contour parameters, and the acquisition module is also used for Obtain the blood vessel type of the blood vessel segment of interest according to the position of the blood vessel. When the blood vessel type is a bifurcation model: the analysis module obtains the bifurcation node information of the blood vessel segment of interest according to the side branch vessel segment parameters; the second display module displays the blood vessel segment of interest. The longitudinal section window, and according to the bifurcation node information, use different colors to identify the main branch and branch of the blood vessel segment of interest in the longitudinal section window.

Optionally, the acquisition module includes a first acquisition unit, a second acquisition unit, a reconstruction calculation unit, and a display unit. The first acquisition unit is used to acquire image data of the target blood vessel and corresponding acquisition parameters. The acquisition parameters include layer thickness and pixel size. , The reconstruction calculation unit is used to perform reconstruction calculation according to the image data and acquisition parameters of the target blood vessel, the display unit is used to display the image of the reconstructed target blood vessel, and the second acquisition unit is used to obtain the selected blood vessel segment of interest in the image Image data.

Optionally, the acquisition module further includes a re-sampling unit, the re-sampling unit is used to re-sample and re-order the image data of the target blood vessel acquired by the first acquisition unit, and the reconstruction calculation unit is used to re-order the image data of the target blood vessel Data and acquisition parameters are reconstructed and calculated.

Optionally, the acquisition module further includes a registration unit, the registration unit is used to register the image of the target blood vessel to correct errors in the acquisition process of the image data of the target blood vessel, and the display unit is used to display the registered image .

Optionally, the blood vessel image processing system further includes a third display module, the reference information also includes stent information, the acquisition module is also used to acquire stent parameters of the blood vessel segment of interest, and the analysis module is also used to detect and reconstruct the stent according to the stent parameters The stent is evaluated and the stent information is obtained. The stent information includes stent position and stent contour information. The third display module is used to display the longitudinal section window of the blood vessel segment of interest, and according to the stent information, the longitudinal section window is displayed in false color Bar identification bracket.

Optionally, the blood vessel image processing system further includes a fourth display module, and the calculation module further includes a fourth calculation unit configured to quantify the first feature that the stenosis rate is greater than the threshold according to the reference lumen information and the reference information The blood vessel segment, the fourth display module is used to display the chart of the blood vessel segment of interest, and mark the first characteristic blood vessel segment whose stenosis rate is in the set interval in the chart.

Optionally, the blood vessel image processing system further includes a fifth display module, when the blood vessel segment of interest contains the second feature, the reference information further includes second feature information, and the analysis module is further used to reconstruct the blood vessel segment of interest based on the reference information And the second feature, the fifth display module is used to display the blood vessel segment of interest and the second feature.

Optionally, the blood vessel image processing system further includes an adjustment module, the adjustment module includes a display unit, an adjustment unit and an update unit, the display unit is used to display the longitudinal section contour and/or the cross section contour of the blood vessel segment of interest according to the reference information, The adjustment unit is used to adjust the longitudinal section profile and/or cross-sectional profile, and the update unit is used to update the reference information, and/or reference lumen information, and the blood flow reserve score value according to the adjusted longitudinal section profile and/or cross-sectional profile. .

Optionally, the blood vessel image processing system further includes a sixth display module for displaying the blood flow reserve score value on the chart of the blood vessel segment of interest in a pseudo-color form, and/or the displayed interest The chart of the blood vessel segment is superimposed to display the simulated retracement curve, and/or the blood vessel segment of interest is reconstructed in three dimensions, and the blood vessel segment of interest after the three-dimensional reconstruction is displayed.

The embodiment of the present invention also discloses a computing device, including: a processor, which is suitable for implementing various instructions; a memory, which is suitable for storing multiple instructions, and the instructions are suitable for being loaded by the processor and executing any of the aforementioned blood vessel images. Approach.

By adopting the calculation device of the above technical solution, the calculation of the blood vessel pressure difference can be more accurate.

The embodiment of the present invention also discloses a storage medium, which stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executed by any of the aforementioned blood vessel image processing methods.

By adopting the storage medium of the above technical solution, the calculation of the blood vessel pressure difference can be more accurate.

Description of the drawings

FIG. 1 shows a flowchart of a method for processing a blood vessel image according to an embodiment of the present invention;

FIG. 2 shows a partial flowchart of a method for processing a blood vessel image according to another embodiment of the present invention;

Fig. 3 shows a flowchart of a method for processing a blood vessel image according to another embodiment of the present invention;

FIG. 4 shows a partial flowchart of a method for processing a blood vessel image according to another embodiment of the present invention;

Fig. 5 shows a schematic block diagram of a blood vessel image processing system according to an embodiment of the present invention.

Fig. 6 shows a schematic diagram of a blood vessel segment of interest in an embodiment of the present invention;

Fig. 7 shows a schematic diagram of a blood vessel segment of interest in another embodiment of the present invention;

Figure 8 shows a three-dimensional schematic diagram of a blood vessel segment of interest in an embodiment of the present invention;

Fig. 9 shows a schematic diagram of a blood vessel segment of interest in an embodiment of the present invention;

Figure 10 shows a schematic diagram of plaques in an embodiment of the present invention;

Figure 11 shows a schematic cross-sectional view of a side support in an embodiment of the present invention;

Figure 12 shows a schematic diagram of a cross-sectional profile of a blood vessel segment of interest in an embodiment of the present invention;

Figure 13 shows a schematic diagram of a bracket in an embodiment of the present invention;

Figure 14 shows a schematic diagram of a stent in another embodiment of the present invention;

Fig. 15 shows a schematic diagram of a blood vessel segment of interest in another embodiment of the present invention.

Detailed ways

The following specific examples illustrate the implementation of the present invention, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Although the description of the present invention will be introduced in conjunction with the preferred embodiments, this does not mean that the features of the present invention are limited to this embodiment. On the contrary, the purpose of introducing the invention in combination with the embodiments is to cover other options or modifications that may be extended based on the claims of the invention. In order to provide an in-depth understanding of the present invention, the following description will contain many specific details. The present invention can also be implemented without using these details. In addition, in order to avoid confusion or obscuring the focus of the present invention, some specific details will be omitted in the description. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other if there is no conflict.

It should be noted that in this specification, similar reference numerals and letters indicate similar items in the following drawings. Therefore, once a certain item is defined in one drawing, it is not necessary to refer to it in subsequent drawings. To further define and explain.

The terms "first", "second", etc. are only used for distinguishing description, and cannot be understood as indicating or implying relative importance.

In order to make the objectives, technical solutions and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below in conjunction with the accompanying drawings.

1, the embodiment of the present invention discloses a method for processing blood vessel images, including the following steps: acquiring image data of a blood vessel segment of interest; acquiring blood flow parameters of the blood vessel segment of interest; detecting and analyzing the blood vessel of interest Segment image data to obtain reference information, which includes the lumen contour parameters and media contour parameters of the blood vessel segment of interest; obtain reference lumen information according to the media contour parameters; calculate according to blood flow parameters, reference information and reference lumen information Obtain the Fractional Flow Reserve (FFR) value of the blood vessel segment of interest.

For acquiring the image data of the blood vessel segment of interest, the image data may be directly acquired, or image data corresponding to the blood vessel segment of interest selected from the image data of a blood vessel segment, which is not limited in this embodiment. The source of the image data can be directly imported related files, it can also be obtained from the real-time configuration connection of other resource libraries, or it can be obtained from the stored image database after searching and locking based on the user’s name and other information. This is not limited. Optionally, the image data is in DICOM (Digital Imaging and Communication in Medicine) format. DICOM covers almost all information exchange protocols such as the collection, archiving, communication, display and query of medical digital images; it is based on an open interconnected architecture and object-oriented The method defines a set of objects containing various types of medical diagnostic images and related analysis, reports and other information; defines the service classes and command sets used for information transmission and exchange, as well as the standard response of messages; details The technology to identify various information objects; provide service support applied to the network environment (OSI or TCP/IP); structured definition of the manufacturer’s compatibility statement (Conformance Statement). Adopting the DICOM format can greatly simplify the realization of medical imaging information exchange, and facilitate the association and synergy with other medical application systems such as HIS and RIS. Optionally, the image data is an image of 200-4000 frames. Within the range of the number of frames, it can ensure a clearer coverage of the multi-angle images of each position of the blood vessel segment, improve the accuracy of calculation, and do not increase the calculation load, and It is less than the number of frames collected each time in the general image data collection process, and it is easy to obtain.

For acquiring the blood flow parameters of the blood vessel segment of interest, the blood flow parameters may include the average maximum blood flow velocity. It is understandable that the average maximum blood flow velocity of the blood vessel segment of interest is required to calculate the FFR value of the blood vessel segment of interest, but there are many forms of the source and acquisition sequence of blood flow parameters, either in the image data collection What is measured in the process may also be obtained by the user in the previous measurement and stored in the database, and obtained directly this time, or it may be obtained by obtaining the input fixed value. It is understandable that the acquisition of blood flow parameters can be carried out before the acquisition of the image data, or simultaneously with the acquisition of the image data, or after the acquisition of the image data, as long as it is before the FFR is calculated. This is not limited.

There are many specific methods for detecting and analyzing the image data of the blood vessel segment of interest to obtain reference information. For example, you can refer to the method in the patent publication number CN10713395A. Algorithms can be used to segment the contours of the lumen and media boundary of the longitudinal section image at multiple cut angles of the blood vessel segment of interest, and combine the longitudinal section contours to segment the contours of the lumen and media boundary in each cross-sectional image , And quantify the area and diameter of the lumen and media boundary in the cross-sectional image in each frame, so as to obtain the corresponding reference information, that is, the lumen profile parameters and media profile parameters of the blood vessel segment of interest. The profile parameters can be The area and diameter corresponding to the contour.

Obtaining the reference lumen through the media profile parameters can make it possible even when there are certain features in the blood vessel segment of interest, such as plaques, so that the lumen profile is significantly squeezed inward, because the media profile is affected by these features. The influence is small, so the reference lumen information obtained by the media profile parameters is closer to the ideal reference lumen and more accurate, which makes the calculation result of FFR more accurate. The reference lumen information may be the boundary contour, area, diameter, etc. of the reference lumen.

In calculating the Fractional Flow Reserve (FFR) value of the blood vessel segment of interest based on the blood flow parameters, reference information and reference lumen information, there are many specific calculation methods, for example, you can refer to the method in the patent publication number CN107115108A Calculate the vascular pressure difference corresponding to the blood vessel segment of interest, that is, the Fractional Flow Reserve (FFR) value of the blood vessel segment of interest. It is understandable that when the reference information only includes the media contour information and the lumen contour information, the blood flow parameters, the lumen contour information and the reference lumen information can be used to calculate the FFR. When the reference information also includes other information, such as stent information and plaque information, the FFR calculation can be corrected accordingly based on these information. In addition, the calculation of FFR can be corrected according to the position of the blood vessel. It is understandable that the media contour parameters are mainly used for the calculation of reference lumen information, and the reference lumen information directly participates in the calculation of FFR.

By adopting the above technical solution, the blood vessel image processing method disclosed in this embodiment can achieve a more accurate calculation result, which facilitates the subsequent application of the FFR value by the user.

Another embodiment of the present invention discloses a method for processing blood vessel images. Compared with the foregoing embodiment, the step of obtaining reference lumen information according to media contour parameters includes: obtaining proximal normal frames and distal normal frames according to media contour parameters. End normal frame; the reference lumen information is calculated according to the near-end normal frame and the far-end normal frame. In obtaining the proximal normal frame and the distal normal frame according to the media contour parameters, the blood vessel of interest can be divided into three segments: the proximal blood vessel segment, the middle blood vessel segment, and the distal blood vessel segment. Optionally, the specific segmentation method can be divided into three equal parts according to the number of frames. Then calculate the smoothness of the media contour in each cross section and the media contour of the adjacent cross section in the proximal blood vessel segment and the distal blood vessel segment according to the media contour parameters, and take the cross section with the highest degree of smoothness. The frames are respectively referred to as the near-end normal frame (PN) and the far-end normal frame (DN). In the general state, that is, when the blood vessel segment does not contain characteristic information such as plaque, the thickness between the lumen and the media is very small, and the contour of the media is basically not affected by the existence of characteristic information such as plaque, so it can be used. Membrane profile parameters replace the lumen profile parameters to determine PN and DN, and the PN and DN obtained thereby are more reliable.

Optionally, the degree of smoothness can be represented by the mean square error of the area of the area enclosed by the media contour. In calculating the reference lumen information based on the near-end normal frame and the far-end normal frame, the diameter or area of the media at PN and DN can be used as the diameter or area of the reference lumen to calculate the information of the reference lumen . There are many specific calculation methods. For example, linear interpolation can be performed based on PN and DN to obtain the reference lumen size at each position of the blood vessel segment of interest. You can also refer to the lumen modeling calculation method in the patent publication number CN108022650A This embodiment will not repeat this description.

In this embodiment, the media contour parameters replace the lumen contour parameters to determine the proximal normal frame and the distal normal frame, and then calculate the corresponding reference lumen, so that the obtained reference lumen information is more accurate, and plaques are reduced. When the characteristic information exists, the error caused by PN and DN is determined by the parameters of the lumen profile.

Referring to Fig. 2, another embodiment of the present invention discloses a method for processing blood vessel images. Compared with the foregoing embodiment, the step of obtaining reference lumen information according to media contour parameters includes: obtaining information about the blood vessel segment of interest. Normal intima thickness; reference lumen information is obtained according to media contour parameters and normal intima thickness. It can be understood that the thickness of the intima between the lumen and the media is basically fixed when the blood vessel segment of interest is in a general state, that is, when it does not contain characteristic information such as plaque. This value is called in this embodiment It is the normal intima thickness. Therefore, when using the media contour parameters to calculate the reference lumen information, according to the normal intima thickness, the reference lumen information in the ideal state can be accurately obtained. There are many methods for the source and acquisition of the normal intima thickness, which can be measured at the same time during the acquisition of image data, or acquired together with the image data. It can also be directly obtained from the database of the individual corresponding to the blood vessel segment of interest, or it can be determined based on the input value. This embodiment is not limited, and the normal intima thickness can be obtained as long as the reference lumen information is calculated. Just before.

For the calculation method of the reference lumen information, there can be multiple methods, for example, the diameter of the reference lumen can be obtained by subtracting twice the normal intima thickness from the diameter of the media, and the area of the reference lumen can be calculated. It is also possible to convert the area of the media to an equivalent diameter and subtract twice the normal intima thickness to obtain the diameter of the reference lumen, and the area of the reference lumen can be calculated, which is not limited in this embodiment.

In this embodiment, the corresponding reference lumen is calculated based on the media contour parameters and the normal intima thickness, so that the obtained reference lumen information is more accurate, the influence of the intima thickness is eliminated, and the corresponding FFR value is also more accurate.

Referring to Figure 3, another embodiment of the present invention discloses a method for processing blood vessel images. Compared with the foregoing embodiment, the reference information also includes the side branch blood vessel segment parameters of the blood vessel segment of interest. The side branch blood vessel segment parameters are determined by The lumen contour parameters are calculated, and the steps of obtaining reference lumen information according to the media contour parameters include: obtaining the proximal normal frame and the distal normal frame according to the media contour parameter; according to the side branch vessel segment parameters, the proximal normal frame and The far-end normal frame is calculated to obtain the reference lumen information. The present invention does not limit the specific length of the blood vessel segment of interest. During the application process, the blood vessel segment of interest may have side branches. The existence of the side branch will affect the calculation of the reference lumen. Therefore, in the blood vessel image processing method disclosed in this embodiment, the reference information obtained by detecting and analyzing the image data of the blood vessel segment of interest also includes the side branch blood vessel segment. Parameters, the side branch blood vessel segment parameters can include one or more of the opening area of the side branch, the position of the side branch blood vessel segment, and the direction of the side branch. Other information of the side branch blood vessel can also be obtained as needed for calculation Get more accurate reference lumen information. Taking the area of the opening as an example, by dividing the contour of the side branch, and then counting the number of pixels in the contour, the opening area of each side branch can be calculated according to the image resolution. When there are side branches, refer to the specific calculation of the lumen and the FFR calculation considering the influence of the side branch blood vessel segment can refer to the method in the patent publication number CN108022650A.

Another embodiment of the present invention discloses a method for processing blood vessel images. Compared with the foregoing embodiment, the reference information also includes side branch blood vessel segment parameters of the blood vessel segment of interest, and the side branch blood vessel segment parameters are calculated from the lumen contour parameters. , The step of obtaining reference lumen information according to the media contour parameters includes: dividing the blood vessel segment of interest into multiple sub-segments according to the side branch vessel segment parameters; obtaining the normal frame in each sub-segment according to the media contour parameters; according to each sub-segment The normal frame in the segment gets the reference lumen information. In this embodiment, the blood vessel segment of interest can be divided into multiple sub-segments according to the position of the side branch opening on the main branch. For example, when the blood vessel segment of interest has three side branches, the blood vessel segment of interest can be divided into four sub-segments according to the positions of the openings of the three side branches. Then, referring to the determination method of PN and DN, the normal frame in each sub-segment is determined. Then, according to the normal frame in each sub-segment, the reference lumen is reconstructed, and the corresponding reference lumen information is calculated. The specific method can refer to the method of calculating the reference lumen information from PN and DN. In this embodiment, since the blood vessel segment of interest is segmented according to the side branches, multiple normal frames are obtained to calculate the reference lumen information, which increases the sampling amount, that is, the number of acquisitions of normal frames, and the side branch segmentation is used More reasonable, so the calculation of reference lumen information is more accurate.

In this embodiment, the corresponding reference lumen information is calculated by the media contour parameters and the side branch vessel segment parameters. At the same time, considering that the lumen contour parameters are used to calculate the reference lumen information when there are certain features in the blood vessel segment of interest, the reference lumen information is not accurate. And the influence of the presence of side branch vessels on the calculation of the reference lumen, so that the obtained reference lumen information is more accurate, and the corresponding FFR value is also more accurate.

Another embodiment of the present invention discloses a method for processing blood vessel images. Compared with the foregoing embodiment, the method for processing blood vessel images further includes the following steps: calculating each side branch according to the reference lumen information and the side branch blood vessel segment parameters Display the chart of the blood vessel segment of interest, and display each side branch in the corresponding position of the chart according to the parameters of the side branch blood vessel segment; and/or display the cross-sectional profile of the side branch and display the calibration value. In calculating the calibration value at each side branch, the specific type of calibration value can be set as required. For example, the calibration value may be one or more of Murray parameters, Finet parameters, HK parameters, and AP parameters. When the blood vessel segment of interest has a side branch vessel segment, define the diameter of the main branch before the bifurcation at each side branch vessel segment as D ₀ , and define the opening diameter of the side branch vessel on the main branch as D ₁ , points The diameter of the main branch behind the fork is defined as D ₂ , D ₀ and D ₂ are obtained from the reference lumen information, and D ₁ is obtained from the side branch vessel segment parameters. Among them, the calculation formula of the Murray parameter based on Murray's law is: Murray=D ₀ ³ /(D ₁ ³ +D ₂ ³ ), and the calculation formula of the Finet parameter based on the Finet diameter model is: Finet=D ₀ /[0.678*( D ₁ +D ₂ )], the calculation formula of HK parameters based on HK diameter model is: HK=D ₀ ^7/3 /(D ₁ ^7/3 +D ₂ ^7/3 ), AP parameters based on area-preservation model The calculation formula is: AP=D ₀ ² /(D ₁ ² +D ₂ ² ). The ideal state of these parameter values is 1, so the closer the calibration value is to 1, the more reasonable in theory, so as to help users judge the division of each side branch and the rationality of the reference lumen information.

Optionally, the threshold range of the calibration value can be set as required. For example, the threshold range of the calibration value can be set to 0.7-1.3. When the calibration value exceeds this range, the calculation results of the side branch vessel segment parameters and/or reference lumen information may deviate from the normal physiological range, prompting the user to obtain the image data again Or adjust the image data to ensure that the FFR calculation result is more accurate and improve the user experience.

In the chart showing the blood vessel segment of interest, each side branch is displayed in the corresponding position of the chart according to the parameters of the side branch blood vessel segment. The chart display form of the blood vessel segment of interest can be in various forms, such as long and short axis display, or It is an equivalent diameter display. This embodiment does not limit this, and can be set and selected according to the user's habits and needs. According to the side branch blood vessel segment parameters, the corresponding side branch blood vessel segment can be displayed on the corresponding position of the chart. Optionally, the equivalent diameter of the respective side branch openings can also be displayed on the corresponding position of the graph. Displaying the side branches in the chart of the blood vessel segment of interest can facilitate the user to observe the blood vessel segment of interest intuitively and comprehensively.

In displaying the cross-sectional profile of the side branch and displaying the calibration value, the cross-section of the side branch blood vessel segment and the lumen contour of the side branch can be reconstructed and displayed through the three-dimensional image slicing algorithm and other methods. The obtained calibration value is displayed in the corresponding side branch snapshot, so that the user can visually observe the calibration value and contour, and determine whether the side branch blood vessel segment parameters and the reference lumen information corresponding to the main branch are incorrect.

Optionally, as shown in Figure 11, "Branch" in the figure corresponds to "side branch", "MU" corresponds to "Murray parameter", "3D" corresponds to "three-dimensional", "ADD SB" corresponds to "add side branch", " DELETE SB" corresponds to "delete side branch". The upper part of the figure shows the cross-sectional contours of the four side branches and marked them. The marking shows the corresponding lumen contour of each side branch. In the cross-sectional contour The upper right of the display shows the calibration value corresponding to the side branch, and also shows the lumen area corresponding to the lumen contour of each side branch. "3D" can be used to switch to display the main branch and/or the main branch and/or in the blood vessel segment of interest after 3D reconstruction Side branch blood vessel segment. The lower part of the figure is used to edit the side branches, that is, add or delete side branches, and display any cross-sectional window of the side branches, so that the user can directly and clearly view the side branch segmentation of the blood vessel of interest, so as to judge the obtained side branch blood vessel Whether the segment parameter is wrong.

Another embodiment of the present invention discloses a method for processing a blood vessel image. Compared with the foregoing embodiment, the method for processing a blood vessel image further includes the following steps: obtaining the blood vessel position of the blood vessel segment of interest; and correcting the blood vessel segment of interest according to the blood vessel position Fractional flow reserve (FFR) value of In the application process, there may be multiple vessel positions corresponding to the vessel segment of interest, such as anterior descending vessel, circumflex vessel, right coronary vessel, diagonal branch vessel, septal branch vessel, middle branch vessel, obtuse edge Branch blood vessels and so on. For blood vessels in different positions, if the same algorithm is used in the analysis and detection process corresponding to the image data, it will cause a certain deviation of the reference information, and then affect the FFR value. Therefore, acquiring the blood vessel position of the blood vessel segment of interest, adjusting the detection and analysis algorithm of the image data according to the difference of the blood vessel position, or correcting the FFR value according to the blood vessel position can make the FFR value more accurate.

Another embodiment of the present invention discloses a method for processing blood vessel images. Compared with the foregoing embodiment, the reference information also includes side branch blood vessel segment parameters of the blood vessel segment of interest, and the side branch blood vessel segment parameters are calculated from the lumen contour parameters. , The blood vessel image processing method further includes the following steps: obtaining the blood vessel type of the blood vessel segment of interest according to the position of the blood vessel; when the blood vessel type is a bifurcation model: obtaining the bifurcation node information of the blood vessel segment of interest according to the side branch vessel segment parameters; Display the longitudinal section window of the vessel segment of interest; according to the bifurcation node information, use different colors to mark the main branch and branch of the vessel segment of interest in the longitudinal section window. It is understandable that blood vessels at different positions correspond to different types, so according to the position of the blood vessel, the type corresponding to the blood vessel of interest can be obtained, for example, whether it is a bifurcation model or a single-vessel model. When the blood vessel is a bifurcation model, the bifurcation will affect the calculation of FFR. Therefore, in this embodiment, when the blood vessel type is a bifurcation model, bifurcation node information can be obtained according to the side branch vessel segment parameters. For example, usually the largest side branch is set as the bifurcation node, and the largest side branch can be found through the area or diameter of the side branch blood vessel in the side branch blood vessel segment parameters, as the bifurcation node, then the blood vessel corresponding to the side branch The segment parameter is the branch node information corresponding to the branch. After displaying the longitudinal section window of the blood vessel segment of interest, determine the location of the bifurcation based on the bifurcation node information. The main branch and branch can be marked in different colors in the longitudinal section view window to facilitate users to observe the vessel segment of interest. Bifurcation situation. At the same time, when calculating FFR, the FFR is corrected according to the information of the bifurcation node, so that the calculation result of FFR is more accurate. There are many specific calculation methods, for example, you can refer to the method in the patent publication number CN108022650A.

Referring to FIG. 4, another embodiment of the present invention discloses a method for processing blood vessel images. Compared with the foregoing embodiment, the step of obtaining image data of a blood vessel segment of interest includes: obtaining image data of a target blood vessel and corresponding The acquisition parameters include layer thickness and pixel size; reconstruct and display the image of the target blood vessel according to the image data and acquisition parameters of the target blood vessel; obtain the image data of the selected blood vessel segment of interest in the image. In this embodiment, the blood vessel segment corresponding to one image data collection is called the target blood vessel. It is understandable that the blood vessel segment of interest can be either the target blood vessel or just a certain segment of the target blood vessel. First, acquire the image data and acquisition parameters of the target blood vessel. The acquisition parameters include layer thickness and pixel size. The layer thickness refers to the collection distance interval between adjacent frames of image data, and there are many ways to obtain it. For example, the layer thickness may be obtained by directly obtaining the layer thickness value, or may be calculated after obtaining the withdrawal speed and the acquisition frame rate, which is not limited in this embodiment. The pixel size refers to the actual size corresponding to each pixel in the image data, and there are many ways to obtain it. For example, the pixel size can be obtained by directly obtaining the actual size value corresponding to each pixel point, or by calculating the size of the catheter opening and the number of pixels corresponding to it during the measurement process, which is not limited in this embodiment.

According to the image data and acquisition parameters of the target blood vessel, methods such as three-dimensional image slicing algorithms can be used to reconstruct and display the image corresponding to the target blood vessel. For example, the longitudinal and cross-sectional view windows of the reconstructed target blood vessel can be displayed. The user can select the vessel segment for which the FFR value needs to be calculated according to the corresponding image, that is, the vessel segment of interest. For example, you can use the method of two markings to select in the longitudinal section window, and set the part between the two markings as the blood vessel segment of interest. The image data belonging to the blood vessel segment of interest is extracted from the image data of the target blood vessel, and the image data of the blood vessel segment of interest is obtained. Through the above method, the acquisition of the image data of the blood vessel segment of interest can be made more convenient, intuitive, and easy to operate.

Another embodiment of the present invention discloses a method for processing blood vessel images. Compared with the foregoing embodiment, the step of reconstructing and displaying the image of the target blood vessel according to the image data and acquisition parameters of the target blood vessel includes: image data of the target blood vessel Perform resampling and reordering; reconstruct and display the image of the target blood vessel based on the reordered image data and acquisition parameters of the target blood vessel. It is understandable that the image data of the target blood vessel can come from multiple sources according to different collection methods. For example, the image data may be OCT (Optical Coherence Tomography) images or IVUS (Intravascular Ultrasound) images. For images with slower retracement speed and higher frame rate during the acquisition process, especially IVUS images, there may be situations where adjacent frames are disordered before and after. Therefore, the image data can be resampled and reordered to eliminate this influence. The specific resampling method can be equal interval sampling, importance sampling, etc., which is not limited in this embodiment. For example, the IVUS image can be sampled at equal intervals with an interval of 5 frames, that is, the first frame, the sixth frame...the 1+5N frame in the image data are all sampled and sorted accordingly. Then according to the image data after resampling and reordering and the acquisition parameters of the target blood vessel, the image of the target blood vessel is reconstructed and displayed. This not only overcomes the problem of chaotic frames that may exist in the image, makes the subsequent acquisition of reference information more accurate, but also reduces the computational load in the reconstruction and display process.

Another embodiment of the present invention discloses a method for processing a blood vessel image. Compared with the foregoing embodiment, the step of reconstructing and displaying the image of the target blood vessel according to the image data and acquisition parameters of the target blood vessel includes: according to the image data of the target blood vessel And the acquisition parameters are used to reconstruct the image of the target blood vessel; the image of the target blood vessel is registered to correct the error in the acquisition process of the image data of the target blood vessel; the registered image is displayed. In the process of acquiring image data of the target blood vessel, the catheter may be displaced in the radial direction during retraction, that is, the position of the catheter in each frame of the image data is not fixed at this time. Therefore, the registration of the image of the target blood vessel can eliminate the deviation caused by this displacement. For example, in the reconstructed cross-sectional contour of the target blood vessel, the center of the catheter may be the center of each frame of image, and each frame of image may be aligned in the longitudinal direction. There are many specific methods used in the image registration process. For example, you can refer to the method in the corresponding article at https://www.onacademic.com/detail/journal_1000039137117910_4183.html and the paper "Image-Based Gating of Intravascular Methods in Ultrasound Pullback Sequences (Sean M. O'Malley, Student Member, IEEE, Juan F. Granada, St'ephane Carlier, Morteza Naghavi, and Ioannis A. Kakadiaris, Member, IEEE), etc. Image registration can eliminate the influence of catheter displacement during the image data collection process, facilitate observation, and make the reference information obtained by subsequent detection and analysis of image data more accurate.

Another embodiment of the present invention discloses a method for processing a blood vessel image. Compared with the foregoing embodiment, the reference information also includes stent information, and the method for processing a blood vessel image further includes the following steps: acquiring stent parameters of the blood vessel segment of interest; Stent parameters Detect the stent and reconstruct the stent, and evaluate the stent to obtain stent information. The stent information includes stent position and stent contour information; the longitudinal section window showing the blood vessel segment of interest; the pseudo-color bar is displayed in the longitudinal section window according to the stent information Identify the bracket.

For the blood vessel segment of interest with a stent, the method disclosed in this embodiment acquires the stent parameters of the blood vessel segment of interest before detecting and analyzing the image data of the blood vessel segment of interest. The stent parameters can be set as required, for example, Including the type and thickness of the stent. When detecting and analyzing the image data of the blood vessel segment of interest, the image data is segmented with reference to the stent parameters, the corresponding stent is detected, and the stent information is obtained, including the stent position and the stent contour information. There are many specific detection methods. For example, image processing methods can be used to pre-process and post-process the image data to be segmented. The pre-processing performs polar coordinate transformation and image standardization on the image data. Original coordinate reconstruction and continuity-based misdetection elimination can also be used for stent detection based on deep learning. After the inspection, the stent is reconstructed. There are many specific reconstruction methods. For example, the volume reconstruction method can be used to perform three-dimensional volume reconstruction on the continuous two-dimensional mask results of the stent segmentation, that is, to assign the layer spacing of the original image to the stent on each frame of image. Become a single voxel for volume reconstruction. The stent can also be evaluated, for example, by calculating the distance between the stent and the tube wall, the attachment and expansion of the stent can be evaluated. The specific method can be to draw a ray from the center of the lumen to the center of the stent according to the center position of each stent point and the lumen contour curve based on the reference information, and calculate the intersection point of the ray and the lumen, so as to calculate the center point of the stent and the lumen The qualitative analysis result of judging the distance between the stent and the lumen and whether the stent is attached to the wall, not attached or covered. It is also possible to fit the stent contour ellipse based on the position of each stent in a single frame image, calculate the average contour area and the minimum contour area of the stent, and compare it with the reference lumen information to determine the expansion of the stent. Then, in the longitudinal section window of the blood vessel segment of interest, the stent can be marked with a pseudo-color bar in the longitudinal section window according to the stent information. For example, the different attachment conditions of the stent can be marked according to the color depth, as shown in Figure 13, This facilitates the user to understand the status of the stent. It is also possible to display the relevant parameters of the stent in the cross-sectional profile window of the blood vessel segment of interest, as shown in Figure 12, where "Stent" corresponds to "stent" and "Expansion" corresponds to "expansion".

In the FFR calculation process of this embodiment, the bracket information is used as a part of the reference information, and the FFR calculation result will be corrected. For the blood vessel segment of interest that has a stent, its lumen contour information can be corrected according to the stent information. For example, in the process of detecting and analyzing the image data of the blood vessel segment of interest, the area occupied by the stent point itself can be obtained according to the stent contour information in the stent information, and the lumen area of each frame of image is subtracted from all of the frame. The area of the stent point is used to obtain the lumen area after placing the stent as a part of the lumen profile parameters for subsequent FFR calculations. Therefore, this embodiment can improve the accuracy of FFR calculation for the blood vessel segment of interest with stent placement and facilitate the user to observe and understand the state of the stent.

Another embodiment of the present invention discloses a method for processing a blood vessel image. Compared with the foregoing embodiment, the method for processing a blood vessel image further includes the following steps: quantifying the first with a stenosis rate greater than a threshold according to reference lumen information and reference information. Characteristic blood vessel segment; a chart showing the blood vessel segment of interest; marking the first characteristic blood vessel segment whose stenosis rate is in the set interval in the chart. The stenosis rate can be defined according to the cross-sectional area or diameter of the blood vessel segment. For example, it is possible to set the stenosis rate=(reference lumen diameter-actual lumen diameter)/reference lumen diameter, where the diameter may be an equivalent diameter calculated based on the area. The diameter information of the reference lumen can be obtained according to the reference lumen information, and the actual lumen diameter can be obtained according to the lumen contour parameters in the reference information, so as to calculate the stenosis rate corresponding to each position (each frame of image) in the blood vessel segment of interest . The threshold of the stenosis rate can be set according to the user's observation and attention needs. For example, if the user needs to focus on the blood vessel segment with a stenosis rate greater than 20% according to his habit, he can set the threshold of the stenosis rate to 0.2. The blood vessel segment whose stenosis rate is greater than the threshold is called the first characteristic blood vessel segment. In this embodiment, the corresponding first characteristic blood vessel segment can be marked on the chart showing the blood vessel segment of interest. In this embodiment, the marked interval can also be set. For example, if only the first M first characteristic blood vessel segments with the largest stenosis rate are marked, then the first M first characteristic blood vessel segments can be marked with a marking line on the chart, and each The stenosis rate corresponding to the segment is marked below the first characteristic blood vessel segment, which is convenient for the user to observe the stenosis of the blood vessel segment of interest. Optionally, the first characteristic blood vessel segment and the pressure drop corresponding to the characteristic blood vessel segment can also be displayed in the chart of the blood vessel segment of interest. As shown in Figure 9, the two first characteristic blood vessel segments are marked, and the corresponding pressure drop of each segment is △1=0.23 and △2=0.03.

Another embodiment of the present invention discloses a method for processing a blood vessel image. Compared with the foregoing embodiment, when the blood vessel segment of interest contains the second feature, the reference information further includes the second feature information, and the blood vessel image processing method further includes The following steps: reconstruct and display the blood vessel segment of interest and the second feature according to the reference information. The second feature can be set as needed, such as plaque, thrombus, dissection, etc., which is not limited in this embodiment. For example, when the second feature is plaque, in the method disclosed in this embodiment, when detecting and analyzing the image data of the blood vessel segment of interest, image processing can be performed on multiple frames of images in the image data. Methods such as degree, edge detection or level set are used to detect and segment the patches, and obtain their corresponding second feature information. The second feature information, as part of the reference information, can include information such as the area, thickness, and angle of the patch. The area can be accumulated and calculated pixel by pixel, the distance between pixels can be calculated thickness, and the pixel distribution calculation angle can be calculated. Then reconstruct and display the blood vessel segment of interest and the corresponding plaque according to the lumen contour information, media contour information, and second feature information in the reference information. For example, based on the result of plaque segmentation, a three-dimensional plaque geometric model is reconstructed, which is convenient for users Observe the condition of the plaque. For another example, as shown in FIG. 10, the cross-sectional contour of the blood vessel segment of interest and the corresponding plaque can be displayed. When the second feature exists in the blood vessel segment of interest, a correction factor is added to the calculation of FFR, and the calculation of FFR is adjusted to make the calculation result of FFR more accurate. There are many specific methods, for example, you can refer to the method in the patent publication number CN109064442A. It is understandable that the media contour parameters are mainly used for the calculation of reference lumen information, and are not necessary for the detection and reconstruction of the second feature.

Optionally, both the longitudinal section window of the blood vessel segment of interest, the cross-sectional window of the blood vessel segment of interest are displayed, and the three-dimensional reconstruction window of the blood vessel segment of interest is also displayed, which is convenient for the user to observe intuitively and clearly. Optionally, the display mode is set in advance according to the possible types of plaques. For example, you can include all modes to display all types of plaques; vulnerable plaque mode to display lipid plaques, fibrous caps, and macrophages; and calcification mode to display calcified plaques. During use, the patch display mode can be adjusted according to the user's choice, which is convenient for the user to classify and observe. Optionally, different plaques can be displayed with different color markers, which is convenient for the user to observe. Optionally, the statistical parameters corresponding to the plaques, such as the area corresponding to the plaques, are displayed at the same time, so as to facilitate the user's quantitative analysis.

Another embodiment of the present invention discloses a method for processing a blood vessel image. Compared with the foregoing embodiment, the method for processing a blood vessel image further includes the following steps: displaying the longitudinal profile and/or transverse profile of the blood vessel segment of interest according to the reference information. Sectional profile; adjust the longitudinal section profile and/or cross-sectional profile; update the reference information, and/or reference lumen information, and the blood flow reserve (FFR) value according to the adjusted longitudinal section profile and/or cross-sectional profile. In this embodiment, the contour of the blood vessel segment of interest is displayed, and the corresponding segmentation of the lumen contour and the media contour can be observed from the contour. When calculating the reference lumen information, according to the reference lumen information and the lumen contour parameters In multiple processes such as FFR calculation and calibration value calculation, the longitudinal section profile and/or cross section profile can be dynamically adjusted to correct the FFR value. For example, when calculating the reference lumen information, whether the media contour parameters are used to obtain PN and DN, and then the reference lumen is calculated, or the media contour parameters and the normal intima thickness are used to obtain the reference lumen, the media contour Obvious errors in segmentation will affect the calculation of reference lumen information and FFR. Therefore, the corresponding contour can be displayed to assist the user in judging whether there is an obvious error in the segmentation. If there is, the contour can be adjusted according to the user's operation. For example, the media contour or the lumen contour in PN and DN can be adjusted. Changing the media contour parameters and the lumen contour parameters, you can also directly select other frames as PN and/or DN, and you can also animate the ellipse as PN and/or DN in the existing frame, which improves the accuracy of FFR calculation.

Optionally, after obtaining the reference information, before calculating the reference lumen information, the longitudinal section contour and/or the cross section contour of the blood vessel segment of interest are displayed. At this time, the contour can be adjusted according to the user's operation, and the cross-sectional contour can be directly modified in each frame. You can also modify the profile of the longitudinal section at each cutting angle, and update the corresponding cross-sectional profile according to the updated profile of the longitudinal section, thereby improving the reference lumen information and/or reference information, including media profile parameters and lumen profile The accuracy of the parameters. When the chart of the blood vessel segment of interest is displayed, such as the chart of the equivalent diameter, the corresponding chart will also be updated.

Optionally, after completing the detection and analysis of the image data of the blood vessel segment of interest, it may be displayed as shown in FIG. 6. In the figure, "Lumen" corresponds to "lumen", "Media" corresponds to "Media", "Plaque" corresponds to "Plaque", "Min/Max" corresponds to "Minimum/Maximum diameter", and "Burden" corresponds to "Load", "1-Contour" corresponds to "1-contour", "CONFIRM ROI" corresponds to "determine blood vessel segment of interest", "UPDATE CONTOUR" corresponds to "update contour", "COMPUTE FFR" corresponds to "calculate FFR", and "UPDATE FFR" corresponds to "Update FFR", "EDIT" corresponds to "Edit", "DONE" corresponds to "Done", "Equivalent Diam" corresponds to "Equivalent Diameter", "Short Diam" corresponds to "Short Diameter", and "Lumen Short-Long" corresponds to "Lumen long and short axis", "MLA" corresponds to "minimum lumen area", and "Diameter" corresponds to "diameter".

The figure can be divided into two parts: contour and FFR calculation and adjustment. Among them, contour includes the display and adjustment of contour. The right side of the figure is used to display the contour, including the cross-sectional contour and the longitudinal section contour of the blood vessel segment of interest. In the cross-sectional contour and the longitudinal section contour, different markings can be used to mark the corresponding lumen contour and media contour. , And display the area calculated from the lumen profile at the cross section and the minimum and maximum diameters, and the area at the cross section calculated from the media profile, as well as the minimum and maximum diameters. When there is plaque in the blood vessel segment, the area of the plaque at the cross section and the corresponding load rate can also be displayed. In addition, the lower part can display the chart of this segment of blood vessels, such as the equivalent diameter chart in the figure, or switch to display other charts, such as the short axis diameter chart. At the same time, you can edit the contour marked in the chart and the reselection of the blood vessel segment of interest, and re-detect and analyze the image data of the blood vessel segment of interest according to the updated contour to obtain new reference information, and update the FFR calculate. As shown in Figure 7, the calculation result of FFR can also be displayed on the corresponding chart, and the cross-sectional view of the branch can also be displayed together, which is convenient for the user to adjust the contour or side branch in the window to make the value of FFR more precise.

Optionally, when there are side branches in the blood vessel segment of interest, the longitudinal section contour and/or cross-sectional contour of the blood vessel segment of interest are displayed according to the reference information, and according to the adjustment of the side branch, such as the adjustment of the contour and size of the side branch, Update the parameters of the side branch vessel segment, thereby updating the calculation result of FFR, making the calculation of FFR more accurate. When the blood vessel segment of interest is a bifurcation model, the bifurcation node information can be updated according to the adjustment of the bifurcation node, for example, any side branch is reselected as the bifurcation node, thereby updating the calculation result of FFR, making the calculation of FFR more precise. You can also adjust the contour according to the calculation result of the calibration value, for example, translate or rotate the position of each tangent in the cross section and longitudinal section to a suitable position to adjust the side branch section, or directly redraw the lumen of the side branch opening contour. When the blood vessel segment of interest has a first characteristic blood vessel segment, the first characteristic blood vessel segment can also be adjusted, such as adding, deleting or editing.

It is understandable that the adjustment of the longitudinal section profile and/or cross-sectional profile of the blood vessel segment of interest can be achieved by adjusting the media profile, lumen profile, and side branch profile of the corresponding image. The setting and selection can dynamically adjust the FFR calculation result, which has the effect of making the FFR value more accurate.

Another embodiment of the present invention discloses a method for processing a blood vessel image. Compared with the foregoing embodiment, the method for processing a blood vessel image further includes the following step: displaying the fractional blood flow reserve (FFR) value in the form of pseudo-color. On the chart of the blood vessel segment of interest; and/or display the chart of the blood vessel segment of interest and superimpose the simulated retracement curve; and/or reconstruct the blood vessel segment of interest in three dimensions and display the blood vessel segment of interest after the three-dimensional reconstruction. As shown in Fig. 7 and Fig. 15, the specific type of the chart of the blood vessel segment of interest can be selected as required. Displaying the FFR value on the chart of the blood vessel segment of interest in the form of false color can clearly and intuitively reflect the shape of the blood vessel segment of interest and the change of the FFR value, which is convenient for users to observe and analyze. There are many specific display methods, for example, you can refer to the method in the publication number CN109166101A. Superimposing the simulated retracement curve on the chart of the blood vessel segment of interest can assist the user in judging the FFR calculation result based on the simulated retracement curve. Three-dimensional reconstruction of the blood vessel segment of interest, and display of the blood vessel segment of interest after the three-dimensional reconstruction, can be drawn through volume reconstruction, using a ray tracing method, which is easy to implement and has a good reconstruction effect. Optionally, the three-dimensionally reconstructed longitudinal section image, three-dimensional image, and cross-sectional image of the blood vessel segment of interest are displayed, so that the user can comprehensively observe the blood vessel segment of interest. For example, as shown in Fig. 8, a three-dimensional image of the blood vessel segment of interest after three-dimensional reconstruction is displayed. Optionally, the corresponding stents, side branches, plaques, etc. can be identified in the corresponding images, so that the user can better observe and analyze the blood vessel segment of interest. For example, as shown in Figure 14, the three-dimensional reconstructed stent can be displayed. Optionally, as shown in FIG. 7, the corresponding stent may be displayed in the chart of the blood vessel segment of interest.

5, the embodiment of the present invention also discloses a blood vessel image processing system, including: an acquisition module 1 for acquiring image data of the blood vessel segment of interest and blood flow parameters of the blood vessel segment of interest; an analysis module 2. Detect and analyze the image data of the blood vessel segment of interest to obtain reference information. The reference information includes the lumen contour parameters and media contour parameters of the blood vessel segment of interest; the calculation module 3 includes a first calculation unit 31 and a second calculation unit 32 The first calculation unit 31 is used to obtain the reference lumen information according to the media contour parameters, and the second calculation unit 32 is used to calculate the blood flow reserve score of the blood vessel segment of interest ( FFR) value.

By adopting the processing system of the above technical solution, referring to the blood vessel image processing method in the foregoing embodiment, the calculation of the blood vessel pressure difference can be more accurate.

Optionally, the first calculation unit 31 includes a normal frame extraction unit and a reference lumen calculation unit. The normal frame extraction unit is used to obtain the proximal normal frame and the distal normal frame according to the media contour parameters, and the reference lumen calculation unit is used for The reference lumen information is calculated according to the near-end normal frame and the far-end normal frame. With reference to the blood vessel image processing method in the foregoing embodiment, the proximal normal frame and the distal normal frame are determined by replacing the lumen contour parameters with the media contour parameters, and then the corresponding reference lumen is calculated, so that the reference lumen is obtained The information is more accurate, reducing the error caused by determining the PN and DN by the lumen contour parameters when the characteristic information such as plaque exists.

Optionally, the obtaining module 1 is also used to obtain the normal intima thickness of the blood vessel segment of interest, and the first calculation unit 31 obtains the reference lumen information according to the media contour parameter and the normal intima thickness. With reference to the blood vessel image processing method in the foregoing embodiment, the corresponding reference lumen is calculated based on the media contour parameters and the normal intima thickness, so that the obtained reference lumen information is more accurate, and the influence of the intima thickness is eliminated. The FFR value is also more accurate.

Optionally, the reference information also includes side branch vessel segment parameters of the blood vessel segment of interest. The side branch vessel segment parameters are calculated by the analysis module 2 according to the lumen contour parameters. The first calculation unit 31 includes a normal frame extraction unit and a reference lumen. The calculation unit, the normal frame extraction unit is used to obtain the proximal normal frame and the distal normal frame according to the media contour parameters, and the reference lumen calculation unit is used to calculate according to the side branch blood vessel segment parameters, the proximal normal frame and the distal normal frame Refer to lumen information. With reference to the blood vessel image processing method in the foregoing embodiment, the corresponding reference lumen information is calculated through the media contour parameters and the side branch vessel segment parameters, so that the obtained reference lumen information is more accurate, and the corresponding FFR value is also more accurate.

Optionally, the reference information also includes side branch vessel segment parameters of the blood vessel segment of interest. The side branch vessel segment parameters are calculated by the analysis module 2 according to the lumen contour parameters. The first calculation unit 31 includes a normal frame extraction unit and a reference lumen. The calculation unit, the normal frame extraction unit is used to divide the blood vessel segment of interest into multiple sub-segments according to the side branch vessel segment parameters, and obtain the normal frame in each sub-segment according to the media contour parameters. The reference lumen calculation unit is used to The normal frame in each sub-segment gets the reference lumen information. With reference to the blood vessel image processing method in the foregoing embodiment, multiple normal frames are acquired to calculate the reference lumen information, which increases the sampling amount and uses side branch segmentation to be more reasonable, thus making the calculation of the reference lumen information more accurate.

Optionally, it further includes a first display module, and the calculation module 3 further includes a third calculation unit. The third calculation unit is used to calculate the calibration value at each side branch according to the reference lumen information and the side branch blood vessel segment parameters. The display module is used to display the chart of the blood vessel segment of interest, and displays each side branch in the corresponding position of the chart according to the side branch blood vessel segment parameters, and/or the first display module is also used to display the cross-sectional profile of the side branch, and The calibration value is displayed. With reference to the blood vessel image processing method in the foregoing embodiment, the user can help the user to judge the rationality of the segmentation of each side branch and the reference lumen information, so that the user can intuitively and comprehensively observe the blood vessel segment of interest, and observe the corresponding media contour and tube. Whether there are obvious errors in the cavity contour.

Optionally, the blood vessel image processing system further includes a correction module. The acquisition module 1 is also used to acquire the blood vessel position of the blood vessel segment of interest, and the correction module is used to correct the blood flow reserve (FFR) of the blood vessel segment of interest according to the blood vessel position. value. With reference to the blood vessel image processing method in the foregoing embodiment, the algorithm for detecting and analyzing image data is adjusted according to the position of the blood vessel, or the FFR value is corrected according to the blood vessel position, which can make the FFR value more accurate.

Optionally, the blood vessel image processing system further includes a second display module, the reference information also includes side branch blood vessel segment parameters of the blood vessel segment of interest, the side branch blood vessel segment parameters are calculated from the lumen contour parameters, and the acquisition module 1 also uses To obtain the blood vessel type of the blood vessel segment of interest according to the position of the blood vessel, when the blood vessel type is a bifurcation model: the analysis module 2 obtains the bifurcation node information of the blood vessel segment of interest according to the side branch vessel segment parameters; the second display module displays the blood vessel of interest The longitudinal section window of the segment, and according to the bifurcation node information, use different colors to identify the main branch and branch of the blood vessel segment of interest in the longitudinal section window. With reference to the blood vessel image processing method in the foregoing embodiment, it is convenient for the user to observe the bifurcation of the blood vessel segment of interest. At the same time, when calculating FFR, the FFR is corrected according to the information of the bifurcation node, so that the calculation result of FFR is more accurate.

Optionally, the acquisition module 1 includes a first acquisition unit, a second acquisition unit, a reconstruction calculation unit, and a display unit. The first acquisition unit is used to acquire image data of the target blood vessel and corresponding acquisition parameters. The acquisition parameters include layer thickness and pixels. The reconstruction calculation unit is used to perform reconstruction calculation according to the image data and acquisition parameters of the target blood vessel, the display unit is used to display the reconstructed target blood vessel image, and the second acquisition unit is used to obtain the selected blood vessel segment of interest in the image Image data. With reference to the blood vessel image processing method in the foregoing embodiment, the acquisition of the image data of the blood vessel segment of interest can be made more convenient, intuitive, and easy to operate.

Optionally, the acquisition module 1 further includes a re-sampling unit, the re-sampling unit is used to re-sample and re-order the image data of the target blood vessel acquired by the first acquisition unit, and the reconstruction calculation unit is used to perform re-sampling and re-ordering according to the re-ordered target blood vessel Image data and acquisition parameters are reconstructed and calculated. With reference to the blood vessel image processing method in the foregoing embodiment, the problem of chaotic frames that may exist in the image is overcome, so that the subsequent reference information obtained is more accurate, and the calculation load in the reconstruction and display process is reduced.

Optionally, the acquisition module 1 further includes a registration unit. The registration unit is used to register the image of the target blood vessel to correct errors in the acquisition process of the image data of the target blood vessel. The display unit is used to display the registered image data. image. With reference to the blood vessel image processing method in the foregoing embodiment, image registration can eliminate the influence of catheter displacement during the image data collection process, facilitate observation, and make the reference information obtained by subsequent detection and analysis of image data more accurate.

Optionally, it further includes a third display module, the reference information also includes stent information, the acquisition module 1 is also used to acquire stent parameters of the blood vessel segment of interest, and the analysis module 2 is also used to detect the stent and reconstruct the stent according to the stent parameters, and The stent is evaluated to obtain stent information. The stent information includes stent position and stent contour information. The third display module is used to display the longitudinal section window of the blood vessel segment of interest, and mark the stent with pseudo-color bars in the longitudinal section window according to the stent information. With reference to the blood vessel image processing method in the foregoing embodiment, the accuracy of FFR calculation for the blood vessel segment of interest with stent placement is improved and the user can observe and understand the state of the stent.

Optionally, it further includes a fourth display module, and the calculation module 3 further includes a fourth calculation unit configured to quantify the first characteristic blood vessel segment whose stenosis rate is greater than the threshold according to the reference lumen information and the reference information, and the fourth The display module is used to display the chart of the blood vessel segment of interest, and mark the first characteristic blood vessel segment whose stenosis rate is in the set interval in the chart. With reference to the blood vessel image processing method in the foregoing embodiment, it is convenient for the user to observe the stenosis of the blood vessel segment of interest.

Optionally, it further includes a fifth display module. When the blood vessel segment of interest includes the second feature, the reference information further includes second feature information, and the analysis module 2 is further configured to reconstruct the blood vessel segment of interest and the second feature based on the reference information, The fifth display module is used to display the blood vessel segment of interest and the second feature. Refer to the blood vessel image processing method in the foregoing embodiment to facilitate the user to observe the second feature, such as the state of the plaque, and when the second feature exists in the blood vessel segment of interest, a correction factor is added to the FFR calculation to adjust the FFR calculation , Which makes the calculation result of FFR more accurate.

Optionally, it further includes an adjustment module. The adjustment module includes a display unit, an adjustment unit, and an update unit. The section profile and/or cross-sectional profile, the updating unit is used to update the reference information, and/or reference lumen information, and the blood flow reserve (FFR) value according to the adjusted longitudinal section profile and/or cross-sectional profile. With reference to the blood vessel image processing method in the foregoing embodiment, the longitudinal section contour and/or cross-sectional contour of the blood vessel segment of interest can be adjusted by adjusting the media contour, lumen contour, and side branch contour of the corresponding image. To achieve this, users can set and select according to their needs, and can dynamically adjust the FFR calculation results, which has the effect of making the FFR value more accurate.

Optionally, it further includes a sixth display module, which is used to display the fractional blood flow reserve (FFR) value on the chart of the blood vessel segment of interest in a pseudo-color form, and/or the displayed blood vessel segment of interest The chart superimposes and displays the simulated retracement curve, and/or three-dimensional reconstruction of the blood vessel segment of interest, and displays the three-dimensional reconstruction of the blood vessel segment of interest. With reference to the blood vessel image processing method in the foregoing embodiment, it is convenient for the user to better observe and analyze the blood vessel segment of interest.

It is understandable that for the display modules appearing in different embodiments of the blood vessel image processing system, these display modules can be separate and independent so as to be able to display corresponding information and images at the same time, or they can be combined and displayed alternately. For example, the display image and information can be switched by pressing the button, which can be specifically set according to the needs of the user.

The embodiment of the present invention also discloses a computing device, including: a processor, which is suitable for implementing various instructions; a memory, which is suitable for storing multiple instructions, and the instructions are suitable for being loaded by the processor and executed by any of the foregoing embodiments. The processing method of blood vessel images.

The embodiment of the present invention also discloses a storage medium, which stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executed by any one of the blood vessel image processing methods in the foregoing embodiments.

The various embodiments disclosed in this application may be implemented in hardware, software, firmware, or a combination of these implementation methods. The embodiments of the present application can be implemented as a computer program or program code executed on a programmable system including at least one processor and a storage system (including volatile and non-volatile memory and/or storage elements) , At least one input device and at least one output device. Program codes can be applied to input instructions to perform the functions described in this application and generate output information. The output information can be applied to one or more output devices in a known manner. For the purposes of this application, a processing system includes any system having a processor such as, for example, a digital signal processor (DSP), a microcontroller, an application specific integrated circuit (ASIC), or a microprocessor.

The program code can be implemented in a high-level programming language or an object-oriented programming language to communicate with the processing system. When needed, assembly language or machine language can also be used to implement the program code. In fact, the mechanism described in this application is not limited to the scope of any particular programming language. In either case, the language can be a compiled language or an interpreted language.

In some cases, the disclosed embodiments may be implemented in hardware, firmware, software, or any combination thereof. The disclosed embodiments can also be implemented as instructions carried by or stored on one or more transient or non-transitory machine-readable (eg, computer-readable) storage media, which can be executed by one or more processors. Read and execute. For example, the instructions can be distributed through a network or through other computer-readable media. Therefore, a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (for example, a computer), including, but not limited to, floppy disks, optical disks, optical disks, read-only memories (CD-ROMs), magnetic Optical disk, read only memory (ROM), random access memory (RAM), erasable programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), magnetic or optical card, flash memory, or A tangible machine-readable memory used to transmit information (for example, carrier waves, infrared signals, digital signals, etc.) using the Internet with electric, optical, acoustic, or other forms of propagating signals. Therefore, a machine-readable medium includes any type of machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (for example, a computer).

In the drawings, some structural or method features may be shown in a specific arrangement and/or order. However, it should be understood that such a specific arrangement and/or ordering may not be required. Rather, in some embodiments, these features may be arranged in a different manner and/or order than shown in the illustrative drawings. In addition, the inclusion of structural or method features in a particular figure does not imply that such features are required in all embodiments, and in some embodiments, these features may not be included or may be combined with other features.

It should be noted that each module/unit mentioned in each device embodiment of this application is a logical module/unit. Physically, a logical module/unit can be a physical module/unit or a physical module/unit. A part of the unit can also be realized by a combination of multiple physical modules/units. The physical realization of these logical modules/units is not the most important. The combination of the functions implemented by these logical modules/units is the solution to this application. The key to the technical question raised. In addition, in order to highlight the innovative part of this application, the above-mentioned device embodiments of this application do not introduce modules/units that are not closely related to solving the technical problems raised by this application. This does not mean that the above-mentioned device embodiments do not exist. Other modules/units.

Although the present invention has been illustrated and described by referring to certain preferred embodiments of the present invention, those of ordinary skill in the art should understand that the above content is a further detailed description of the present invention in combination with specific embodiments and cannot be considered The specific implementation of the present invention is only limited to these descriptions. Those skilled in the art can make various changes in form and details, including some simple deductions or substitutions, without departing from the spirit and scope of the present invention.

Claims

A method for processing blood vessel images is characterized in that it comprises the following steps:

Obtain image data of the blood vessel segment of interest;

Acquiring the blood flow parameters of the blood vessel segment of interest;

Detecting and analyzing the image data of the blood vessel segment of interest to obtain reference information, the reference information including the lumen contour parameters and the media contour parameters of the blood vessel segment of interest;

Obtaining reference lumen information according to the media contour parameters;

The blood flow reserve score value of the blood vessel segment of interest is calculated according to the blood flow parameter, the reference information and the reference lumen information.
The method for processing blood vessel images according to claim 1, wherein the step of obtaining the reference lumen information according to the media contour parameters comprises:

Obtaining the near-end normal frame and the far-end normal frame according to the media contour parameters, and calculating the reference lumen information according to the near-end normal frame and the far-end normal frame;

or,

Obtain the normal intima thickness of the blood vessel segment of interest, and obtain the reference lumen information according to the media contour parameter and the normal intima thickness.
The method for processing blood vessel images according to claim 1, wherein the reference information further includes side branch blood vessel segment parameters of the blood vessel segment of interest, and the side branch blood vessel segment parameters are determined by the lumen profile parameters. The step of obtaining reference lumen information according to the media contour parameters by calculation includes:

Obtaining the proximal normal frame and the distal normal frame according to the media contour parameters, and calculating the reference lumen information according to the side branch vessel segment parameters, the proximal normal frame and the distal normal frame;

or,

Dividing the blood vessel segment of interest into multiple sub-segments according to the parameters of the side branch blood vessel segment,

Obtain the normal frames in each of the sub-segments according to the media contour parameters,

The reference lumen information is obtained according to the normal frame in each sub-segment.
The method for processing blood vessel images according to claim 3, further comprising the following steps:

Calculating a calibration value at each side branch according to the reference lumen information and the side branch blood vessel segment parameters;

Displaying the chart of the blood vessel segment of interest, and displaying each of the side branches at the corresponding position of the chart according to the side branch blood vessel segment parameters;

And/or display the cross-sectional profile of the side support, and display the calibration value.
The method for processing blood vessel images according to claim 1, further comprising the following steps:

Acquiring the blood vessel position of the blood vessel segment of interest;

The blood flow reserve score value is corrected according to the position of the blood vessel.
The method for processing blood vessel images according to claim 5, wherein the reference information further includes side branch blood vessel segment parameters of the blood vessel segment of interest, and the side branch blood vessel segment parameters are determined by the lumen profile parameters. It is calculated that the method for processing the blood vessel image further includes the following steps:

Obtaining the blood vessel type of the blood vessel segment of interest according to the position of the blood vessel;

When the blood vessel type is a bifurcation model:

Obtaining bifurcation node information of the blood vessel segment of interest according to the parameters of the side branch blood vessel segment;

Display the longitudinal section window of the blood vessel segment of interest;

According to the bifurcation node information, the main branches and branches of the blood vessel segment of interest are identified in the longitudinal section window with different colors.
The method for processing blood vessel images according to claim 1, wherein the step of acquiring image data of the blood vessel segment of interest comprises:

Acquiring image data of the target blood vessel and corresponding acquisition parameters, where the acquisition parameters include layer thickness and pixel size;

Reconstructing and displaying the image of the target blood vessel according to the image data of the target blood vessel and the acquisition parameters;

Obtain image data of the selected blood vessel segment of interest in the image.
8. The method for processing blood vessel images according to claim 7, wherein the step of reconstructing and displaying the image of the target blood vessel based on the image data of the target blood vessel and the acquisition parameters comprises:

Re-sampling and re-ordering the image data of the target blood vessel,

Reconstruct and display the image of the target blood vessel according to the reordered image data of the target blood vessel and the acquisition parameters;

or,

Reconstruct the image of the target blood vessel according to the image data of the target blood vessel and the acquisition parameters,

Registering the image of the target blood vessel to correct errors in the acquisition process of the image data of the target blood vessel;

Display the registered image.
The method for processing blood vessel images according to claim 1, wherein the reference information further includes stent information, and the method for processing blood vessel images further comprises the following steps:

Acquiring the stent parameters of the blood vessel segment of interest;

Detecting the stent and reconstructing the stent according to the stent parameters, and evaluating the stent to obtain the stent information, the stent information including stent position and stent contour information;

Display the longitudinal section window of the blood vessel segment of interest;

According to the bracket information, the bracket is identified by a pseudo-color bar in the longitudinal section window.
The method for processing blood vessel images according to claim 1, further comprising the following steps:

Quantify the first characteristic blood vessel segment whose stenosis rate is greater than a threshold value according to the reference lumen information and the reference information;

Display the chart of the blood vessel segment of interest;

Mark the first characteristic blood vessel segment with the stenosis rate in the set interval in the graph.
The blood vessel image processing method according to claim 1, wherein when the blood vessel segment of interest contains a second feature, the reference information further includes second feature information, and the blood vessel image processing method further comprises The following steps:

The vessel segment of interest and the second feature are reconstructed and displayed according to the reference information.
The method for processing blood vessel images according to claim 1, further comprising the following steps:

Displaying the longitudinal section contour and/or the cross section contour of the blood vessel segment of interest according to the reference information;

Adjusting the profile of the longitudinal section and/or the profile of the cross section;

The reference information, and/or the reference lumen information, and the blood flow reserve score value are updated according to the adjusted longitudinal section profile and/or the cross section profile.
The method for processing blood vessel images according to claim 1, further comprising the following steps:

Displaying the blood flow reserve score value on the chart of the blood vessel segment of interest in a pseudo-color form;

And/or display the chart of the blood vessel segment of interest and superimpose the simulated retracement curve;

And/or three-dimensionally reconstruct the blood vessel segment of interest, and display the blood vessel segment of interest after the three-dimensional reconstruction.
A processing system for blood vessel images, which is characterized in that it comprises:

An acquisition module for acquiring image data of the blood vessel segment of interest and blood flow parameters of the blood vessel segment of interest;

The analysis module detects and analyzes the image data of the blood vessel segment of interest to obtain reference information, and the reference information includes the lumen contour parameters and media contour parameters of the blood vessel segment of interest;

The calculation module includes a first calculation unit and a second calculation unit. The first calculation unit is used to obtain reference lumen information according to the media contour parameters, and the second calculation unit is used to obtain reference lumen information according to the blood flow parameters, The reference information and the reference lumen information are calculated to obtain the blood flow reserve score value of the blood vessel segment of interest.
The blood vessel image processing system according to claim 14, wherein the first calculation unit comprises a normal frame extraction unit and a reference lumen calculation unit, and the normal frame extraction unit is configured to perform according to the media contour parameters The near-end normal frame and the far-end normal frame are obtained, and the reference lumen calculation unit is configured to calculate the reference lumen information according to the near-end normal frame and the far-end normal frame.
The blood vessel image processing system according to claim 14, wherein the acquisition module is further configured to acquire the normal intima thickness of the blood vessel segment of interest, and the first calculation unit is based on the media contour parameter And the normal intima thickness to obtain the reference lumen information.
The blood vessel image processing system of claim 14, wherein the reference information further includes side branch blood vessel segment parameters of the blood vessel segment of interest, and the side branch blood vessel segment parameters are determined by the analysis module according to the The lumen contour parameters are calculated, and the first calculation unit includes a normal frame extraction unit and a reference lumen calculation unit, wherein,

The normal frame extraction unit is used to obtain the proximal normal frame and the distal normal frame according to the media contour parameters, and the reference lumen calculation unit is used to obtain the proximal normal frame according to the side branch blood vessel segment parameters and the proximal normal frame. And calculating the remote normal frame to obtain the reference lumen information;

or,

The normal frame extraction unit is used to divide the blood vessel segment of interest into multiple sub-segments according to the side branch blood vessel segment parameters, and obtain the normal frame in each of the sub-segments according to the media contour parameters, so The reference lumen calculation unit is used to obtain the reference lumen information according to the normal frame in each sub-segment.
The blood vessel image processing system according to claim 17, further comprising a first display module, and the calculation module further includes a third calculation unit, the third calculation unit being configured to perform according to the reference lumen information And the side branch blood vessel segment parameters to calculate the calibration value at each side branch, the first display module is used to display the chart of the blood vessel segment of interest, and according to the side branch blood vessel segment parameters, each of the The side support is displayed at the corresponding position of the chart, and/or the first display module is also used to display the cross-sectional profile of the side support and display the calibration value.
The blood vessel image processing system according to claim 14, further comprising a correction module, the acquisition module is also used to acquire the blood vessel position of the blood vessel segment of interest, and the correction module is used to obtain the blood vessel position according to the blood vessel The position corrects the blood flow reserve score value of the blood vessel segment of interest.
The blood vessel image processing system according to claim 19, further comprising a second display module, the reference information further includes side branch blood vessel segment parameters of the blood vessel segment of interest, and the side branch blood vessel segment parameters Calculated by the lumen contour parameters, the acquisition module is also used to acquire the blood vessel type of the blood vessel segment of interest according to the position of the blood vessel. When the blood vessel type is a bifurcation model: the analysis module The side branch blood vessel segment parameters obtain the bifurcation node information of the blood vessel segment of interest; the second display module displays the longitudinal section window of the blood vessel segment of interest, and displays the bifurcation node information in different colors according to the bifurcation node information. The longitudinal section window identifies the main branch and branch of the blood vessel segment of interest.
The blood vessel image processing system according to claim 14, wherein the acquisition module includes a first acquisition unit, a second acquisition unit, a reconstruction calculation unit, and a display unit, and the first acquisition unit is used to acquire a target blood vessel The image data of the target vessel and the corresponding acquisition parameters, where the acquisition parameters include layer thickness and pixel size, the reconstruction calculation unit is used to perform reconstruction calculations based on the image data of the target blood vessel and the acquisition parameters, and the display unit is used for The reconstructed image of the target blood vessel is displayed, and the second obtaining unit is used to obtain image data of the selected blood vessel segment of interest in the image.
The blood vessel image processing system according to claim 21, wherein:

The acquisition module further includes a re-sampling unit, the re-sampling unit is used to re-sample and re-order the image data of the target blood vessel acquired by the first acquisition unit, and the reconstruction calculation unit is used to re-sampling Performing reconstruction calculation on the image data of the target blood vessel and the acquisition parameters;

or,

The acquisition module further includes a registration unit, the registration unit is used to register the image of the target blood vessel to correct errors in the acquisition process of the image data of the target blood vessel, and the display unit is used for Display the registered image.
The blood vessel image processing system according to claim 14, further comprising a third display module, the reference information further includes stent information, and the acquisition module is further configured to acquire stent parameters of the blood vessel segment of interest , The analysis module is also used to detect the stent and reconstruct the stent according to the stent parameters, and evaluate the stent to obtain the stent information. The stent information includes stent position and stent contour information, so The third display module is used to display the longitudinal section window of the blood vessel segment of interest, and mark the stent with a pseudo-color bar in the longitudinal section window according to the stent information.
The blood vessel image processing system according to claim 14, further comprising a fourth display module, and the calculation module further includes a fourth calculation unit, the fourth calculation unit being configured to perform according to the reference lumen information And the reference information to quantify the first characteristic blood vessel segment whose stenosis rate is greater than a threshold, and the fourth display module is used to display a chart of the blood vessel segment of interest and mark that the stenosis rate in the chart is within a set interval The first characteristic blood vessel segment.
The blood vessel image processing system according to claim 14, further comprising a fifth display module, when the blood vessel segment of interest contains a second feature, the reference information further comprises second feature information, The analysis module is further configured to reconstruct the blood vessel segment of interest and the second feature according to the reference information, and the fifth display module is configured to display the blood vessel segment of interest and the second feature.
The blood vessel image processing system according to claim 14, further comprising an adjustment module, the adjustment module comprising a display unit, an adjustment unit and an update unit, and the display unit is configured to display the The longitudinal section profile and/or the cross-sectional profile of the blood vessel segment of interest, the adjustment unit is used to adjust the longitudinal section profile and/or the cross-sectional profile, and the update unit is used to adjust the longitudinal section profile according to the adjusted longitudinal section profile. The profile and/or the cross-sectional profile update the reference information, and/or the reference lumen information, and the blood flow reserve score value.
The blood vessel image processing system according to claim 14, further comprising a sixth display module, the sixth display module is used to display the blood flow reserve value in the form of false color on the interest On the graph of the blood vessel segment, and/or the graph of the blood vessel segment of interest displayed and superimposed to display the simulated retracement curve, and/or the blood vessel segment of interest is reconstructed in three dimensions, and the three-dimensional reconstructed blood vessel segment of interest is displayed. Vascular segment.
A computing device, characterized in that it comprises:

Processor, suitable for implementing various instructions;

The memory is adapted to store a plurality of instructions, and the instructions are adapted to be loaded by the processor and execute the blood vessel image processing method according to any one of claims 1-13.
A storage medium, wherein the storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the blood vessel image processing method according to any one of claims 1-13.