Method for determining parameters of a vascular stent, electronic device and storage medium

Abstract

The application provides a blood vessel stent parameter determination method, an electronic device and a storage medium. The determination method comprises the following steps: segmenting a pre-acquired medical image to obtain a blood vessel mask image; obtaining a blood vessel center line corresponding to a blood vessel region of interest according to the blood vessel mask image; determining a cross section corresponding to each center point on the blood vessel center line according to the blood vessel mask image; and determining a diameter of a blood vessel stent corresponding to the blood vessel region of interest according to the cross section corresponding to each center point on the blood vessel center line. The application can accurately determine the parameters of the blood vessel stent, and effectively improves the diagnosis efficiency and accuracy.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method for determining vascular stent parameters, an electronic device, and a storage medium. Background Technology

[0002] A vascular stent is an implanted stent that opens up narrowed or blocked blood vessels. It is primarily used for cardiovascular and cerebrovascular diseases such as coronary artery disease, myocardial infarction, and cerebral infarction. Vascular stents effectively promote normal blood flow, facilitate the recovery of vascular remodeling function, and effectively prevent vascular elasticity recoil. Some stents can even prevent the blood vessel from contracting and becoming blocked again. They are mainly classified into coronary stents, cerebral stents, renal artery stents, and aortic stents.

[0003] With the development of medical image processing technology, a technique for measuring vascular parameters based on vascular images has emerged. This technique enables interactive vascular parameter measurement, allowing for the measurement of relevant parameters in parts of interest within the blood vessel. This facilitates the analysis of vascular conditions and the selection of appropriate vascular stents for treatment.

[0004] In traditional techniques, vascular parameters are usually measured based on two-dimensional vascular images. However, two-dimensional vascular images lack information and cannot fully express the information of the blood vessels, resulting in inaccurate vascular parameter measurements. This makes it difficult to conduct in-depth analysis of the vascular condition and thus makes it impossible to accurately select the corresponding type of vascular stent for treatment.

[0005] It should be noted that the information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method, electronic device, and storage medium for determining vascular stent parameters, which can accurately select the optimal vascular stent model through precise vascular parameters.

[0007] To achieve the above objectives, the present invention provides a method for determining vascular stent parameters, the method comprising:

[0008] The pre-acquired medical images are segmented to obtain vascular mask images;

[0009] Based on the vascular mask image, obtain the center line of the vascular region of interest;

[0010] The diameter of the vascular stent corresponding to the region of interest is determined based on the cross-section corresponding to each center point on the vascular centerline.

[0011] Optionally, the method further includes:

[0012] Based on the blood vessel centerline and the cross-section corresponding to each center point on the blood vessel centerline, the reconstructed structure of the blood vessel wall of the region of interest is obtained;

[0013] The length of the vascular stent corresponding to the region of interest is determined based on the vascular centerline and the reconstructed vascular wall structure.

[0014] Optionally, obtaining the reconstructed vessel wall structure of the region of interest based on the vessel centerline and the cross-section corresponding to each center point on the vessel centerline includes:

[0015] Based on the cross-section corresponding to each center point on the center line of the blood vessel, obtain the maximum tangential diameter of the blood vessel corresponding to each center point;

[0016] Based on each center point on the center line of the blood vessel and its corresponding maximum internal diameter of the blood vessel, a corresponding closed contour curve is generated.

[0017] The closed contour curves are surface-fitted using a surface fitting method to obtain the reconstructed vascular wall structure of the region of interest.

[0018] Optionally, determining the length of the vascular stent corresponding to the region of interest based on the vascular centerline and the reconstructed vascular wall structure includes:

[0019] Calculate the path length of the blood vessel centerline based on the coordinates of all center points on the centerline.

[0020] Based on the reconstructed vascular wall structure, calculate the path lengths of the outer and inner curves of the vascular wall corresponding to the region of interest.

[0021] The length of the vascular stent corresponding to the region of interest is determined based on the path length of the vessel centerline, the path length of the outer curve side of the vessel wall, and the path length of the inner curve side.

[0022] Optionally, calculating the path length of the blood vessel centerline based on the coordinates of each center point on the blood vessel centerline includes:

[0023] Calculate the Euclidean distance between all adjacent two center points based on the coordinates of all center points on the central line of the blood vessel.

[0024] Add the Euclidean distances between all adjacent pairs of said center points to obtain the path length of said vessel centerline.

[0025] Optionally, calculating the path lengths of the outer curve and the inner curve of the vessel wall corresponding to the region of interest based on the reconstructed vessel wall structure includes:

[0026] Based on the reconstructed vascular wall structure, the outer curvature and inner curvature of the vascular wall corresponding to the region of interest are obtained;

[0027] Based on the coordinates of all pixels on the outer curve, calculate the length of the outer curve path of the vessel wall corresponding to the region of interest.

[0028] The length of the inner curve path of the vessel wall corresponding to the region of interest is calculated based on the coordinates of all pixels on the inner curve.

[0029] Optionally, obtaining the outer curvature and inner curvature of the vessel wall corresponding to the region of interest based on the reconstructed vessel wall structure includes:

[0030] For each center point on the central line of the aforementioned blood vessel:

[0031] Obtain the two intersection points on the reconstructed blood vessel wall structure that intersect the normal to the center point;

[0032] Form a vector from the two intersection points and the center point, and calculate the angle between each vector and the normal vector of the center point.

[0033] The intersection points of vectors with an angle less than 90° are taken as the path points on the outer curved side of the blood vessel wall corresponding to the center point, and the intersection points of vectors with an angle greater than 90° are taken as the path points on the inner curved side of the blood vessel wall corresponding to the center point.

[0034] Based on the outward curve path points of the vessel wall corresponding to all center points, obtain the outward curve of the vessel wall corresponding to the region of interest. Based on the inward curve path points of the vessel wall corresponding to all center points, obtain the inward curve of the vessel wall corresponding to the region of interest.

[0035] Optionally, determining the length of the vascular stent corresponding to the region of interest based on the vascular centerline and the reconstructed vascular wall structure further includes:

[0036] Calculate the Euclidean length of the blood vessel centerline based on the coordinates of the starting center point and the ending center point of the centerline.

[0037] The curvature of the region of interest is calculated based on the path length and Euclidean length of the vessel centerline.

[0038] The length of the vascular stent corresponding to the region of interest is determined based on the curvature.

[0039] Optionally, the method further includes:

[0040] The model of the vascular stent is determined based on its diameter and length.

[0041] Optionally, determining the diameter of the vascular stent corresponding to the region of interest based on the cross-section corresponding to each center point on the vascular centerline includes:

[0042] Based on the cross-section corresponding to each center point on the center line of the blood vessel, obtain the maximum tangential diameter of the blood vessel corresponding to each center point;

[0043] The maximum internal diameter of the vessel corresponding to the region of interest is determined based on the maximum internal diameter of the vessel corresponding to all the center points.

[0044] The diameter of the vascular stent corresponding to the region of interest is determined based on the maximum inner diameter of the blood vessel.

[0045] To achieve the above objectives, the present invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the method for determining vascular stent parameters described above.

[0046] To achieve the above objectives, the present invention also provides a readable storage medium storing a computer program, which, when executed by a processor, implements the method for determining vascular stent parameters described above.

[0047] Compared with existing technologies, the method, electronic device, and storage medium for determining vascular stent parameters provided by this invention have the following advantages: This invention first segments a pre-acquired medical image to obtain a vascular mask image; then, based on the vascular mask image, it obtains the vascular centerline corresponding to the region of interest; next, based on the vascular mask image, it determines the cross-section corresponding to each center point on the vascular centerline; and finally, based on the cross-section corresponding to each center point on the vascular centerline, it determines the diameter of the vascular stent corresponding to the region of interest. Therefore, this invention, by obtaining the vascular centerline corresponding to the region of interest and the cross-section corresponding to each center point on the vascular centerline, and determining the diameter of the vascular stent corresponding to the region of interest based on the cross-section corresponding to each center point on the vascular centerline, can accurately determine the diameter of the vascular stent corresponding to the region of interest, laying a good foundation for accurately determining the stent model and effectively improving diagnostic efficiency and accuracy. Furthermore, the present invention reconstructs the internal structure of the region of interest based on the blood vessel centerline and the cross-section corresponding to each center point on the blood vessel centerline to obtain the reconstructed blood vessel wall structure. Based on the blood vessel centerline and the reconstructed blood vessel wall structure, the length of the vascular stent corresponding to the region of interest is determined, which further provides a basis for accurately determining the type of vascular stent and is more helpful in accurately determining the type of vascular stent. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating a method for determining vascular stent parameters according to an embodiment of the present invention.

[0049] Figure 2 This is a schematic diagram of a blood vessel mask image in a specific example of the present invention;

[0050] Figure 3 This is a schematic diagram illustrating the specific process for determining the diameter of a vascular stent in one embodiment of the present invention.

[0051] Figure 4 This is a schematic diagram of a blood vessel cross-section in a specific example of the present invention;

[0052] Figure 5 This is a schematic diagram illustrating the specific process of obtaining the maximum and minimum intravascular diameters corresponding to the center point in one embodiment of the present invention.

[0053] Figure 6 This is a schematic diagram of the process for obtaining the reconstructed blood vessel wall structure according to one embodiment of the present invention;

[0054] Figure 7This is a schematic diagram of the center line of the blood vessel corresponding to the region of interest in a specific example of the present invention.

[0055] Figure 8 This is a schematic diagram of the cross-section corresponding to the region of interest in a specific example of the present invention;

[0056] Figure 9 This is a schematic diagram of a blood vessel wall reconstruction structure in a specific example of the present invention;

[0057] Figure 10 This is a schematic diagram of the process for determining the length of a vascular stent in one embodiment of the present invention.

[0058] Figure 11 This is a schematic diagram illustrating the acquisition of the outer curve and the inner curve in one embodiment of the present invention.

[0059] Figure 12 This is a schematic diagram of the process for obtaining the center line of a blood vessel in one embodiment of the present invention;

[0060] Figure 13 This is a flowchart illustrating the process of determining the target path between the starting node and the target node in one embodiment of the present invention.

[0061] Figure 14 This is a schematic flowchart of the first correction process in one embodiment of the present invention;

[0062] Figure 15 This is a schematic flowchart of the second correction process in one embodiment of the present invention;

[0063] Figure 16 This is a schematic diagram illustrating the acquisition of the second mapping point in a specific example of the present invention;

[0064] Figure 17 This is a schematic diagram of the process for obtaining a cross-section according to one embodiment of the present invention;

[0065] Figure 18 This is a schematic diagram of a connected component obtained using the watershed algorithm in a specific example of the present invention;

[0066] Figure 19 This is a block diagram of an electronic device according to one embodiment of the present invention.

[0067] The reference numerals in the attached figures are as follows:

[0068] Outline -1; Centerline -2; Outer curve -31; Inner curve -32; Path point -4; Peak points -51, 52;

[0069] Processor-101; Communication interface-102; Memory-103; Communication bus-104. Detailed Implementation

[0070] The method for determining vascular stent parameters, electronic equipment, and storage medium proposed in this invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of this invention will become clearer from the following description. It should be noted that the drawings are in a very simplified form and use non-precise proportions, only for the purpose of conveniently and clearly illustrating the embodiments of this invention. Please refer to the drawings to make the objectives, features, and advantages of this invention more apparent and understandable. It should be understood that the structures, proportions, sizes, etc., depicted in the accompanying drawings are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed in the specification, and are not intended to limit the implementation conditions of this invention. Any modifications to the structure, changes in the proportional relationships, or adjustments to the size, provided that the effects and objectives achieved by this invention are the same or similar, should still fall within the scope of the technical content disclosed in this invention.

[0071] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0072] Furthermore, in the description of this specification, the reference to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., means that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0073] The core idea of ​​this invention lies in providing a method, electronic device, and storage medium for determining vascular stent parameters, which allows for accurate selection of the optimal vascular stent model through precise vascular parameters. It should be noted that the method for determining vascular stent parameters in this invention can be applied to the electronic device described in this invention. This electronic device can be a personal computer, a mobile terminal, etc., and the mobile terminal can be a mobile phone, tablet computer, or other hardware device with various operating systems. Furthermore, it should be noted that although this invention uses the aortic arch as the region of interest and determines the aortic vascular stent model by acquiring the vascular parameters of the aortic arch region as an example, this does not constitute a limitation of the invention. As those skilled in the art will understand, the method for determining vascular stent parameters provided by this invention can also be used to determine the parameters and models of stents in other vascular locations. Additionally, it should be noted that all calculations in this invention are performed in the world coordinate system. Specifically, based on the pre-acquired mapping relationship between the image coordinate system and the world coordinate system, the coordinates of each pixel in the vascular mask image in the image coordinate system can be converted to coordinates in the world coordinate system before calculation. The mapping relationship between the image coordinate system and the world coordinate system can be obtained from the parameters of the medical image acquisition device.

[0074] To achieve the above-mentioned goals, this invention provides a method for determining vascular stent parameters. Please refer to [the relevant documentation]. Figure 1 The diagram illustrates a flowchart of a method for determining vascular stent parameters according to an embodiment of the present invention. Figure 1 As shown, the method for determining the parameters of the vascular stent includes the following steps:

[0075] Step S100: Segment the pre-acquired medical image to obtain a vascular mask image.

[0076] Step S200: Obtain the center line of the blood vessel corresponding to the region of interest based on the blood vessel mask image.

[0077] Step S300: Based on the vascular mask image, determine the cross-section corresponding to each center point on the vascular centerline.

[0078] Step S400: Determine the diameter of the vascular stent corresponding to the region of interest based on the cross-section corresponding to each center point on the vascular centerline.

[0079] Therefore, this invention obtains the vascular centerline corresponding to the vascular region of interest and the cross-section corresponding to each center point on the vascular centerline, and determines the diameter of the vascular stent corresponding to the vascular region of interest based on the cross-section corresponding to each center point on the vascular centerline. This allows for accurate determination of the diameter of the vascular stent corresponding to the vascular region of interest, laying a good foundation for accurately determining the type of vascular stent and effectively improving diagnostic efficiency and accuracy.

[0080] Specifically, the pre-acquired medical images can be CTA (Computed Tomography Angiography) images, MRA (Magnetic Resonance Angiography) images, or other medical images. These medical images can be acquired using image acquisition devices such as CT and MRI imaging equipment, or obtained through internet searches, or by scanning with a scanning device. The size of the medical images can be set according to specific circumstances, and this invention does not impose any limitations on this; for example, the size of the medical image can be 512×512×130 pixels.

[0081] Preferably, before segmenting the medical image, the method further includes filtering the pre-acquired medical image. Thus, by filtering the acquired medical image (e.g., Gaussian filtering), noise in the medical image can be effectively removed, laying a good foundation for obtaining an accurate vascular mask image.

[0082] Correspondingly, step S100 involves segmenting the filtered medical image to obtain a vascular mask image. It should be noted that, as those skilled in the art will understand, existing image segmentation methods, such as thresholding, region growing, and deep learning-based neural network segmentation, can be used to segment the medical image. This invention does not limit the segmentation method. Please refer to... Figure 2 The diagram illustrates a vascular mask image in a specific example of the present invention. Figure 2 As shown, by segmenting the filtered medical image, a complete aortic vascular mask image can be obtained. In the aortic vascular mask image, the pixel value of the aortic vascular region is 1, and the pixel value of other regions is 0.

[0083] Please continue to refer to this. Figure 3 The diagram illustrates a specific process for determining the diameter of a vascular stent according to an embodiment of the present invention. Figure 3 The step of determining the diameter of the vascular stent corresponding to the region of interest based on the cross-section corresponding to each center point on the vascular centerline includes:

[0084] Based on the cross-section corresponding to each center point on the center line of the blood vessel, obtain the maximum tangential diameter of the blood vessel corresponding to each center point;

[0085] The maximum internal diameter of the vessel corresponding to the region of interest is determined based on the maximum internal diameter of the vessel corresponding to all the center points.

[0086] The diameter of the vascular stent corresponding to the region of interest is determined based on the maximum inner diameter of the blood vessel.

[0087] Therefore, based on the cross-section corresponding to each center point on the blood vessel centerline, the maximum internal diameter of the blood vessel corresponding to that center point can be obtained. By sorting the maximum internal diameters of the blood vessels corresponding to all the center points, the largest maximum internal diameter of the blood vessel (i.e., the maximum internal diameter of the blood vessel corresponding to the region of interest) can be determined. Thus, the diameter of the vascular stent can be determined based on the maximum internal diameter of the blood vessel. The diameter of the vascular stent should be greater than the maximum internal diameter of the blood vessel to ensure that the vascular stent can expand the blood vessel wall after deployment.

[0088] Furthermore, the present invention can also obtain the minimum vascular incision diameter corresponding to each center point based on the cross-section corresponding to each center point on the vascular centerline. By sorting the minimum vascular incision diameters corresponding to all center points, the minimum minimum vascular incision diameter (i.e., the minimum vascular incision diameter corresponding to the region of interest) can be determined. Based on the minimum vascular incision diameter, the diameter of the guidewire in the delivery system used to deliver the vascular stent can be determined. The diameter of the guidewire should be smaller than the minimum vascular incision diameter to ensure that the guidewire can be smoothly inserted into the blood vessel.

[0089] Please continue to refer to this. Figure 4 The diagram illustrates a cross-section of a blood vessel provided in a specific example of the present invention. Figure 4 As shown, the coordinates of point o are the coordinates of the center point, the contour line 1 is the contour curve of the cross section corresponding to the center point o, the length of ab is the maximum internal diameter of the blood vessel corresponding to the center point o (i.e., the maximum internal diameter of the cross section corresponding to the center point o, which is also the maximum internal diameter of the blood vessel corresponding to the region of interest), and the length of cd is the minimum internal diameter of the blood vessel corresponding to the center point o (i.e., the minimum internal diameter of the cross section corresponding to the center point o, which is also the minimum internal diameter of the blood vessel corresponding to the region of interest).

[0090] Further, please refer to Figure 5 The diagram illustrates the specific process for obtaining the maximum and minimum intravascular diameters corresponding to the center point, as provided in one embodiment of the present invention. Figure 5As shown, obtaining the maximum and minimum intravascular diameters corresponding to each center point based on the cross-section corresponding to each center point on the vessel centerline includes:

[0091] For each center point on the central line of the aforementioned blood vessel:

[0092] Map the cross section corresponding to the center point onto the plane Z=0 to obtain the mapping plane corresponding to the center point;

[0093] Based on the position coordinates of each pixel on the mapping plane, the maximum and minimum inscribed diameters of the mapping plane are obtained.

[0094] The maximum tangential diameter of the blood vessel corresponding to the center point is obtained based on the maximum tangential diameter, and the minimum tangential diameter of the blood vessel corresponding to the center point is obtained based on the minimum tangential diameter.

[0095] Therefore, this invention significantly reduces computation by first mapping the cross-sections corresponding to each center point on the blood vessel's central line to a plane with Z=0 (i.e., a plane with Z coordinates of 0, also known as the XOY plane with the world coordinate system as the reference), and then calculating the parameters. Specifically, taking one center point as an example, the cross-section corresponding to that center point can be moved to the plane with Z=0 through rotation and translation operations to obtain the corresponding mapping plane (the Z coordinates of each pixel on the mapping plane are 0). The positional mapping relationship between the mapping plane and the cross-section can be represented by a rotation and translation matrix, with different cross-sections corresponding to different rotation and translation matrices. Based on the position coordinates of each pixel on the mapping plane, the perimeter, area, maximum inscribed diameter, minimum inscribed diameter, coordinates of the contour points corresponding to the maximum inscribed diameter, and coordinates of the contour points corresponding to the minimum inscribed diameter, etc., of the mapping plane can be obtained. Since the perimeter, area, maximum inscribed diameter, and minimum inscribed diameter are fixed properties and do not change with rotation and translation, the perimeter, area, maximum inscribed diameter, and minimum inscribed diameter of the mapping plane are the same as the perimeter, area, maximum inscribed diameter, and minimum inscribed diameter of the cross-section corresponding to the center point. By inversely transforming the contour coordinates of the mapping plane, the coordinates of the contour point corresponding to the maximum inscribed diameter, and the coordinates of the contour point corresponding to the minimum inscribed diameter onto the cross-section using the rotation and translation matrix, the contour coordinates of the cross-section, the coordinates of the contour point corresponding to the maximum inscribed diameter, and the coordinates of the contour point corresponding to the minimum inscribed diameter can be obtained.

[0096] In one exemplary embodiment, the method further includes:

[0097] Based on the blood vessel centerline and the cross-section corresponding to each center point on the blood vessel centerline, the reconstructed structure of the blood vessel wall of the region of interest is obtained;

[0098] The length of the vascular stent corresponding to the region of interest is determined based on the vascular centerline and the reconstructed vascular wall structure.

[0099] Therefore, this invention reconstructs the internal structure of the vessel region of interest based on the vessel centerline and the cross-section corresponding to each center point on the vessel centerline to obtain the reconstructed vessel wall structure. Based on the vessel centerline and the reconstructed vessel wall structure, the length of the vascular stent corresponding to the vessel region of interest is determined, which further provides a basis for accurately determining the type of vascular stent and is more helpful in accurately determining the type of vascular stent.

[0100] Please continue to refer to this. Figure 6 The diagram illustrates, schematically, the process for obtaining a reconstructed vascular wall structure according to an embodiment of the present invention. Figure 6 As shown, obtaining the reconstructed vessel wall structure of the region of interest based on the vessel centerline and the cross-section corresponding to each center point on the vessel centerline includes:

[0101] Based on the cross-section corresponding to each center point on the center line of the blood vessel, obtain the maximum tangential diameter of the blood vessel corresponding to each center point;

[0102] Based on each center point on the center line of the blood vessel and its corresponding maximum internal diameter of the blood vessel, a corresponding closed contour curve is generated.

[0103] The closed contour curves are surface-fitted using a surface fitting method to obtain the reconstructed vascular wall structure of the region of interest.

[0104] Specifically, the maximum tangential diameter of the blood vessel corresponding to each center point can be obtained based on the maximum inscribed diameter of the cross-section corresponding to that center point. Then, a circle is drawn with that center point as the center and the maximum tangential diameter of the blood vessel corresponding to that center point as the diameter to obtain the closed contour curve corresponding to that center point. Finally, a surface fitting method is used to surface-fit all the closed contour curves corresponding to the center points to obtain the reconstructed structure of the blood vessel wall of the region of interest. Please refer to [reference needed]. Figures 7 to 9 ,in Figure 7 A schematic diagram of the blood vessel centerline corresponding to the region of interest in a specific example of the present invention is shown. Figure 8 A schematic diagram of the cross-section corresponding to the region of interest in a specific example of the present invention is shown. Figure 9A schematic diagram of a blood vessel wall reconstruction structure provided by a specific example of the present invention is shown.

[0105] Please continue to refer to this. Figure 10 The diagram illustrates a flowchart of determining the length of a vascular stent according to an embodiment of the present invention. Figure 10 As shown, determining the length of the vascular stent corresponding to the region of interest based on the vascular centerline and the reconstructed vascular wall structure includes:

[0106] Calculate the path length of the blood vessel centerline based on the coordinates of all center points on the centerline.

[0107] Based on the reconstructed vascular wall structure, calculate the path lengths of the outer and inner curves of the vascular wall corresponding to the region of interest.

[0108] The length of the vascular stent corresponding to the region of interest is determined based on the path length of the vessel centerline, the path length of the outer curve side of the vessel wall, and the path length of the inner curve side.

[0109] Therefore, the length of the vascular stent can be determined based on the path length of the vascular centerline, the path length of the outer curved side of the vascular wall, and the path length of the inner curved side. Combined with the diameter of the vascular stent determined above, the model of the vascular stent can be determined.

[0110] Specifically, calculating the path length of the blood vessel centerline based on the coordinates of each center point on the blood vessel centerline includes:

[0111] Calculate the Euclidean distance between all adjacent two center points based on the coordinates of all center points on the central line of the blood vessel.

[0112] Add the Euclidean distances between all adjacent pairs of said center points to obtain the path length of said vessel centerline.

[0113] Therefore, by sequentially calculating the Euclidean distance between each pair of adjacent center points on the blood vessel centerline and summing all the Euclidean distances between each pair of adjacent center points, the path length of the blood vessel centerline can be obtained.

[0114] Further, the step of calculating the outer curvature path length and inner curvature path length of the vessel wall corresponding to the region of interest based on the reconstructed vessel wall structure includes:

[0115] Based on the reconstructed vascular wall structure, the outer curvature and inner curvature of the vascular wall corresponding to the region of interest are obtained;

[0116] Based on the coordinates of all pixels on the outer curve, calculate the length of the outer curve path of the vessel wall corresponding to the region of interest.

[0117] The length of the inner curve path of the vessel wall corresponding to the region of interest is calculated based on the coordinates of all pixels on the inner curve.

[0118] For details, please refer to Figure 9 ,like Figure 9 As shown, in this invention, the curve containing the blood vessel wall on the side with a radius of curvature greater than the blood vessel centerline 2 on the reconstructed blood vessel wall structure is defined as the outer curved curve 31, and the curve containing the blood vessel wall on the side with a radius of curvature less than the blood vessel centerline 2 on the reconstructed blood vessel wall structure is defined as the inner curved curve 32. Therefore, by using the reconstructed blood vessel wall structure, the coordinates of each point on the outer curved curve 31 and the inner curved curve 32 of the blood vessel wall corresponding to the region of interest can be obtained. Then, by sequentially calculating the Euclidean distance between each pair of adjacent points on the outer curved curve 31 and summing the Euclidean distances between all pairs of adjacent points on the outer curved curve 31, the path length of the outer curved curve 31, which is also the outer curved path length of the blood vessel wall corresponding to the region of interest, can be obtained. Similarly, by sequentially calculating the Euclidean distance between each pair of adjacent points on the inner curve 32 and summing the Euclidean distances between all pairs of adjacent points on the inner curve 32, the path length of the inner curve 32 can be obtained, which is also the inner curve path length of the vessel wall corresponding to the region of interest.

[0119] Furthermore, please continue to refer to... Figure 11 The diagram illustrates an embodiment of the present invention for obtaining the outer curve and the inner curve. Figure 11 As shown, obtaining the outer curvature and inner curvature of the vessel wall corresponding to the region of interest based on the reconstructed vessel wall structure includes:

[0120] For each center point on the central line of the aforementioned blood vessel:

[0121] Obtain the two intersection points on the reconstructed blood vessel wall structure that intersect the normal to the center point;

[0122] Form a vector from the two intersection points and the center point, and calculate the angle between each vector and the normal vector of the center point.

[0123] The intersection points of vectors with an angle less than 90° are taken as the path points on the outer curved side of the blood vessel wall corresponding to the center point, and the intersection points of vectors with an angle greater than 90° are taken as the path points on the inner curved side of the blood vessel wall corresponding to the center point.

[0124] Based on the outward curve path points of the vessel wall corresponding to all center points, obtain the outward curve of the vessel wall corresponding to the region of interest. Based on the inward curve path points of the vessel wall corresponding to all center points, obtain the inward curve of the vessel wall corresponding to the region of interest.

[0125] For details, please continue to refer to Figure 9 ,like Figure 9 As shown, taking the center point O as an example, the vector The vector representing the tangent line at the center point O. This represents the normal vector of the center point O. with vector Perpendicular to each other, intersection points C and D are the AND vectors on the reconstructed blood vessel wall structure. The two points where the lines (i.e., the normals) intersect are due to and The angle between them is 0°. and If the angle between the two points is 180°, then intersection point C is taken as the path point on the outer curve of the vessel wall corresponding to center point O, and intersection point D is taken as the path point on the inner curve of the vessel wall corresponding to center point O. Similarly, the outer curve and inner curve path points of the vessel wall corresponding to all center points on the vessel centerline can be obtained. By connecting all the outer curve path points, the outer curve curve of the vessel wall corresponding to the region of interest can be obtained, and by connecting all the inner curve path points, the inner curve curve of the vessel wall corresponding to the region of interest can be obtained. It should be noted that, as those skilled in the art will understand, if the point on the reconstructed vessel wall structure that intersects the normal to the center point is a sub-pixel point, then the pixel on the reconstructed vessel wall structure that is closest to the sub-pixel point is taken as the intersection point with the normal to the center point.

[0126] To further improve the accuracy of the determined vascular stent length, the step of determining the length of the vascular stent corresponding to the region of interest based on the vascular centerline and the reconstructed vascular wall structure further includes:

[0127] Calculate the Euclidean length of the blood vessel centerline based on the coordinates of the starting center point and the ending center point of the centerline.

[0128] The curvature of the region of interest is calculated based on the path length and Euclidean length of the vessel centerline.

[0129] The length of the vascular stent corresponding to the region of interest is determined based on the curvature.

[0130] Specifically, assuming the Euclidean length of the vessel centerline is D1 and the path length of the vessel centerline is D2, then the curvature of the region of interest is D2 / D1. Therefore, by combining the curvature of the region of interest, the path length of the vessel centerline, and the path lengths of the vessel wall on both the outer and inner curved sides, the length of the vascular stent corresponding to the region of interest can be determined more accurately, thus facilitating the accurate determination of the stent model.

[0131] In one exemplary embodiment, the method further includes:

[0132] The model of the vascular stent is determined based on its diameter and length.

[0133] Therefore, by determining the model of the vascular stent based on its diameter and length, the present invention can further improve diagnostic efficiency and accuracy.

[0134] The following explains how to obtain the vascular centerline of the region of interest and the cross-section corresponding to each center point on the vascular centerline.

[0135] Please refer to Figure 12 The diagram illustrates a flowchart of obtaining the vascular centerline according to an embodiment of the present invention. Figure 12 As shown, step S200, obtaining the center line of the blood vessel corresponding to the region of interest based on the blood vessel mask image, includes:

[0136] Based on the vascular mask image, obtain the position coordinates of the starting point and the ending point;

[0137] Based on the position coordinates of the starting point and the ending point, a preset algorithm is used to determine the target path between the starting point and the ending point;

[0138] The target path is taken as the center line of the blood vessel corresponding to the region of interest.

[0139] Specifically, based on actual needs, the center position of the cross-section at the beginning of the region of interest (ROI) on the vascular mask image where the ROI centerline needs to be calculated can be used as the starting point, and the center position of the cross-section at the end of the ROI region can be used as the ending point. Based on the positions of the starting and ending points on the vascular mask image, the coordinates of the starting and ending points (in the world coordinate system, specifically, based on the mapping relationship between the image coordinate system and the world coordinate system, and the positions of the starting and ending points in the image coordinate system) can be obtained. For example, when the ROI region where the ROI centerline needs to be calculated is the aortic arch, the center position of the starting slice layer of the ascending aorta region can be used as the starting point, and the center position of the starting slice layer of the descending aorta region can be used as the ending point. Thus, based on the target path between the starting and ending points, the ROI centerline of the aortic arch region can be obtained.

[0140] It should be noted that, as those skilled in the art will understand, the starting point and the ending point can be selected manually or by a computer according to a pre-set algorithm, and this invention does not impose any limitations on this. Furthermore, it should be noted that in some other embodiments, existing methods for extracting vascular centerlines can also be used, such as methods based on region growing and methods based on vascular centerline models, and this invention does not impose any limitations on this.

[0141] To further improve the accuracy of the extracted vascular centerline, the method for obtaining vascular information provided by this invention further includes:

[0142] Based on the vascular mask image, obtain the position coordinates of the midpoint.

[0143] Correspondingly, determining the target path between the starting point and the ending point using a preset algorithm based on the position coordinates of the starting point and the ending point includes:

[0144] Based on the position coordinates of the starting point, the intermediate point, and the ending point, a preset algorithm is used to determine a first target path between the starting point and the intermediate point, and a second target path between the intermediate point and the ending point.

[0145] Connect the first target path and the second target path to determine the target path between the starting point and the ending point.

[0146] Specifically, the midpoint is a necessary point along the center line of the blood vessel corresponding to the region of interest. Since the midpoint is a necessary point along the center line of the blood vessel to be extracted, the accuracy of the obtained center line of the blood vessel can be further improved.

[0147] Further, the step of using a preset algorithm to determine the first target path between the starting point and the intermediate point includes:

[0148] Using the starting point as the starting node and the intermediate point as the target node, the A* algorithm is used to determine the first target path between the starting point and the intermediate point;

[0149] The step of using a preset algorithm to determine the second target path between the intermediate point and the termination point includes:

[0150] Using the intermediate point as the starting node and the ending point as the target node, the A* algorithm is used to determine the second target path between the intermediate point and the ending point.

[0151] For details, please refer to Figure 13 This diagram illustrates a flowchart of determining the target path between the starting node and the target node according to an embodiment of the present invention. Figure 13 As shown, the target path between the starting node and the target node can be determined using the following steps:

[0152] Step A: Create an open list to store nodes to be detected and a closed list to store detected nodes, and put the starting point into the open list;

[0153] Step B: Determine whether the open list is an empty set. If yes, end the calculation; otherwise, proceed to step C.

[0154] Step C: Sort the cost function F values ​​of each node in the open list, select the node with the smallest cost function F value as the current node, and move the current node from the open list to the closed list, wherein:

[0155] F(P) = w1*G(P) + w2*H(P);

[0156]

[0157]

[0158] In the formula, F(P) is the cost function, G(P) is the actual cost from the starting node to node P, and H(P) is the estimated cost from node P to the ending node D. Let be the Euclidean distance from node P to the terminal node D. Let w1 be the Euclidean distance from node P to its parent node, w2 be the first weight coefficient, and w1 be the second weight coefficient.

[0159] Step D: Determine whether the current node is a termination node. If yes, proceed to step E; otherwise, proceed to step F1.

[0160] Step E: Starting from the termination node, trace back the parent node step by step until the starting node is reached. Connect all the traced nodes sequentially from the starting node to form the target path.

[0161] Step F1: Based on the blood vessel mask image, determine all neighboring nodes in the surrounding area of ​​the current node, and select one of the neighboring nodes as the current neighboring node;

[0162] Step F2: Determine whether the current neighboring node is in the closed list. If yes, proceed to step F3; otherwise, proceed to step F4.

[0163] Step F3: Skip the current neighbor node, and take the next neighbor node as the current neighbor node, then return to execute step F2;

[0164] Step F4: Determine whether the current neighboring node is in the open list. If yes, proceed to step F5; otherwise, proceed to step F6.

[0165] Step F5: Calculate the G value of the current neighbor node relative to the current node. If the newly calculated G value is less than the existing G value of the current neighbor node, update the existing G value of the current neighbor node to the newly calculated G value, update the parent node of the current neighbor node to the current node, and execute step F7.

[0166] Step F6: Add the neighboring node to the open list, set the current node as the parent node of the neighboring node, and execute step F7;

[0167] Step F7: Determine whether the current neighbor node is the last neighbor node. If yes, return to step B; otherwise, proceed to step F8.

[0168] Step F8: Select the next neighboring node as the current neighboring node and return to step F2.

[0169] Specifically, when only the starting node exists in the open list, the starting node is removed from the open list. Each node in the open list has its own stored total cost (F value), actual cost (G value), and estimated cost (H value), which can be respectively referred to as the node's stored total cost (F value), stored actual cost (G value), and stored estimated cost (H value). The starting node's stored actual cost is 0. As the node's parent node information is updated, the node's stored total cost (F value) and stored actual cost (G value) change accordingly. The neighboring nodes adjacent to the starting node initially all have the starting node as their parent node.

[0170] in:

[0171]

[0172]

[0173] When obtaining the neighboring nodes of the current node, the non-zero pixels in the 26 neighborhoods of the current node on the blood vessel mask image (preferably the smoothed blood vessel mask image) are selected as the neighboring nodes of the current node.

[0174] It should be noted that, as those skilled in the art will understand, after traversing all neighboring nodes of the current node, the process returns to step B until the final selected current node is the termination node. From the termination node, the process moves towards its parent node, and then from that parent node towards its own parent node, and so on, until the starting node is reached. The path formed by these nodes is the target path, i.e., the vascular centerline. Furthermore, it should be noted that although this invention uses the A* algorithm as an example, as those skilled in the art will understand, other existing path algorithms, such as breadth-first search, Dijkstra's algorithm, and best-first search, can also be used to determine the target path between the starting node and the termination node. This invention does not limit this approach.

[0175] Therefore, by taking the starting point as the starting node and the intermediate point as the target node, and using... Figure 13 The process shown can obtain the target path (i.e., the first target path) between the starting point and the intermediate point; by using the intermediate point as the starting node and the ending point as the target node, and employing... Figure 4The process shown allows us to obtain the target path (i.e., the second target path) between the intermediate point and the termination point. It should be noted that, as those skilled in the art will understand, in step E, after traversing all neighboring nodes of the current node, we return to step B. Thus, by repeatedly executing steps B to E until the final selected current node is the termination node, we move from the termination node towards its parent node, and from the parent node towards its own parent node, and so on, until we reach the starting node. The path formed by these nodes is the target path.

[0176] Furthermore, the first weighting coefficient is a dynamic coefficient related to the node P. Therefore, by setting the first weighting coefficient to a dynamic coefficient related to the node P, the present invention can achieve dynamic adjustment of the cost function, thereby facilitating efficient finding of the target path.

[0177] Specifically, before using the A* algorithm to determine the target path between the starting point and the ending point, the method further includes:

[0178] For each non-zero pixel in the blood vessel mask image, its surrounding neighboring pixels are traversed from near to far until the zero pixel closest to the non-zero pixel is found. The distance between the non-zero pixel and the zero pixel is calculated and set as the pixel value of the non-zero pixel to obtain the blood vessel distance transformation image.

[0179] The formula for calculating the first weighting coefficient w1 is as follows:

[0180] w1=β*e ΔP

[0181] Wherein, β is the first adjustment factor, and 0 < β < 1, and ΔP is the absolute value of the difference between the maximum pixel value in the blood vessel distance transformation image and the pixel value of node P in the blood vessel distance transformation image.

[0182] Since the center point of each cross-section of a blood vessel is furthest from the vessel wall, the pixel value of the pixel at the center point of each cross-section of the blood vessel region is the largest in the blood vessel distance transformation image. If the pixel value of node P in the blood vessel distance transformation image is larger, the value of w1 is smaller. That is, the first weight coefficient corresponding to node P which is closer to the actual center line of the blood vessel is smaller. This setting can ensure that the finally obtained path node walks along the center of the blood vessel as much as possible, that is, ensure that the obtained target path is closer to the actual center line of the blood vessel, thereby ensuring the accuracy of the obtained blood vessel center line.

[0183] Furthermore, the second weighting coefficient w2 is also a dynamic coefficient related to the node P. Therefore, by setting the second weighting coefficient as a dynamic coefficient related to the node P, dynamic adjustment of the cost function can be further achieved, which is more conducive to efficiently finding the target path.

[0184] Specifically, the formula for calculating the second weighting coefficient w2 is as follows:

[0185]

[0186] Where σ is the second adjustment factor, and 0 < σ < 1, |Z P -Z D | is the Z-coordinate of the node P. P The Z coordinate of the termination node D D The absolute value of the difference between them.

[0187] Since the slice layers of the starting node and the ending node are furthest apart by default (i.e., the absolute value of the difference between the Z-coordinates of the starting and ending nodes is the largest), for example, the aorta runs from top to bottom along the head and neck of the human body. Therefore, by setting the second weighting coefficient W2 to be dynamically related to the slice layer (i.e., the Z-coordinate), where the larger the absolute value of the difference between the Z-coordinates of node P and the ending node D, the larger W2 becomes, it is more conducive to efficiently finding the optimal path. It should be noted that, as those skilled in the art will understand, if the acquired medical image contains nerves and blood vessels, the parameter W2 can be directly set to 1.

[0188] Preferably, the method further includes:

[0189] The target path is modified to obtain a modified target path;

[0190] The step of using the target path as the centerline of the blood vessel corresponding to the region of interest includes:

[0191] The corrected target path is used as the center line of the blood vessel corresponding to the region of interest.

[0192] Although the present invention dynamically adjusts the values ​​of the first weighting coefficient W1 and the second weighting coefficient W2 when determining the target path, there is still a possibility that some path points on the calculated target path may not be in the middle of the blood vessel, but instead travel along the blood vessel wall. Therefore, the present invention can ensure that all points on the final target path travel along the center of the blood vessel by correcting the target path, thereby ensuring the accuracy of the final obtained blood vessel centerline.

[0193] Further, the step of correcting the target path to obtain a corrected target path includes:

[0194] A first correction process is performed on each path point on the target path corresponding to the unbranched blood vessel region to obtain the corresponding first corrected path point;

[0195] A second correction process is performed on each path point on the target path corresponding to the bifurcation vessel region to obtain the corresponding second corrected path point;

[0196] Based on the first and second corrected path points, obtain the corrected target path.

[0197] Therefore, the present invention performs a first correction process on each path point corresponding to the unbranched vessel region on the target path, and a second correction process on each path point corresponding to the bifurcation vessel region on the target path, which can further ensure the accuracy of the finally obtained vessel centerline.

[0198] Furthermore, before performing the first correction process on each path point corresponding to the unbranched vessel region on the target path, the method further includes:

[0199] For each non-zero pixel in the blood vessel mask image, its surrounding neighboring pixels are traversed from near to far until the zero pixel closest to the non-zero pixel is found. The distance between the non-zero pixel and the zero pixel is calculated and set as the pixel value of the non-zero pixel to obtain a blood vessel distance transformation image.

[0200] Please continue to refer to this. Figure 14 The diagram illustrates a flowchart of the first correction process provided by an embodiment of the present invention. Figure 14 As shown, the first correction process for each path point on the target path corresponding to the unbranched blood vessel region to obtain the corresponding first corrected path point includes:

[0201] For each path point on the target path corresponding to the unbranched blood vessel region:

[0202] The path point is mapped onto the first cross-sectional image corresponding to the blood vessel distance transformation image onto the plane Z=0 to obtain the corresponding first mapped image;

[0203] The pixel with the largest pixel value in the first mapped image is taken as the corresponding first mapping point;

[0204] Based on the first mapping point, obtain the corresponding first correction point.

[0205] Taking one of the path points on the target path corresponding to the unbranched blood vessel region as an example, the first cross-sectional image corresponding to the pixel point on the blood vessel distance transformation image can be obtained based on the path point and the point set of its corresponding cross-section (refer to the relevant description below); then, the first cross-sectional image is mapped to the Z=0 plane (i.e., the plane with Z coordinate of 0, i.e., the XOY plane with the world coordinate system as the reference system) through a rotation and translation matrix to obtain the corresponding first mapped image; then, each pixel point in the first mapped image is traversed to find the pixel point with the largest pixel value (i.e., the point farthest from the edge of the blood vessel, i.e., the center point), and the pixel point with the largest pixel value is taken as the first mapped point corresponding to the path point; finally, the first mapped point is mapped to the first cross-sectional image through the inverse matrix of the rotation and translation matrix to obtain the first correction point corresponding to the pixel point.

[0206] Please continue to refer to this. Figure 15 The diagram illustrates a flow chart of the second correction process provided by an embodiment of the present invention. Figure 15 As shown, the second correction process for each path point on the target path corresponding to the bifurcation vessel region to obtain the corresponding second corrected path point includes:

[0207] For each path point on the target path corresponding to the bifurcation vessel region:

[0208] The path point is mapped onto the second cross-sectional image corresponding to the blood vessel distance transformation image onto the plane Z=0 to obtain the corresponding second mapped image;

[0209] Based on the pixel values ​​of each pixel in the second mapped image, two peak points are obtained;

[0210] The peak point closest to the path point is taken as the corresponding second mapping point;

[0211] Based on the second mapping point, obtain the corresponding second correction point.

[0212] Specifically, taking a path point on the target path corresponding to a bifurcation vessel region as an example, the second cross-sectional image corresponding to the path point on the vessel distance transformation image can be obtained based on the point set of the path point and its corresponding cross-section (refer to the relevant description below); then, the second cross-sectional image is mapped onto the Z=0 plane (i.e., the plane with Z coordinate 0, i.e., the XOY plane with the world coordinate system as the reference system) through a rotation and translation matrix to obtain the corresponding second mapped image; then, each pixel in the second mapped image is traversed to find two pixel peak points (these two peak points correspond to the centers of the two branch vessels, respectively). The two pixel peaks may be the two points with the largest pixel values ​​in the second mapped image (i.e., the two peaks have the same pixel value and the largest pixel value), or they may be the largest pixel value point and the second largest pixel value point in the second mapped image (i.e., one peak point is the largest pixel value point and the other is the second largest pixel value point). The distances between these two peaks and the path point are then calculated, and the peak point closest to the path point is taken as the second mapped point of the path point. Finally, the second mapped point is mapped onto the second cross-sectional image using the inverse of the rotation and translation matrix to obtain the second correction point corresponding to the path point. Please refer to [reference needed]. Figure 16 The diagram illustrates the acquisition of the second mapping point according to a specific example of the present invention. Figure 16 As shown, two peak points were found in the second mapping image corresponding to path point 4: peak point 51 and peak point 52. Peak point 51 is closer to path point 4, so peak point 51 is used as the second correction point corresponding to path point 4.

[0213] Further, please refer to Figure 17 The diagram illustrates a process for obtaining a cross-section according to an embodiment of the present invention. Figure 17 As shown, step S300, determining the cross-section corresponding to each center point on the blood vessel centerline based on the blood vessel mask image, includes:

[0214] Calculate the position coordinates of each non-zero pixel in the blood vessel mask image;

[0215] For each center point on the central line of the aforementioned blood vessel:

[0216] The center point and its adjacent neighboring center points are combined to form a first vector, and the center point and each of the non-zero pixel points are combined to form a second vector.

[0217] Calculate the angle between the first vector and the second vector;

[0218] The set of points consisting of non-zero pixels whose included angle is within a preset range is taken as the set of points of the cross section corresponding to the center point;

[0219] The center point and the set of points corresponding to its cross-section are fitted together to obtain the cross-section corresponding to the center point.

[0220] Specifically, the position coordinates of all non-zero pixels (pixels with a pixel value of 1) can be stored in a valid set. Then, the first center point on the blood vessel centerline (i.e., the starting pixel on the blood vessel centerline) is taken as the current point, and the current point and the next center point (i.e., the second pixel on the blood vessel centerline) are combined to form a first vector. And to form a second vector by combining the current point (i.e., the starting pixel) with the first non-zero pixel A1 in the valid set. By calculating the first vector With the second vector The included angle θ 11 And determine the included angle θ 11 Whether it is within a preset range (e.g., 90°±1°), if the judgment result is the included angle θ 11 If the pixel is within a preset range, it indicates that the non-zero pixel is a point on the cross-section corresponding to the current point. Therefore, point A1 is saved to the set of points used to store the cross-section of the current point. Then, the current point and the next non-zero pixel A2 in the valid set are combined to form a second vector. And determine the first vector With the second vector The included angle θ 12 If the point A2 is within a preset range, and the result is yes, then the point A2 is saved to a set of points used to store the cross-section of the current point. This process is repeated for each non-zero pixel in the valid set until all non-zero pixels in the valid set have been traversed to obtain the point set of the cross-section corresponding to the first center point. After obtaining the point set of the cross-section corresponding to the first center point, the second center point is used as the current point, and the above process is repeated to obtain the point set of the cross-section corresponding to the second center point. This continues until the current point is the last center point. For the last center point, a first vector can be formed by the last center point and its adjacent previous center point to obtain the point set of the cross-section corresponding to the last center point.

[0221] It should be noted that, as those skilled in the art will understand, the coordinates of the current point are assumed to be (X... j ,Y j Z j The coordinates of the adjacent center point are (X... k,Y k Z k The coordinates of the non-zero pixel point Ai are (X... Ai ,Y Ai Z Ai If ), then the first vector Second vector Then the first vector With the second vector The included angle θ ji for:

[0222]

[0223] Furthermore, it should be noted that in some other embodiments, when obtaining the first vector, if the current point is neither the first center point nor the last center point on the blood vessel centerline, the current point can be combined with the previous or next center point on the blood vessel centerline to form the first vector. This invention does not impose any limitations on this.

[0224] Since the obtained cross-sectional point set data is discrete, it is impossible to directly calculate the parameters of the blood vessel. Therefore, by fitting each center point on the blood vessel's centerline to the point set of its corresponding cross-section, the cross-section corresponding to each center point on the blood vessel's centerline can be obtained. Specifically, by fitting the first center point on the blood vessel's centerline to the point set of its corresponding cross-section, for example using least squares fitting, the cross-section corresponding to the first center point can be obtained; by fitting the second center point on the blood vessel's centerline to the point set of its corresponding cross-section, for example using least squares fitting, the cross-section corresponding to the second center point can be obtained; and so on, the cross-section corresponding to each center point on the blood vessel's centerline can be obtained.

[0225] Preferably, the method for determining vascular stent parameters provided by the present invention further includes:

[0226] The feature information of the cross section corresponding to each center point on the center line of the blood vessel corresponding to the bifurcation vessel region is corrected.

[0227] Specifically, the second mapping image corresponding to the center point is segmented using the watershed algorithm (refer to the relevant description above) by using the second mapping point corresponding to the center point as the seed point; and the feature information of the corresponding cross section is corrected according to the feature information of the connected domain where the second mapping point is located.

[0228] Specifically, in the second mapped image, the second mapped point can be used as a seed point. Then, based on the seed point, surrounding pixels are traversed. When a pixel with a value of 1 is encountered or no pixel is found, the process stops, thus separating the two branch vessel regions. The connected component where the second mapped point is located is the branch vessel region of interest. For more information on the watershed algorithm, please refer to existing technologies; it will not be elaborated upon here. Please refer to [reference needed]. Figure 18 The diagram illustrates a connected component obtained using the watershed algorithm in a specific example of the present invention. Figure 14 As shown, by employing the watershed algorithm, peak point 51 (reference) can be identified. Figure 16 The region containing the second mapping point (i.e., the second mapping point) and the peak point 52 is completely separated. Therefore, based on the attribute information corresponding to the connected component where the second mapping point is located, the characteristic information of the corresponding cross-section can be corrected. Specifically, based on the position coordinates of each pixel in the connected component where the second mapping point is located, the perimeter, area, contour coordinates, maximum inscribed diameter, minimum inscribed diameter, coordinates of the contour point corresponding to the maximum diameter, and coordinates of the contour point corresponding to the minimum diameter of the connected component can be obtained. The perimeter, area, maximum inscribed diameter, and minimum inscribed diameter of this connected component are the perimeter, area, maximum inscribed diameter, and minimum inscribed diameter of the corresponding cross-section. By using the inverse of the rotation and translation matrix between the second cross-sectional image and the second mapping image, the contour coordinates of the corresponding cross-section, the coordinates of the contour point corresponding to the maximum inscribed diameter, and the coordinates of the contour point corresponding to the minimum inscribed diameter can be obtained.

[0229] Based on the same inventive concept, the present invention also provides an electronic device, please refer to [reference needed]. Figure 19 A block diagram illustrating an embodiment of the electronic device provided by the present invention is shown. Figure 19 As shown, the electronic device includes a processor 101 and a memory 103. The memory 103 stores a computer program. When the computer program is executed by the processor 101, it implements the method for determining vascular stent parameters described above. Since the electronic device provided by this invention and the method for determining vascular stent parameters described above belong to the same inventive concept, the electronic device provided by this invention has all the advantages of the method for determining vascular stent parameters described above, and therefore will not be described again.

[0230] like Figure 19As shown, the electronic device also includes a communication interface 102 and a communication bus 104, wherein the processor 101, the communication interface 102, and the memory 103 communicate with each other via the communication bus 104. The communication bus 104 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus 104 can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is used in the figure, but this does not indicate that there is only one bus or one type of bus. The communication interface 102 is used for communication between the aforementioned electronic device and other devices.

[0231] The processor 101 referred to in this invention can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 101 is the control center of the electronic device, connecting various parts of the electronic device through various interfaces and lines.

[0232] The memory 103 can be used to store the computer program. The processor 101 implements various functions of the electronic device by running or executing the computer program stored in the memory 103 and calling the data stored in the memory 103.

[0233] The memory 103 may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0234] The present invention also provides a readable storage medium storing a computer program, which, when executed by a processor, can implement the method for determining vascular stent parameters described above. Since the readable storage medium provided by the present invention and the method for determining vascular stent parameters described above belong to the same inventive concept, the readable storage medium provided by the present invention has all the advantages of the method for determining vascular stent parameters described above, and therefore will not be elaborated further.

[0235] The readable storage medium of embodiments of the present invention can be any combination of one or more computer-readable media. The readable medium can be a computer-readable signal medium or a computer-readable storage medium. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections having one or more wires, portable computer hard disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device.

[0236] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0237] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0238] In summary, compared with the prior art, the method, electronic device, and storage medium for determining vascular stent parameters provided by the present invention have the following advantages: The present invention first segments a pre-acquired medical image to obtain a vascular mask image; then, based on the vascular mask image, it obtains the vascular centerline corresponding to the region of interest; then, based on the vascular mask image, it determines the cross-section corresponding to each center point on the vascular centerline; and finally, based on the cross-section corresponding to each center point on the vascular centerline, it determines the diameter of the vascular stent corresponding to the region of interest. Therefore, the present invention, by obtaining the vascular centerline corresponding to the region of interest and the cross-section corresponding to each center point on the vascular centerline, and determining the diameter of the vascular stent corresponding to the region of interest based on the cross-section corresponding to each center point on the vascular centerline, can accurately determine the diameter of the vascular stent corresponding to the region of interest, laying a good foundation for accurately determining the stent model and effectively improving diagnostic efficiency and accuracy. Furthermore, the present invention reconstructs the internal structure of the region of interest based on the blood vessel centerline and the cross-section corresponding to each center point on the blood vessel centerline to obtain the reconstructed blood vessel wall structure. Based on the blood vessel centerline and the reconstructed blood vessel wall structure, the length of the vascular stent corresponding to the region of interest is determined, which further provides a basis for accurately determining the type of vascular stent and is more helpful in accurately determining the type of vascular stent.

[0239] It should be noted that the apparatus and methods disclosed in the embodiments herein can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments herein. In this regard, each block in a flowchart or block diagram may represent a module, program, or part of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system to perform the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0240] In addition, the functional modules in the various embodiments of this article can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0241] The above description is merely a description of preferred embodiments of the present invention and is not intended to limit the scope of the invention in any way. Any changes or modifications made by those skilled in the art based on the above disclosure are within the protection scope of the present invention. Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the present invention and its equivalents, the present invention also intends to include these modifications and variations.

Claims

1. A method for determining vascular stent parameters, characterized in that, include: The pre-acquired medical images are segmented to obtain vascular mask images; Based on the vascular mask image, obtain the center line of the vascular region of interest; Based on the vascular mask image, determine the cross-section corresponding to each center point on the vascular centerline; The diameter of the vascular stent corresponding to the region of interest is determined based on the cross-section corresponding to each center point on the vascular centerline. The method further includes: Based on the cross-section corresponding to each center point on the center line of the blood vessel, obtain the maximum tangential diameter of the blood vessel corresponding to each center point; Based on each center point on the center line of the blood vessel and its corresponding maximum internal diameter of the blood vessel, a corresponding closed contour curve is generated. The closed contour curves are surface-fitted using a surface fitting method to obtain the reconstructed vascular wall structure of the region of interest. Calculate the path length of the blood vessel centerline based on the coordinates of all center points on the centerline. Based on the reconstructed vascular wall structure, the outer curvature and inner curvature of the vascular wall corresponding to the region of interest are obtained; Based on the coordinates of all pixels on the outer curve, calculate the length of the outer curve path of the vessel wall corresponding to the region of interest. Based on the coordinates of all pixels on the inner curve, calculate the inner curve path length of the vessel wall corresponding to the region of interest. The length of the vascular stent corresponding to the region of interest is determined based on the path length of the vessel centerline, the path length of the outer curve side of the vessel wall, and the path length of the inner curve side.

2. The method for determining vascular stent parameters according to claim 1, characterized in that, The step of calculating the path length of the blood vessel centerline based on the coordinates of each center point on the blood vessel centerline includes: Calculate the Euclidean distance between all adjacent two center points based on the coordinates of all center points on the central line of the blood vessel. Add the Euclidean distances between all adjacent pairs of said center points to obtain the path length of said vessel centerline.

3. The method for determining vascular stent parameters according to claim 1, characterized in that, The step of obtaining the outer curvature and inner curvature of the vessel wall corresponding to the region of interest based on the reconstructed vessel wall structure includes: For each center point on the central line of the aforementioned blood vessel: Obtain the two intersection points on the reconstructed blood vessel wall structure that intersect the normal to the center point; Form a vector from the two intersection points and the center point, and calculate the angle between each vector and the normal vector of the center point. The intersection points of vectors with an angle less than 90° are taken as the path points on the outer curved side of the blood vessel wall corresponding to the center point, and the intersection points of vectors with an angle greater than 90° are taken as the path points on the inner curved side of the blood vessel wall corresponding to the center point. Based on the outward curve path points of the vessel wall corresponding to all center points, obtain the outward curve of the vessel wall corresponding to the region of interest. Based on the inward curve path points of the vessel wall corresponding to all center points, obtain the inward curve of the vessel wall corresponding to the region of interest.

4. The method for determining vascular stent parameters according to claim 1, characterized in that, The step of determining the length of the vascular stent corresponding to the region of interest based on the vascular centerline and the reconstructed vascular wall structure further includes: Calculate the Euclidean length of the blood vessel centerline based on the coordinates of the starting center point and the ending center point of the centerline. The curvature of the region of interest is calculated based on the path length and Euclidean length of the vessel centerline. The step of determining the length of the vascular stent corresponding to the region of interest based on the path length of the vessel centerline, the path length of the outer curvature side of the vessel wall, and the path length of the inner curvature side includes: The length of the vascular stent corresponding to the region of interest is determined based on the curvature of the region of interest, the path length of the vessel centerline, the path length of the outer curved side of the vessel wall, and the path length of the inner curved side.

5. The method for determining vascular stent parameters according to claim 1, characterized in that, The method further includes: The model of the vascular stent is determined based on its diameter and length.

6. The method for determining vascular stent parameters according to claim 1, characterized in that, The step of determining the diameter of the vascular stent corresponding to the region of interest based on the cross-section corresponding to each center point on the vascular centerline includes: Based on the cross-section corresponding to each center point on the center line of the blood vessel, obtain the maximum tangential diameter of the blood vessel corresponding to each center point; The maximum internal diameter of the vessel corresponding to the region of interest is determined based on the maximum internal diameter of the vessel corresponding to all the center points. The diameter of the vascular stent corresponding to the region of interest is determined based on the maximum inner diameter of the blood vessel.

7. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program, which, when executed by the processor, implements the method of any one of claims 1 to 6.

8. A readable storage medium, characterized in that, The readable storage medium stores a computer program, which, when executed by a processor, implements the method of any one of claims 1 to 6.

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