Intravascular ultrasound image processing method, system, equipment and medium

Abstract

The invention relates to the field of image processing, and discloses an intravascular ultrasonic image processing method, system and device and a medium, and the method comprises the steps: firstly obtaining a CAG image and an IVUS image sequence of a target blood vessel; then three-dimensional coordinate data of the target blood vessel in a three-dimensional space and first blood vessel diameter change data of the target blood vessel are calculated based on the CAG images of the multiple shooting angles; wherein; performing image segmentation on each frame of IVUS image in the IVUS image sequence to obtain a vascular membrane edge image of each frame of IVUS image, and calculating second blood vessel diameter change data of the target blood vessel based on the vascular membrane edge image; and finally, a three-dimensional model of the target blood vessel is constructed based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data and the vascular membrane edge image, the three-dimensional model of the target blood vessel can be constructed based on blood vessel diameter changes determined by different images and coordinates in a three-dimensional space, and user requirements are met.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to an intravascular ultrasound image processing method, system, device and medium. Background Art

[0002] Both X-ray coronary angiography (CAG) images and intravascular ultrasound (IVUS) images can be used for auxiliary diagnosis. Among them, IVUS images record the internal information of blood vessels, and CAG images record the spatial structure information of blood vessels.

[0003] In the related art, IVUS images and CAG images can be fused to reconstruct the coronary arteries.

[0004] However, the related art reconstructs a two-dimensional image, which cannot support operations such as rotation and switching of viewing angles and cannot meet user needs. Summary of the invention

[0005] In order to solve or partially solve the problems existing in the related art, the present application provides an intravascular ultrasound image processing method, system, device and medium, which can perform three-dimensional modeling of the intravascular ultrasound image and obtain a three-dimensional image of the intravascular ultrasound image to meet user needs.

[0006] The first aspect of the present application provides an intravascular ultrasound image processing method, comprising:

[0007] Obtain CAG images and IVUS image sequences of the target blood vessels;

[0008] Calculating the three-dimensional coordinate data of the target blood vessel in three-dimensional space and calculating the first blood vessel diameter change data of the target blood vessel based on the CAG images at multiple shooting angles; wherein the three-dimensional coordinate data at least includes the three-dimensional coordinates of the blood vessel axis;

[0009] Performing image segmentation on each frame of the IVUS image in the IVUS image sequence to obtain a vascular membrane edge image of each frame of the IVUS image, and calculating second blood vessel diameter change data of the target blood vessel based on the vascular membrane edge image;

[0010] A three-dimensional model of the target blood vessel is constructed based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data, and the blood vessel membrane edge image.

[0011] A second aspect of the present application provides an intravascular ultrasound image processing device, comprising:

[0012] An acquisition module, used to obtain CAG images and IVUS image sequences of target blood vessels;

[0013] A first calculation module, used to calculate the three-dimensional coordinate data of the target blood vessel in the three-dimensional space and calculate the first blood vessel diameter change data of the target blood vessel based on the CAG images at multiple shooting angles; wherein the three-dimensional coordinate data at least includes the three-dimensional coordinates of the blood vessel axis;

[0014] a second calculation module, configured to perform image segmentation on each frame of the IVUS image in the IVUS image sequence, obtain a vascular membrane edge image of each frame of the IVUS image, and calculate second vascular diameter change data of the target blood vessel based on the vascular membrane edge image;

[0015] A construction module is used to construct a three-dimensional model of the target blood vessel based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data and the blood vessel membrane edge image.

[0016] A third aspect of the present application provides an electronic device, including:

[0017] Processor; and

[0018] The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is caused to execute the method as described above.

[0019] A fourth aspect of the present application provides a computer-readable storage medium having executable code stored thereon. When the executable code is executed by a processor of an electronic device, the processor is caused to execute the method as described above.

[0020] The technical solution provided by this application may have the following beneficial effects:

[0021] The intravascular ultrasound image processing method provided by the present application first obtains a CAG image and an IVUS image sequence of a target blood vessel; then, based on the CAG images at multiple shooting angles, three-dimensional coordinate data of the target blood vessel in three-dimensional space and first blood vessel diameter change data of the target blood vessel are calculated; wherein the three-dimensional coordinate data at least includes the three-dimensional coordinates of the blood vessel axis; then, each frame of the IVUS image in the IVUS image sequence is segmented to obtain a vascular membrane edge image of each frame of the IVUS image, and second blood vessel diameter change data of the target blood vessel is calculated based on the vascular membrane edge image; finally, a three-dimensional model of the target blood vessel is constructed based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data and the vascular membrane edge image. The three-dimensional model of the target blood vessel can be constructed based on the blood vessel diameter changes determined by different images and the coordinates in three-dimensional space, thereby meeting user needs.

[0022] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other objects, features and advantages of the present application will become more apparent by describing in more detail exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0024] Figure 1 A schematic diagram of a flow chart of an intravascular ultrasound image processing method shown in the present application;

[0025] Figure 2 is a schematic diagram of image segmentation shown in an embodiment of the present application;

[0026] Figure 3 It is a schematic diagram of the principle of creating a three-dimensional model shown in an embodiment of the present application;

[0027] Figure 4 A schematic diagram of the structure of an intravascular ultrasound image processing device provided in an embodiment of the present application;

[0028] Figure 5 It is a schematic diagram of the structure of an electronic device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0030] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0031] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0032] In the related art, CAG images (Coronary Angiography) are also called coronary artery angiography images, and IVUS image sequences can provide different information about blood vessels respectively. The related art lacks a related technical solution for three-dimensional modeling of CAG images and IVUS image sequences.

[0033] In an embodiment of the present application, a method, device, system and medium for processing intravascular ultrasound images are provided, which can perform three-dimensional modeling and display of blood vessels by combining CAG images and IVUS image sequences.

[0034] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0035] See also Figure 1 , Figure 1 The present application shows a flow chart of an intravascular ultrasound image processing method.

[0036] An intravascular ultrasound image processing method provided in an embodiment of the present application includes:

[0037] S100 , obtaining a CAG image and an IVUS image sequence of a target blood vessel.

[0038] In the embodiment of the present application, the CAG image is a coronary angiography image, and before shooting, the coordinate data of the X-ray transmitting device and the receiving device in the three-dimensional space can be pre-recorded. The shooting angle of the CAG image can be at least two, and the CAG image can be shot based on different shooting angles. Based on different shooting angles, more blood vessel observation effects can be obtained, and the three-dimensional space coordinate system corresponding to the CAG image at the specified shooting angle is used as the basis for constructing the three-dimensional space.

[0039] The target blood vessel may be a blood vessel segment of interest specified by a user, and the CAG image in the embodiment of the present application may only retain the blood vessel segment of interest, while deleting images of other blood vessel segments other than the blood vessel segment of interest.

[0040] The IVUS image sequence of the target blood vessel includes multiple frames of IVUS images, which are cross-sectional images of the target blood vessel and may include images of the vascular endothelium, vascular adventitia, and other tissues inside and outside the blood vessel. In actual use, the acquisition time of the IVUS image can correspond to the pulling speed of the probe, for example, less than 10 mm / s, or other speeds, which can be set according to actual needs, and accordingly, the number of IVUS images matching the pulling speed can be obtained.

[0041] In the embodiment of the present application, there may be a rotation angle between two frames of IVUS images. Therefore, each IVUS image in the IVUS image sequence in the embodiment of the present application may be an image after image registration.

[0042] In the application, a certain frame, such as a target frame IVUS image, is used as a reference, and a registration operation can be performed based on the similarity between the target frame IVUS image and the next frame IVUS image. For example, the next frame IVUS image is rotated, and the similarity between the next frame IVUS image and the target frame IVUS image is calculated during the rotation process. When the similarity exceeds the rotation angle corresponding to the predetermined threshold, or the rotation angle does not exceed the predetermined threshold after the rotation is completed, the rotation angle with the largest similarity is selected as the rotation angle corresponding to the next frame IVUS image, and then the next frame IVUS image is rotated based on the rotation angle to achieve registration with the target frame IVUS image. The first frame IVUS image in the IVUS image sequence can be used as the starting point, and all IVUS images can be registered in sequence to obtain the IVUS image sequence used in the subsequent embodiments of the present application.

[0043] S101. Calculate the three-dimensional coordinate data of the target blood vessel in three-dimensional space and calculate the first blood vessel diameter change data of the target blood vessel based on the CAG images at multiple shooting angles; wherein the three-dimensional coordinate data at least includes the three-dimensional coordinates of the blood vessel axis.

[0044] In an embodiment of the present application, multiple CAG images at different shooting angles of the basic CAG image can be obtained. Based on the CAG images at different shooting angles, the axis pixel coordinates of the vascular axis of the target blood vessel can be calculated, thereby determining the three-dimensional coordinates of the vascular axis in the aforementioned three-dimensional space.

[0045] The first blood vessel diameter change data of the target blood vessel can also be calculated based on the CAG image. Since the diameters of the target blood vessel in each blood vessel segment are different, in order to reflect such differences, the internal width change curve of the target blood vessel in the CAG image can be calculated and used as the first blood vessel diameter change data.

[0046] It is understandable that in the embodiment of the present application, the target blood vessel may be a blood vessel corresponding to the aforementioned IVUS image sequence. After obtaining the CAG basic image, the background in the image may be deleted, and the coronary artery blood vessel image in the image may be identified based on the image recognition algorithm. Then, the target blood vessel is retained, and the blood vessel images corresponding to other blood vessels not related to the target blood vessel are deleted to obtain the CAG image in the embodiment of the present application. In the application, the target blood vessel segment may be determined based on the user's specified operation. Based on this, the CAG image in the embodiment of the present application may calculate the width of the target blood vessel in the blood vessel contour, for example, by calculating the distance based on algorithms such as pixel distance transformation, and obtaining the target blood vessel width, thereby obtaining the first blood vessel diameter change data based on multiple target blood vessel widths.

[0047] S102, performing image segmentation on each frame of the IVUS image in the IVUS image sequence to obtain a vascular membrane edge image of each frame of the IVUS image, and calculating second blood vessel diameter change data of the target blood vessel based on the vascular membrane edge image.

[0048] In an embodiment of the present application, for each frame of IVUS image in the IVUS image sequence, image segmentation can be performed to obtain a vascular membrane edge image of the target blood vessel in each frame of IVUS image. The vascular membrane edge can be a vascular intima edge and / or a vascular adventitia edge, that is, the vascular membrane edge image can include an image corresponding to the target vascular intima and / or the target vascular adventitia, and the image can be embodied in the form of a curve. In the application, the edge of the target vascular membrane in the IVUS image can be automatically identified using an image segmentation algorithm, and a vascular membrane edge image including only the target vascular intima edge and / or the target vascular adventitia edge is obtained.

[0049] After the vascular membrane edge image of the target blood vessel is obtained, the second blood vessel diameter change data of the target blood vessel can be further calculated. Based on each frame of the vascular membrane edge image, the blood vessel diameter corresponding to each frame of the vascular membrane edge image can be calculated respectively according to the vascular intima or the vascular adventitia as a closed figure at the angle calibrated when the image is collected, so that the target blood vessel diameter change curve of the target blood vessel is obtained by sequentially connecting multiple blood vessel diameters as the second target blood vessel diameter change data.

[0050] S104: construct a three-dimensional model of the target blood vessel based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data, and the blood vessel membrane edge image.

[0051] In the embodiment of the present application, the first blood vessel diameter change data can be obtained based on the CAG image, the second blood vessel diameter change data can be obtained based on the IVUS image sequence, and three-dimensional data and a vascular membrane edge image can be obtained. Therefore, in the three-dimensional space, the first blood vessel diameter change data and the second blood vessel change data can determine the angle with the same direction as the CAG image and the IVUS image, and then determine the specific position of each blood vessel segment in the three-dimensional space according to the three-dimensional coordinate data, and can construct a three-dimensional model of the target blood vessel based on the aforementioned multiple data.

[0052] It is understandable that there is one first blood vessel diameter change data and there may be multiple second blood vessel diameter change data, and the second blood vessel diameter change data with the greatest similarity to the first blood vessel diameter change data may be used as a basis for creating a three-dimensional model.

[0053] It can be seen from the above embodiments that the embodiments of the present application can calculate the coordinate data of the vascular axis of the target blood vessel in the three-dimensional space based on the CAG image and can calculate the vascular membrane edge image based on the IVUS image, and then can create a three-dimensional model of the target blood vessel in the three-dimensional space, which can meet user needs.

[0054] In the above-mentioned embodiment, the relevant process of calculating the three-dimensional coordinate data of the target blood vessel is introduced, and this process is described in detail below.

[0055] In the embodiment of the present application, the three-dimensional coordinate data of the target blood vessel in the three-dimensional space is calculated based on the CAG images at multiple shooting angles, including:

[0056] Extracting the axis pixel position of the blood vessel axis in the target blood vessel in the CAG image at each shooting angle respectively;

[0057] The three-dimensional coordinates of the blood vessel axis in the three-dimensional space are calculated based on the plurality of axis pixel positions, and the three-dimensional coordinates corresponding to all the blood vessel axes are used as the three-dimensional coordinate data of the target blood vessel.

[0058] In the embodiment of the present application, at each shooting angle, the internal width data of the blood vessel in the CAG image where the target blood vessel is located can be extracted respectively, and the axis pixel position of the blood vessel axis of the target blood vessel can also be obtained, and then the three-dimensional coordinate data of the blood vessel axis of the target blood vessel in the three-dimensional space can be determined. Among them, the three-dimensional coordinate data can be obtained based on the projection calculation of the target blood vessel in the three-dimensional space, or based on algorithms such as triangulation and projection transformation. It is understandable that if the internal width data of the blood vessel cannot be obtained from a certain shooting angle, the internal width data of the blood vessel is determined from another shooting angle. It is understandable that the blood vessel axis is formed by connecting the center points of the blood vessel cross section.

[0059] It is understandable that the width of the target blood vessel may be different in each blood vessel segment, and therefore, the intravascular width data of each blood vessel segment can be calculated through CAG images taken at different angles, and therefore, a blood vessel internal width variation curve can be obtained based on each blood vessel internal width data corresponding to the target blood vessel. The blood vessel internal width variation curve can be used as the first blood vessel diameter variation data of the target blood vessel.

[0060] It can be seen that in the embodiment of the present application, the three-dimensional coordinate data of the vascular axis of the target blood vessel in the three-dimensional space can be determined through CAG images of multiple shooting angles, and the first blood vessel inner diameter change data including the internal width change curve of the target blood vessel can be obtained, which lays a data foundation for creating a three-dimensional model.

[0061] In the embodiment of the present application, image segmentation can be performed on each frame of IVUS image in the IVUS image sequence to obtain a vascular membrane edge image of each frame of IVUS image.

[0062] In the embodiment of the present application, the intima position and adventitia position in each frame of IVUS image can be determined based on the image grayscale algorithm, wherein the image grayscale algorithm can be the intima position and adventitia position obtained by processing the image based on the grayscale change of the image. Figure 2 , Figure 2 It is a schematic diagram of image segmentation shown in an embodiment of the present application. Figure 2 In the IVUS image 201 , the intimal contour 2021 corresponding to the intimal position of the target blood vessel and the adventitial contour 2022 corresponding to the adventitial position can be obtained based on the image grayscale algorithm, and then the vascular membrane edge image 202 can be drawn.

[0063] Further, the centroid 2021 of the vascular endothelium in the calculated vascular edge image 202 can be obtained. In this way, the centroid corresponding to each frame of the IVUS image in the IVUS image sequence can be obtained, and then, the vascular endothelium diameter change curve corresponding to the target blood vessel can be obtained as the vascular endothelium diameter change data of the target blood vessel. Since the IVUS image can be observed by 360-degree rotation, different vascular endothelium diameter change curves can be obtained based on different observation angles, and the vascular endothelium diameter change data corresponding to multiple observation angles are used as the second vascular diameter change data of the target blood vessel. It can be understood that the vascular diameter of a blood vessel observed at different angles is different. If it is drawn from 360 different angles, 360 different diameter change curves can be obtained. The number of observation angles in the embodiment of the present application can be set according to actual needs.

[0064] Thus, a blood vessel internal width change curve and multiple blood vessel endothelial diameter change curves can be obtained, and then the viewing angle at which the CAG image and the IVUS image have the same observation angle can be determined.

[0065] In the embodiment of the present application, constructing the three-dimensional model of the target blood vessel based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data and the blood vessel membrane edge image includes:

[0066] Comparing the first blood vessel diameter change data with the second blood vessel diameter change data obtained at multiple observation angles for similarity, and determining the target measurement angle corresponding to the second blood vessel diameter data with the greatest similarity;

[0067] Determine the blood vessel direction of the diameter of the target blood vessel in the three-dimensional space based on the three-dimensional coordinate data of the blood vessel axis of the target blood vessel in the three-dimensional space, the shooting direction of the blood vessel axis in the three-dimensional space, and the target measurement angle;

[0068] Determine the coordinates of the inner membrane edge curve and the outer membrane edge curve in each of the blood vessel membrane edge images in the three-dimensional space based on the blood vessel direction;

[0069] In the three-dimensional space, a curved surface is used to connect adjacent intimal edge curves and adventitial edge curves to construct a three-dimensional model of the target blood vessel.

[0070] In the embodiment of the present application, the target measurement angle corresponding to the second blood vessel diameter data with the greatest similarity is the same angle as the shooting angle of the first blood vessel diameter data. The straight line where the diameter corresponding to the second blood vessel diameter data is located can be used as the straight line disposed in the shooting direction, and the three-dimensional coordinate data of the blood vessel axis in the three-dimensional space is determined, and the shooting direction obtained above is also determined, so that the blood vessel direction of the blood vessel diameter in the three-dimensional space can be determined.

[0071] Based on this, the coordinates of the vascular membrane edge image in three-dimensional space can be obtained, and then a series of rings consisting of multiple vascular intimal edge curves and vascular adventitia edge curves along the vascular axis can be obtained. Then, the adjacent vascular intimal edge curves and adjacent vascular adventitia edge curves are connected using surfaces to construct a three-dimensional model of the target blood vessel. Figure 3 As shown, Figure 3 It is a schematic diagram of the principle of creating a three-dimensional model shown in an embodiment of the present application. Figure 3 In the figure, the outer membrane contour edge connection line 301 and the inner membrane contour edge connection line 302 are used to connect each blood vessel membrane edge image 300 respectively, so as to construct a three-dimensional model of the target blood vessel.

[0072] The three-dimensional model constructed based on the embodiment of the present application has no blind spots and can provide structural information and the degree of lesions of the blood vessel wall, thereby providing a better data foundation and judgment basis for subsequent user diagnosis and other operations.

[0073] Corresponding to the method embodiment, the embodiment of the present application also provides an intravascular ultrasound image processing device.

[0074] See also Figure 4 , Figure 4 A schematic diagram of the structure of an intravascular ultrasound image processing device provided in an embodiment of the present application.

[0075] An intravascular ultrasound image processing device shown in an embodiment of the present application includes:

[0076] Acquisition module 1, used to obtain CAG images and IVUS image sequences of target blood vessels;

[0077] A first calculation module 2, used for calculating the three-dimensional coordinate data of the target blood vessel in the three-dimensional space and calculating the first blood vessel diameter change data of the target blood vessel based on the CAG images at multiple shooting angles; wherein the three-dimensional coordinate data at least includes the three-dimensional coordinates of the blood vessel axis;

[0078] A second calculation module 3 is used to perform image segmentation on each frame of the IVUS image in the IVUS image sequence to obtain a vascular membrane edge image of each frame of the IVUS image, and calculate the second blood vessel diameter change data of the target blood vessel based on the vascular membrane edge image;

[0079] The construction module 4 is used to construct a three-dimensional model of the target blood vessel based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data and the blood vessel membrane edge image.

[0080] In some embodiments, the calculating the three-dimensional coordinate data of the target blood vessel in the three-dimensional space based on the CAG images at multiple shooting angles includes:

[0081] Extracting the axis pixel position of the blood vessel axis in the target blood vessel in the CAG image at each shooting angle respectively;

[0082] The three-dimensional coordinates of the blood vessel axis in the three-dimensional space are calculated based on the plurality of axis pixel positions, and the three-dimensional coordinates corresponding to all the blood vessel axes are used as the three-dimensional coordinate data of the target blood vessel.

[0083] In some embodiments, the calculating the first blood vessel diameter change data of the target blood vessel based on the CAG images at multiple shooting angles includes:

[0084] Determine intravascular width data of the target blood vessel in each blood vessel segment in the CAG images at multiple shooting angles;

[0085] First blood vessel diameter change data of the target blood vessel is calculated based on the intra-blood vessel width data.

[0086] In some embodiments, performing image segmentation on each frame of the IVUS image in the IVUS image sequence to obtain a vascular membrane edge image of each frame of the IVUS image includes:

[0087] Determine the vascular intima position and vascular adventitia position corresponding to each frame of IVUS image in the IVUS image sequence based on an image grayscale change algorithm;

[0088] The vascular membrane edge image corresponding to the IVUS image is drawn according to the vascular intima position and the vascular adventitia position corresponding to each frame of the IVUS image.

[0089] In some embodiments, the calculating the second blood vessel diameter change data of the target blood vessel based on the blood vessel membrane edge image includes:

[0090] Determine the centroid of the vascular intima in each frame of the vascular membrane edge image;

[0091] The blood vessel intima diameter change data at multiple observation angles are calculated based on the centroid as second blood vessel diameter change data of the target blood vessel.

[0092] In some embodiments, each frame of IVUS sub-image in the IVUS image is an image after eliminating rotation errors based on the similarity of images at adjacent positions.

[0093] In some embodiments, constructing the three-dimensional model of the target blood vessel based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data, and the blood vessel membrane edge image includes:

[0094] Comparing the first blood vessel diameter change data with the second blood vessel diameter change data obtained at multiple observation angles for similarity, and determining the target measurement angle corresponding to the second blood vessel diameter data with the greatest similarity;

[0095] Determine the blood vessel direction of the diameter of the target blood vessel in the three-dimensional space based on the three-dimensional coordinate data of the blood vessel axis of the target blood vessel in the three-dimensional space, the shooting direction of the blood vessel axis in the three-dimensional space, and the target measurement angle;

[0096] Determine the coordinates of the inner membrane edge curve and the outer membrane edge curve in each of the blood vessel membrane edge images in the three-dimensional space based on the blood vessel direction;

[0097] In the three-dimensional space, a curved surface is used to connect adjacent intimal edge curves and adventitial edge curves to construct a three-dimensional model of the target blood vessel.

[0098] The device of the embodiment of the present application can calculate the coordinate data of the vascular axis of the target blood vessel in three-dimensional space based on the CAG image and can calculate the vascular membrane edge image based on the IVUS image, and then can create a three-dimensional model of the target blood vessel in three-dimensional space, which can meet user needs.

[0099] Figure 5 It is a schematic diagram of the structure of an electronic device shown in an embodiment of the present application.

[0100] See also Figure 5 , an embodiment of the present application provides an electronic device 500 including a memory 501 and a processor 502.

[0101] The processor 502 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0102] The memory 501 may include various types of storage units, such as system memory, read-only memory (ROM) and permanent storage devices. Among them, ROM can store static data or instructions required by the processor 502 or other modules of the computer. The permanent storage device can be a readable and writable storage device. The permanent storage device can be a non-volatile storage device that will not lose the stored instructions and data even if the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In some other embodiments, the permanent storage device can be a removable storage device (such as a floppy disk, optical drive). The system memory can be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory can store some or all instructions and data required by the processor at run time.

[0103] In addition, the memory 501 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (e.g., DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and magnetic disks and / or optical disks may also be used. In some embodiments, the memory 501 may include a removable storage device that can be read and / or written, such as a laser disc (CD), a read-only digital versatile disk (e.g., DVD-ROM, double-layer DVD-ROM), a read-only Blu-ray disk, an ultra-density optical disk, a flash memory card (e.g., SD card, min SD card, Micro-SD card, etc.), a magnetic floppy disk, etc. The computer-readable storage medium does not include carrier waves and instantaneous electronic signals transmitted wirelessly or wired.

[0104] The memory 501 stores executable codes, and when the executable codes are processed by the processor 502 , the processor 502 can execute part or all of the methods described above.

[0105] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0106] Alternatively, the present application can also be implemented as a computer-readable storage medium (or non-transitory machine-readable storage medium or machine-readable storage medium) on which executable code (or computer program or computer instruction code) is stored. When the executable code (or computer program or computer instruction code) is executed by a processor of an electronic device (or server, etc.), the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0107] The embodiments of the present application have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for processing intravascular ultrasound images, characterized in that: include: Obtain CAG images and IVUS image sequences of the target blood vessels; Calculating the three-dimensional coordinate data of the target blood vessel in three-dimensional space and calculating the first blood vessel diameter change data of the target blood vessel based on the CAG images at multiple shooting angles; wherein the three-dimensional coordinate data at least includes the three-dimensional coordinates of the blood vessel axis; Performing image segmentation on each frame of the IVUS image in the IVUS image sequence to obtain a vascular membrane edge image of each frame of the IVUS image, and calculating second blood vessel diameter change data of the target blood vessel based on the vascular membrane edge image; A three-dimensional model of the target blood vessel is constructed based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data, and the blood vessel membrane edge image.

2. The method according to claim 1, characterized in that The calculating the three-dimensional coordinate data of the target blood vessel in the three-dimensional space based on the CAG images at multiple shooting angles includes: Extracting the axis pixel position of the blood vessel axis in the target blood vessel in the CAG image at each shooting angle respectively; The three-dimensional coordinates of the blood vessel axis in the three-dimensional space are calculated based on the plurality of axis pixel positions, and the three-dimensional coordinates corresponding to all the blood vessel axes are used as the three-dimensional coordinate data of the target blood vessel.

3. The method according to claim 1, characterized in that: The calculating the first blood vessel diameter change data of the target blood vessel based on the CAG images at multiple shooting angles includes: Determine intravascular width data of the target blood vessel in each blood vessel segment in the CAG images at multiple shooting angles; First blood vessel diameter change data of the target blood vessel is calculated based on the intra-blood vessel width data.

4. The method according to claim 1, characterized in that: The step of performing image segmentation on each frame of the IVUS image in the IVUS image sequence to obtain a vascular membrane edge image of each frame of the IVUS image comprises: Determine the vascular intima position and vascular adventitia position corresponding to each frame of IVUS image in the IVUS image sequence based on an image grayscale change algorithm; The vascular membrane edge image corresponding to the IVUS image is drawn according to the vascular intima position and the vascular adventitia position corresponding to each frame of the IVUS image.

5. The method according to claim 4, characterized in that The calculating the second blood vessel diameter change data of the target blood vessel based on the blood vessel membrane edge image comprises: Determine the centroid of the vascular intima in each frame of the vascular membrane edge image; The blood vessel intima diameter change data at multiple observation angles are calculated based on the centroid as second blood vessel diameter change data of the target blood vessel.

6. The method according to claim 4 or 5, characterized in that: Each frame of IVUS sub-image in the IVUS image is an image after eliminating rotation errors based on the similarity of images at adjacent positions.

7. The method according to claim 1, characterized in that The constructing the three-dimensional model of the target blood vessel based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data and the blood vessel membrane edge image includes: Comparing the first blood vessel diameter change data with the second blood vessel diameter change data obtained at multiple observation angles for similarity, and determining the target measurement angle corresponding to the second blood vessel diameter data with the greatest similarity; Determine the blood vessel direction of the diameter of the target blood vessel in the three-dimensional space based on the three-dimensional coordinate data of the blood vessel axis of the target blood vessel in the three-dimensional space, the shooting direction of the blood vessel axis in the three-dimensional space, and the target measurement angle; Determine the coordinates of the inner membrane edge curve and the outer membrane edge curve in each of the blood vessel membrane edge images in the three-dimensional space based on the blood vessel direction; In the three-dimensional space, a curved surface is used to connect adjacent intimal edge curves and adventitial edge curves to construct a three-dimensional model of the target blood vessel.

8. An intravascular ultrasound image processing device, characterized in that: include: An acquisition module, used for obtaining CAG images and IVUS image sequences of target blood vessels; A first calculation module, used to calculate the three-dimensional coordinate data of the target blood vessel in the three-dimensional space and calculate the first blood vessel diameter change data of the target blood vessel based on the CAG images at multiple shooting angles; wherein the three-dimensional coordinate data at least includes the three-dimensional coordinates of the blood vessel axis; a second calculation module, configured to perform image segmentation on each frame of the IVUS image in the IVUS image sequence, obtain a vascular membrane edge image of each frame of the IVUS image, and calculate second vascular diameter change data of the target blood vessel based on the vascular membrane edge image; A construction module is used to construct a three-dimensional model of the target blood vessel based on the first blood vessel diameter change data, the second blood vessel diameter change data, the three-dimensional coordinate data and the blood vessel membrane edge image.

9. An electronic device, characterized in that: include: processor; as well as A memory having executable codes stored thereon, which, when executed by the processor, causes the processor to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having executable codes stored thereon, which, when executed by a processor of an electronic device, causes the processor to execute the method according to any one of claims 1 to 7.

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