A method, apparatus, electronic device and storage medium for automated microcatheter shaping

Abstract

This disclosure presents an automated microcatheter shaping method, apparatus, electronic device, and storage medium. The automated microcatheter shaping method includes: acquiring cranial imaging data containing an aneurysm and performing three-dimensional reconstruction processing on the cranial imaging data to obtain a vascular model; segmenting the vascular model to obtain aneurysm segmentation results; obtaining the centerline of the carrier artery based on the vascular model and the aneurysm segmentation results (the centerline of the artery containing the aneurysm); measuring the aneurysm based on the carrier artery centerline, the aneurysm segmentation results, and the vascular model to obtain aneurysm measurement results; using the aneurysm measurement results to characterize the morphological information of the aneurysm; and obtaining a target microcatheter shaping scheme based on the aneurysm segmentation results, the aneurysm measurement results, and the carrier artery centerline. By implementing this disclosure, automated and precise microcatheter shaping is achieved, improving the efficiency of microcatheter shaping and increasing the success rate of interventional surgeries.

Description

Technical Field

[0001] This disclosure generally relates to the field of image processing technology. More specifically, this disclosure relates to a method, apparatus, electronic device, and storage medium for automated shaping of microcatheters. Background Technology

[0002] In the field of neurointervention, microcatheters are key instruments for treating cerebrovascular diseases such as aneurysms, arteriovenous malformations, vascular stenosis, and acute stroke. For example, in interventional embolization of intracranial aneurysms, the appropriate microcatheter is first selectively delivered into the aneurysm. Because vascular and aneurysm morphologies vary among patients, customized design and shaping of the microcatheter (including the shape of the shaping needle at the tip and the path the microcatheter takes to the aneurysm) are necessary to ensure treatment effectiveness and accurate, safe delivery to the aneurysm location.

[0003] Currently, before performing interventional surgery, doctors will imagine the three-dimensional vascular morphology based on two-dimensional medical images, and then manually roughly shape the microcatheter outside the body. The shaping result depends on the doctor's clinical experience and skills. If the clinician is not experienced enough or encounters complex vascular and hemangioma morphologies, multiple shapings are often required, which not only prolongs the operation time and increases the patient's pain, but also affects the final surgical treatment effect.

[0004] In view of this, there is an urgent need to provide a method, device, electronic device and storage medium for automatic microcatheter shaping, so as to realize automatic and precise shaping of microcatheters, improve the efficiency of microcatheter shaping and increase the success rate of interventional surgery. Summary of the Invention

[0005] In order to at least address one or more of the technical problems mentioned above, this disclosure provides a method, apparatus, electronic device, and storage medium for automated shaping of microcatheters in several aspects.

[0006] In a first aspect, this disclosure provides an automated microcatheter shaping method, the method comprising: acquiring cranial imaging data containing an aneurysm, and performing three-dimensional reconstruction processing on the cranial imaging data to obtain a vascular model; segmenting the vascular model into an aneurysm to obtain an aneurysm segmentation result; obtaining the centerline of the aneurysm-bearing artery based on the vascular model and the aneurysm segmentation result, wherein the centerline of the aneurysm-bearing artery refers to the centerline of the artery where the aneurysm is located; measuring the aneurysm based on the centerline of the aneurysm-bearing artery, the aneurysm segmentation result, and the vascular model to obtain the aneurysm measurement result; the aneurysm measurement result being used to characterize the morphological information of the aneurysm; and obtaining a target microcatheter shaping scheme based on the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery.

[0007] In some embodiments, the cranial imaging data is any one of CT angiography data, magnetic resonance angiography data, and digital subtraction angiography data.

[0008] In some embodiments, obtaining the centerline of the aneurysm-bearing artery based on the vascular model and the aneurysm segmentation result includes: extracting the centerline of each artery in the vascular model based on the vascular model; and determining the centerline of the aneurysm-bearing artery based on the aneurysm location information in the aneurysm segmentation result and the centerline of each artery.

[0009] In some embodiments, the aneurysm measurement results include at least one of the following: aneurysm neck, aneurysm diameter, aneurysm height, aneurysm width, aneurysm entry angle, and aneurysm volume.

[0010] In some embodiments, obtaining the target microcatheter shaping scheme based on the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the carrier artery includes: matching the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the carrier artery from a pre-set database to obtain a matching result; the database stores multiple data entries, each data entry including at least: a vascular model, aneurysm measurement result, centerline of the carrier artery, microcatheter shaping scheme, and surgical result; if the matching result indicates that data is matched from the database, then the reference microcatheter shaping scheme in the matched data is used as the target microcatheter shaping scheme; if the matching result indicates that no data is matched from the database, then the target microcatheter shaping scheme is generated based on the aneurysm segmentation result, the aneurysm measurement result, the centerline of the carrier artery, and a specified microcatheter shaping algorithm.

[0011] In some embodiments, the step of matching the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery from a pre-set database to obtain a matching result includes: for each piece of data in the database, calculating the matching degree between the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery and the data according to the weights configured for the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery;

[0012] If the maximum value of the matching degree between the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery and the data in the database is greater than or equal to a specified threshold, then the matching result indicates that data has been matched from the database; if the maximum value of the matching degree between the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery and the data in the database is less than a specified threshold, then the matching result indicates that data has not been matched from the database.

[0013] In some embodiments, after obtaining the target microcatheter shaping scheme, the method further includes: displaying the target microcatheter shaping scheme.

[0014] In a second aspect, this disclosure provides an automated microcatheter shaping device, the device comprising: a three-dimensional reconstruction module for acquiring cranial image data containing an aneurysm and performing three-dimensional reconstruction processing on the cranial image data to obtain a vascular model; a segmentation module for segmenting the vascular model into an aneurysm to obtain an aneurysm segmentation result; a centerline extraction module for obtaining the centerline of the aneurysm-bearing artery based on the vascular model and the aneurysm segmentation result, wherein the centerline of the aneurysm-bearing artery refers to the centerline of the artery where the aneurysm is located; a measurement module for measuring the aneurysm based on the centerline of the aneurysm-bearing artery, the aneurysm segmentation result, and the vascular model to obtain the aneurysm measurement result; the aneurysm measurement result is used to characterize the morphological information of the aneurysm; and a target microcatheter shaping scheme acquisition module for obtaining a target microcatheter shaping scheme based on the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery.

[0015] In a third aspect, this disclosure provides an electronic device comprising: a processor configured to execute program instructions; and a memory configured to store the program instructions, which, when loaded and executed by the processor, cause the processor to perform the microcatheter auto-shaping method according to the first aspect or any alternative embodiment of the first aspect.

[0016] In a fourth aspect, this disclosure provides a computer-readable storage medium storing program instructions that, when loaded and executed by a processor, cause the processor to perform the microcatheter auto-shaping method according to the first aspect or any alternative embodiment of the first aspect.

[0017] By utilizing the microcatheter automatic shaping method, apparatus, electronic device, and storage medium provided above, this embodiment of the present disclosure performs three-dimensional reconstruction processing on the acquired cranial image data containing aneurysms to obtain a vascular model. Based on the vascular model, aneurysm segmentation results are obtained, and then the centerline of the aneurysm-bearing artery is extracted. The aneurysm is then measured based on the centerline of the aneurysm-bearing artery, the aneurysm segmentation results, and the vascular model to obtain aneurysm measurement results. Based on the aneurysm segmentation results, aneurysm measurement results, and the centerline of the aneurysm-bearing artery, a microcatheter shaping scheme is automatically obtained, achieving automatic and precise microcatheter shaping, improving the efficiency of microcatheter shaping, and increasing the success rate of interventional surgery. Attached Figure Description

[0018] The above and other objects, features, and advantages of exemplary embodiments of this disclosure will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of this disclosure are illustrated by way of example and not limitation, and like or corresponding reference numerals denote like or corresponding parts, wherein:

[0019] Figure 1 An exemplary flowchart of an automated microcatheter shaping method according to some embodiments of this disclosure is shown;

[0020] Figure 2 An overall flowchart illustrating the automated shaping of microcatheters according to some embodiments of this disclosure is shown;

[0021] Figure 3 An exemplary structural block diagram of a microcatheter automatic shaping device according to some embodiments of this disclosure is shown;

[0022] Figure 4 An exemplary structural block diagram of an electronic device according to some embodiments of this disclosure is shown. Detailed Implementation

[0023] The technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, not all of them. Based on the embodiments in this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0024] It should be understood that the terms “comprising” and “including” used in this disclosure and claims indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0025] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure. As used in this disclosure and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this disclosure and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0026] As used in this specification and claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0027] The specific embodiments disclosed herein will now be described in detail with reference to the accompanying drawings.

[0028] Exemplary application scenarios

[0029] Aneurysm embolization is the primary treatment for intracranial aneurysms, requiring the selective delivery of a microcatheter to the aneurysm site. Because vascular and aneurysm morphologies vary among patients, customized design and shaping of the microcatheter tip and the pathway for delivery to the aneurysm are necessary to ensure accurate and safe delivery of the microcatheter to the designated location and to guarantee optimal treatment outcomes.

[0030] The shape of the end of the microcatheter that first enters the blood vessel (the end where the shaping needle is located) is particularly important. The shape of this end directly determines whether the microcatheter can reach the designated location (i.e., the aneurysm), thus affecting the success or failure of the surgery. Previously, before performing aneurysm embolization, doctors would visualize the three-dimensional vascular morphology based on two-dimensional medical images, and then manually reshape the microcatheter's shaping needle externally. The shaping plan relied entirely on the doctor's clinical experience. If the clinician lacked experience or encountered complex vascular and aneurysm morphologies, multiple shaping attempts were often necessary, not only prolonging the surgery time and increasing patient suffering but also affecting the final treatment outcome.

[0031] In view of this, the present disclosure provides an automated microcatheter shaping scheme to achieve automated and precise microcatheter shaping, improve the efficiency of microcatheter shaping, and increase the success rate of interventional surgery.

[0032] Figure 1 An exemplary flowchart of an automated microcatheter shaping method 100 according to some embodiments of this disclosure is shown. It will be understood that the automated microcatheter shaping method 100 can be performed by any suitable device with data processing capabilities, such as, but not limited to, terminal devices, processors, and servers.

[0033] like Figure 1As shown, the automatic microcatheter shaping method 100 includes: Step S110: acquiring cranial image data containing an aneurysm and performing three-dimensional reconstruction processing on the cranial image data to obtain a vascular model; Step S120: segmenting the vascular model into an aneurysm to obtain an aneurysm segmentation result; Step S130: obtaining the centerline of the aneurysm-bearing artery based on the vascular model and the aneurysm segmentation result; Step S140: measuring the aneurysm based on the centerline of the aneurysm-bearing artery, the aneurysm segmentation result, and the vascular model to obtain an aneurysm measurement result; Step S150: obtaining a target microcatheter shaping scheme based on the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery.

[0034] For example, in this disclosed embodiment, the aneurysm in step S110 refers to a localized dilation or bulging of the arterial wall caused by lesion or injury, manifesting as a permanent abnormal dilation of the blood vessel wall. Cranial imaging data refers to image data of the internal structures of the brain obtained through medical imaging technology, which can be any one of CT angiography (CTA), magnetic resonance angiography (MRA), or digital subtraction angiography (DSA).

[0035] In this disclosed embodiment, the above-mentioned brain imaging data containing aneurysms is acquired by specialized medical imaging equipment, such as computed tomography (CT) equipment, magnetic resonance imaging (MRI) equipment, ultrasound imaging equipment, positron emission tomography (PET) equipment, etc.

[0036] In practice, a professional imaging device (CT, MRI or DSA) is used to scan the patient's brain to acquire brain image data including the aneurysm. The acquired brain image data is then transmitted to the computer system of the device that performs the microcatheter automatic shaping method 100 for subsequent processing.

[0037] In this disclosed embodiment, 3D reconstruction is a technology that transforms 2D medical image data into a 3D visualization model through computer processing and analysis. Based on this, a vascular model refers to a 3D model generated using 3D reconstruction technology that can intuitively display the spatial structure of blood vessels. In this disclosed embodiment, a specific 3D reconstruction method may involve inputting cranial image data into 3D reconstruction software, such as Mimics or 3D Slicer, to process the cranial image data and generate a vascular model.

[0038] In this disclosed embodiment, the three-dimensional reconstruction process can be as follows: camera calibration is performed based on cranial image data to establish the relationship between the image coordinate system and the world coordinate system. Then, feature information of key points is extracted from the cranial image data, and algorithms such as triangulation or surface reconstruction are used to restore the three-dimensional structure of cranial blood vessels. Finally, the texture information of the cranial image data is mapped onto the three-dimensional structure to obtain the aforementioned blood vessel model.

[0039] For example, in this disclosed embodiment, the aneurysm segmentation result in step S120 refers to the aneurysm marker on the vascular model, which can be represented, for example, by a detection box. There are many methods for segmenting aneurysms on a vascular model to obtain the aneurysm segmentation result, such as manual segmentation and automatic segmentation. Automatic segmentation methods can include segmentation using neural networks or segmentation using traditional image segmentation algorithms (e.g., conventional thresholding, region growing algorithms, etc.). Specifically, neural network segmentation can involve inputting the vascular model into a pre-trained aneurysm segmentation model, which then outputs the aneurysm segmentation result. Manual segmentation methods can involve receiving aneurysms manually selected by a physician on the vascular model and extracting the aneurysms.

[0040] For example, in this disclosed embodiment, the centerline of the carrier artery in step S130 refers to the centerline of the artery where the aneurysm is located. Here, the centerline refers to the central path of the artery, which is formed by connecting the geometric center points of the arteries. The aforementioned centerline of the carrier artery can be characterized using parametric equations in a world coordinate system. Ideally, to ensure that the microcatheter can move smoothly within the carrier vessel and avoid colliding with or penetrating the vessel wall, the vessel centerline is the ideal movement path for the microcatheter. Therefore, the microcatheter shaping scheme can be determined based on the vessel centerline.

[0041] As for how to obtain the centerline of the tumor-bearing artery based on the vascular model and aneurysm segmentation results, the following examples illustrate this, and will not be elaborated here.

[0042] For example, in this disclosed embodiment, the aneurysm measurement results in step S140 are used to characterize the morphological information of the aneurysm. Here, the aneurysm measurement results may include at least one of the following: aneurysm neck, aneurysm diameter, aneurysm height, aneurysm width, aneurysm entry angle, aneurysm volume, etc.

[0043] The aneurysm neck refers to the width of the connection between the aneurysm and the parent artery, which significantly affects the insertion of the microcatheter into the aneurysm and the placement of embolic material. The aneurysm diameter is the widest point of the aneurysm and is an important indicator of its size. The aneurysm height is the vertical distance from the aneurysm neck to the top of the aneurysm, reflecting its size in the longitudinal direction. The aneurysm width is the maximum width perpendicular to the aneurysm height, describing its size in the transverse direction. The aneurysm angle of incidence is the angle between the aneurysm and the parent artery, affecting the difficulty and method of microcatheter insertion. The aneurysm volume refers to the space occupied by the aneurysm. These dimensions, calculated from the aneurysm's three-dimensional morphology, are valuable for assessing the severity of the aneurysm and determining the required amount of embolic material.

[0044] In this disclosed embodiment, the aforementioned aneurysm measurement results can be calculated using conventional measurement tools and algorithms. For example, for measuring the aneurysm neck, the measurement tool determines the boundary of the neck based on the aneurysm segmentation results and the vascular model, and then calculates the distance between two points on the boundary using an algorithm. As another example, for measuring the aneurysm volume, the measurement tool calculates its volume using mathematical methods such as integration based on the aneurysm's three-dimensional morphological data. Furthermore, for calculating the aneurysm incidence angle, the measurement tool can calculate the angle between the line connecting the point on the centerline of the aneurysm-carrying artery corresponding to the upstream positioning point on the centerline of the aneurysm-carrying artery and the centerline of the aneurysm neck, and the centerline of the aneurysm-carrying artery.

[0045] For example, the target microcatheter shaping scheme in step S150 above may include: the shaping path of the microcatheter and / or the shape of the shaping needle at the tip of the microcatheter. Here, the shape of the shaping needle may include, but is not limited to, the bending shape, bending angle and length of the shaping needle.

[0046] In this disclosed embodiment, there are many methods for obtaining the target microcatheter shaping scheme based on aneurysm segmentation results, aneurysm measurement results, and the centerline of the carrier artery. For example, based on the aneurysm segmentation results, aneurysm measurement results, and the centerline of the carrier artery, a matching process can be performed from a pre-set database, and the microcatheter shaping scheme in the database that matches the aneurysm segmentation results, aneurysm measurement results, and the centerline of the carrier artery can be used as the target microcatheter shaping scheme. Another example is that the target microcatheter shaping scheme can be generated based on a specified microcatheter shaping algorithm, the aneurysm segmentation results, the aneurysm measurement results, and the centerline of the carrier artery. Yet another example is that the target microcatheter shaping scheme can be generated based on the aneurysm segmentation results, aneurysm measurement results, and the centerline of the carrier artery, first by matching the aneurysm segmentation results, aneurysm measurement results, and the centerline of the carrier artery from a pre-set database, and if no matching microcatheter shaping scheme is found in the database, then the target microcatheter shaping scheme can be generated based on the specified microcatheter shaping algorithm, the aneurysm segmentation results, the aneurysm measurement results, and the centerline of the carrier artery. This disclosed embodiment does not specifically limit these methods.

[0047] The following examples illustrate the specific implementation of the target microcatheter shaping scheme based on aneurysm segmentation results, aneurysm measurement results, and the centerline of the tumor-bearing artery. These details will not be elaborated upon here.

[0048] In this disclosed embodiment, after obtaining the target microcatheter shaping plan, the target microcatheter shaping plan can be displayed so that doctors can intuitively see the target microcatheter shaping plan, understand the specific shape and parameter requirements of the microcatheter, thereby providing clear guidance for shaping the microcatheter in subsequent actual surgery. This improves the efficiency and accuracy of surgical preparation when performing aneurysm embolization to treat intracranial aneurysms based on the target microcatheter shaping plan, and reduces operational errors caused by unclear understanding of the plan.

[0049] This disclosed embodiment performs three-dimensional reconstruction processing on the acquired cranial image data containing aneurysms to obtain a vascular model. Then, based on the vascular model, the aneurysm segmentation result is obtained. Next, the centerline of the aneurysm-bearing artery is extracted. Then, based on the centerline of the aneurysm-bearing artery, the aneurysm segmentation result, and the vascular model, the aneurysm is measured to obtain the aneurysm measurement result. Based on the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery, a microcatheter shaping scheme is automatically obtained, realizing automatic and precise microcatheter shaping, improving the efficiency of microcatheter shaping, and increasing the success rate of interventional surgery.

[0050] As an optional embodiment of this disclosure, the step S130 above, which obtains the centerline of the tumor-bearing artery based on the vascular model and aneurysm segmentation results, includes: extracting the centerline of each artery in the vascular model based on the vascular model; and determining the centerline of the tumor-bearing artery based on the aneurysm location information in the aneurysm segmentation results and the centerline of each artery.

[0051] For example, in this disclosed embodiment, a conventional centerline extraction algorithm (e.g., skeletonization algorithm) can be used to process the vascular model to extract the arterial centerline of each artery in the vascular model.

[0052] In this disclosed embodiment, the location information of the aneurysm can be the coordinates of the center point of the aneurysm in the world coordinate system. In the above embodiment, after obtaining the aneurysm segmentation result, the location information of the aneurysm can be obtained. Then, based on the distance from the location information of the aneurysm to the center line of each artery, the center line of the carrier artery is determined. For example, the center line of the artery corresponding to the smallest distance is taken as the center line of the carrier artery.

[0053] As an optional embodiment of this disclosure, the step S150 above, which obtains the target microcatheter shaping scheme based on the aneurysm segmentation result, aneurysm measurement result, and centerline of the carrier artery, includes: matching the aneurysm segmentation result, aneurysm measurement result, and centerline of the carrier artery from a pre-set database to obtain a matching result; if the matching result indicates that data is matched from the database, then the reference microcatheter shaping scheme in the matched data is used as the target microcatheter shaping scheme; if the matching result indicates that no data is matched from the database, then the target microcatheter shaping scheme is generated based on the aneurysm segmentation result, aneurysm measurement result, centerline of the carrier artery, and a specified microcatheter shaping algorithm.

[0054] For example, in this disclosed embodiment, the aforementioned database is pre-set and can be constructed based on a large amount of clinical case data to provide a reference for the formulation of microcatheter shaping plans for new cases. In this disclosed embodiment, the aforementioned database stores multiple data entries, each of which includes at least: vascular model, aneurysm measurement results, centerline of the aneurysm-bearing artery, microcatheter shaping plan, and surgical results.

[0055] In this disclosed embodiment, when matching the aneurysm segmentation results, aneurysm measurement results, and the centerline of the aneurysm-bearing artery with data in the database, for each piece of data in the database, the matching degree between the aneurysm segmentation results, aneurysm measurement results, and the centerline of the aneurysm-bearing artery and the data is calculated according to the weights configured for the aneurysm segmentation results, aneurysm measurement results, and the centerline of the aneurysm-bearing artery and the data in the database is greater than or equal to a specified threshold, then the matching result indicates that data has been matched from the database; if the maximum value of the matching degree between the aneurysm segmentation results, aneurysm measurement results, and the centerline of the aneurysm-bearing artery and the data in the database is less than the specified threshold, then the matching result indicates that no data has been matched from the database. Here, weights can be set in advance for the aneurysm segmentation results, aneurysm measurement results, and the centerline of the aneurysm-bearing artery, and then the matching degree with the data in the database can be calculated by weighted average. The matching degree can be represented by Euclidean distance, etc., and this disclosed embodiment does not limit the matching degree.

[0056] The specified threshold mentioned above is any reasonable value that is set in advance, such as 98%. This disclosed embodiment does not specifically limit it. It is used to determine whether the matching degree is high enough. When the maximum value of the matching degree between the current case (i.e., the above-mentioned aneurysm segmentation result, aneurysm measurement result, and centerline of the aneurysm-bearing artery) and the data in the database is greater than or equal to the specified threshold, it is considered that suitable data has been matched from the database.

[0057] If the maximum matching degree between the current medical record and the data in the database is less than the specified threshold, it is considered that no suitable data has been found in the database. Based on this, a specified microcatheter shaping algorithm can be used to generate a target microcatheter shaping scheme based on the aneurysm segmentation results, aneurysm measurement results, and the centerline of the aneurysm-bearing artery of the current case.

[0058] The embodiments disclosed herein utilize the above-described method to both leverage existing clinical experience data and generate reasonable solutions through algorithms in the absence of matching data, thereby improving the accuracy and adaptability of microcatheter shaping solutions.

[0059] Figure 2 An overall flowchart of the automated shaping of microcatheters according to some embodiments of this disclosure is shown.

[0060] like Figure 2As shown, the automated microcatheter shaping scheme includes several parts: 3D reconstruction, aneurysm segmentation, centerline extraction, aneurysm measurement, automated microcatheter shaping recommendation, and display of the microcatheter shaping scheme (microcatheter shaping path and microcatheter shaping morphology). Specifically, 3D reconstruction refers to performing 3D reconstruction processing on the acquired cranial image data containing the aneurysm to obtain a vascular model; aneurysm segmentation refers to marking the aneurysm on the vascular model; centerline extraction refers to extracting the centerline of the aneurysm-bearing artery from the vascular model; aneurysm measurement refers to measuring the morphological information of the aneurysm; automated microcatheter shaping recommendation refers to matching microcatheter shaping schemes from a pre-set database that match the aneurysm measurement results, the centerline of the aneurysm-bearing artery, and the aneurysm segmentation results; and the microcatheter shaping scheme refers to displaying the microcatheter shaping path and microcatheter shaping morphology on a display device for physician review. Specific implementation details can be found in the description of the above embodiments and will not be repeated here.

[0061] Figure 3 Specific example diagrams of an automated microcatheter shaping device 300 according to some embodiments of this disclosure are shown.

[0062] like Figure 3 As shown, the automated microcatheter shaping device 300 includes: a three-dimensional reconstruction module 310, used to acquire cranial image data containing aneurysms and perform three-dimensional reconstruction processing on the cranial image data to obtain a vascular model; a segmentation module 320, used to segment the vascular model into aneurysms to obtain aneurysm segmentation results; a centerline extraction module 330, used to obtain the centerline of the aneurysm-bearing artery based on the vascular model and the aneurysm segmentation results, where the centerline of the aneurysm-bearing artery refers to the centerline of the artery where the aneurysm is located; a measurement module 340, used to measure the aneurysm based on the centerline of the aneurysm-bearing artery, the aneurysm segmentation results, and the vascular model to obtain aneurysm measurement results; the aneurysm measurement results are used to characterize the morphological information of the aneurysm; and a target microcatheter shaping scheme acquisition module 350, used to obtain the target microcatheter shaping scheme based on the aneurysm segmentation results, the aneurysm measurement results, and the centerline of the aneurysm-bearing artery.

[0063] As an optional embodiment of this disclosure, the cranial imaging data is any one of CT angiography data, magnetic resonance angiography data, or digital subtraction angiography data.

[0064] As an optional embodiment of this disclosure, the centerline extraction module 330 is specifically used to: extract the arterial centerline of each artery in the vascular model based on the vascular model; and determine the centerline of the aneurysm-bearing artery based on the aneurysm location information in the aneurysm segmentation results and the arterial centerline of each artery.

[0065] As an optional embodiment of this disclosure, the aneurysm measurement results include at least one of the following: aneurysm neck, aneurysm diameter, aneurysm height, aneurysm width, aneurysm entry angle, and aneurysm volume.

[0066] As an optional embodiment of this disclosure, the target microcatheter shaping scheme acquisition module 350 is specifically used to: match the aneurysm segmentation results, aneurysm measurement results, and the centerline of the carrier artery from a pre-set database to obtain a matching result; the database stores multiple data entries, each data entry including at least: a vascular model, aneurysm measurement results, the centerline of the carrier artery, a microcatheter shaping scheme, and surgical results; if the matching result indicates that data is matched from the database, the reference microcatheter shaping scheme in the matched data is used as the target microcatheter shaping scheme; if the matching result indicates that no data is matched from the database, the target microcatheter shaping scheme is generated based on the aneurysm segmentation results, aneurysm measurement results, the centerline of the carrier artery, and a specified microcatheter shaping algorithm.

[0067] As an optional embodiment of this disclosure, the target microcatheter shaping scheme obtaining module 350, based on the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery, performs matching from a pre-set database to obtain a matching result. This includes: for each piece of data in the database, calculating the matching degree between the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery and the data according to the weights configured for the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery; if the maximum value of the matching degree between the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery and the data in the database is greater than or equal to a specified threshold, then determining that a matching result indicates that data has been matched from the database; if the maximum value of the matching degree between the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery and the data in the database is less than the specified threshold, then determining that a matching result indicates that no data has been matched from the database.

[0068] For detailed implementation methods and technical effects, please refer to the specific description of the above-described method 100 embodiments, which will not be repeated here.

[0069] This completes the work on... Figure 3 Description of the device shown.

[0070] Correspondingly, this disclosure also provides Figure 3 The hardware structure diagram of the device shown is as follows: Figure 4 As shown, the electronic device 400 can be a device for implementing the method 100 described above. For example... Figure 4As shown, the electronic device 400 includes a processor 410 and a memory 420. The memory 420 is configured to store program instructions; the processor 410 is configured to load and execute the program instructions stored in the memory 420 to implement the corresponding microcatheter auto-shaping method embodiment shown above.

[0071] As one embodiment, memory 420 can be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as program instructions, data, etc. For example, memory 420 can be volatile memory, non-volatile memory, or similar storage media. Specifically, memory 420 can be RAM (Random Access Memory), flash memory, storage drives (such as hard disk drives), solid-state drives, any type of storage disk (such as optical discs, DVDs, etc.), or similar storage media, or combinations thereof.

[0072] This concludes the process. Figure 4 Description of the electronic device shown.

[0073] While numerous embodiments of this disclosure have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and intent of this disclosure. It should be understood that various alternatives to the embodiments of this disclosure described herein may be employed in the practice of this disclosure. The appended claims are intended to define the scope of this disclosure and therefore cover equivalents or alternatives within the scope of these claims.

Claims

1. A method for automatically shaping microcatheters, characterized in that, The method includes: Acquire cranial imaging data containing aneurysms, and perform three-dimensional reconstruction processing on the cranial imaging data to obtain a vascular model; The aneurysm segmentation was performed on the vascular model to obtain the aneurysm segmentation results; Based on the vascular model and the aneurysm segmentation results, the center line of the aneurysm-bearing artery is extracted, where the center line of the aneurysm-bearing artery refers to the center line of the artery where the aneurysm is located. The aneurysm is measured based on the centerline of the carrier artery, the aneurysm segmentation results, and the vascular model to obtain the aneurysm measurement results; the aneurysm measurement results are used to characterize the morphological information of the aneurysm. Based on the aneurysm segmentation results, the aneurysm measurement results, and the centerline of the aneurysm-bearing artery, a target microcatheter shaping scheme is obtained; The step of obtaining the target microcatheter shaping scheme based on the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery includes: Based on the aneurysm segmentation results, the aneurysm measurement results, and the centerline of the carrier artery, a matching result is obtained from a pre-set database. The database stores multiple data entries, each of which includes at least: a vascular model, aneurysm measurement results, the centerline of the carrier artery, a microcatheter shaping plan, and surgical results. If the matching result indicates that data is matched from the database, then the reference microcatheter shaping scheme in the matched data is taken as the target microcatheter shaping scheme; If the matching result indicates that no data can be matched from the database, the target microcatheter shaping scheme is generated based on the aneurysm segmentation result, the aneurysm measurement result, the centerline of the aneurysm-bearing artery, and the specified microcatheter shaping algorithm.

2. The method according to claim 1, characterized in that, The cranial imaging data can be any one of CT angiography data, magnetic resonance angiography data, or digital subtraction angiography data.

3. The method according to claim 1, characterized in that, The extraction of the centerline of the aneurysm-bearing artery based on the vascular model and the aneurysm segmentation results includes: Based on the vascular model, the arterial centerline of each artery in the vascular model is extracted; The centerline of the tumor-bearing artery is determined based on the location information of the aneurysm in the aneurysm segmentation results and the centerline of each artery.

4. The method according to claim 1, characterized in that, The aneurysm measurement results include at least one of the following: aneurysm neck, aneurysm diameter, aneurysm height, aneurysm width, aneurysm entry angle, and aneurysm volume.

5. The method according to claim 1, characterized in that, The matching process, based on the aneurysm segmentation results, the aneurysm measurement results, and the centerline of the carrier artery, is performed from a pre-defined database to obtain matching results, including: For each piece of data in the database, the matching degree between the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery and the data is calculated based on the weights already configured for the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery. If the maximum value of the matching degree between the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery and the data in the database is greater than or equal to a specified threshold, then the matching result is determined to indicate that data has been matched from the database; If the maximum value of the matching degree between the aneurysm segmentation result, the aneurysm measurement result, and the centerline of the aneurysm-bearing artery and the data in the database is less than a specified threshold, then the matching result indicates that no data can be matched from the database.

6. The method according to claim 1, characterized in that, After obtaining the target microcatheter shaping scheme, the method further includes: The target microcatheter shaping scheme is shown.

7. An automated microcatheter shaping device, characterized in that, The device includes: The three-dimensional reconstruction module is used to acquire cranial imaging data containing aneurysms and to perform three-dimensional reconstruction processing on the cranial imaging data to obtain a vascular model. The segmentation module is used to segment the vascular model into aneurysms and obtain the aneurysm segmentation results. The centerline extraction module is used to obtain the centerline of the tumor-bearing artery based on the vascular model and the aneurysm segmentation result, wherein the centerline of the tumor-bearing artery refers to the centerline of the artery where the aneurysm is located. The measurement module is used to measure the aneurysm based on the centerline of the aneurysm-bearing artery, the aneurysm segmentation results, and the vascular model to obtain the aneurysm measurement results; the aneurysm measurement results are used to characterize the morphological information of the aneurysm. A target microcatheter shaping scheme acquisition module is used to obtain a target microcatheter shaping scheme based on the aneurysm segmentation results, the aneurysm measurement results, and the centerline of the aneurysm-bearing artery. Specifically, the target microcatheter shaping scheme acquisition module is used for: Based on the aneurysm segmentation results, the aneurysm measurement results, and the centerline of the carrier artery, a matching result is obtained from a pre-set database. The database stores multiple data entries, each of which includes at least: a vascular model, aneurysm measurement results, the centerline of the carrier artery, a microcatheter shaping plan, and surgical results. If the matching result indicates that data is matched from the database, then the reference microcatheter shaping scheme in the matched data is taken as the target microcatheter shaping scheme; If the matching result indicates that no data can be matched from the database, the target microcatheter shaping scheme is generated based on the aneurysm segmentation result, the aneurysm measurement result, the centerline of the aneurysm-bearing artery, and the specified microcatheter shaping algorithm.

8. An electronic device, characterized in that, include: A processor, configured to execute program instructions; as well as A memory configured to store the program instructions, which, when loaded and executed by the processor, cause the processor to perform the microcatheter auto-shaping method according to any one of claims 1-6.

9. A computer-readable storage medium storing program instructions, characterized in that, When the program instructions are loaded and executed by the processor, the processor performs the microcatheter automatic shaping method according to any one of claims 1-6.

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