Multi-mode electromagnetic navigation assisted fresh corpse head transnasal endoscopic dissection measurement equipment and method

Abstract

The invention discloses a multi-mode electromagnetic navigation assisted fresh corpse head transnasal endoscopic dissection measurement device and a multi-mode electromagnetic navigation assisted fresh corpse head transnasal endoscopic dissection measurement method. The method is applied to a control module of the device, and the device further comprises an endoscope module and an electromagnetic tracking module. The method comprises the following steps: acquiring multi-modal image information corresponding to a fresh corpse head to be measured; generating a three-dimensional model corresponding to the fresh corpse head according to the multi-modal image information; obtaining a target position corresponding to a preset key anatomical structure in the three-dimensional model; the key anatomical structure at least comprises one or more of a nasal cavity, a paranasal sinus, a blood vessel and a nerve; when the endoscope module enters the nasal cavity of the fresh corpse head, magnetic field information sent by the electromagnetic tracking module is obtained; calculating a corresponding spatial position of the electromagnetic tracking module in the three-dimensional model according to the magnetic field information; generating navigation information corresponding to the endoscope module according to the spatial position and the target position, wherein the navigation information comprises direction information and distance information; and moving the endoscope module to the target position according to the navigation information.

Description

Technical Field

[0001] The present application relates to the field of electromagnetic navigation technology, and in particular to a multi-modal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device and method for a fresh cadaver head. Background Art

[0002] In the field of modern medicine, especially in otolaryngology and neurosurgery, endoscopic endoscopic approach (EEA) has become an important minimally invasive surgical technique. EEA enters the skull base through the nasal cavity and can be used to treat a variety of diseases, such as pituitary tumors and meningiomas. However, due to the complex anatomical structure of the nasal cavity and paranasal sinuses and the large individual differences, a highly accurate navigation and positioning system is required during the operation to ensure the safety and effectiveness of the operation.

[0003] Traditional navigation systems mainly rely on preoperative imaging data (such as CT and MRI) for positioning, but these systems have the following limitations:

[0004] 1. Low image registration accuracy: The registration error between image data of different modalities is large, which affects the navigation accuracy.

[0005] 2. Insufficient real-time feedback: Traditional systems lack real-time dynamic update capabilities and cannot adjust according to changes during the surgical process.

[0006] 3. Complex operation: Key anatomical structures need to be manually marked, which increases the workload of doctors.

[0007] 4. Security issues: In a complex environment, the stability and reliability of the system are difficult to guarantee.

[0008] Therefore, there is an urgent need for a multi-modal electromagnetic navigation-assisted fresh cadaver head transnasal endoscopic anatomical measurement device and method to solve at least one of the above problems. Summary of the invention

[0009] The present application provides a multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device and method for fresh cadaver heads, aiming to solve the problem that traditional navigation systems mainly rely on preoperative imaging data (such as CT and MRI) for positioning, but these systems have limitations such as low image registration accuracy, insufficient real-time feedback, complex operation and safety issues.

[0010] In a first aspect, the present application provides a method for measuring the anatomy of a fresh cadaver head through transnasal endoscopic anatomy assisted by a multimodal electromagnetic navigation, which is applied to a control module of a device for measuring the anatomy of a fresh cadaver head through transnasal endoscopic anatomy assisted by a multimodal electromagnetic navigation. The device for measuring the anatomy of a fresh cadaver head through transnasal endoscopic anatomy assisted by a multimodal electromagnetic navigation further comprises an endoscope module and an electromagnetic tracking module. The front end of the endoscope module is used to extend into the nasal cavity of the fresh cadaver head to be measured. The electromagnetic tracking module is arranged at the front end of the endoscope module to measure the magnetic field information of the nasal cavity. The method comprises:

[0011] Acquire multimodal image information corresponding to the fresh cadaver head to be measured, wherein the multimodal image information at least includes CT image information and MRI image information;

[0012] Generating a three-dimensional model corresponding to the fresh corpse head according to the multimodal image information;

[0013] Acquire a target position corresponding to a preset key anatomical structure in the three-dimensional model; the key anatomical structure includes at least one or more of a nasal cavity, a paranasal sinus, a blood vessel, and a nerve;

[0014] When the endoscope module enters the nasal cavity of the fresh cadaver head, obtaining magnetic field information sent by the electromagnetic tracking module;

[0015] Calculating the spatial position corresponding to the electromagnetic tracking module in the three-dimensional model according to the magnetic field information;

[0016] Generate navigation information corresponding to the endoscope module according to the spatial position and the target position, the navigation information including direction information and distance information;

[0017] The endoscope module is moved to the target position according to the navigation information.

[0018] In some embodiments, generating a three-dimensional model corresponding to the fresh corpse head according to the multimodal image information includes: performing initial alignment and fine alignment on the CT image information and the MRI image information; inputting the CT image information and the MRI image information into a pre-trained multi-task segmentation model, respectively, to complete automatic segmentation of the CT image information and the MRI image information, and respectively obtain segmentation information corresponding to the CT image information and the MRI image information; generating a CT three-dimensional model and a MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information; generating multiple label information corresponding to the CT three-dimensional model and the MRI three-dimensional model based on natural language processing technology; completing the fusion of the CT three-dimensional model and the MRI three-dimensional model according to the label information, and obtaining the three-dimensional model corresponding to the fresh corpse head.

[0019] Exemplarily, before respectively performing initial registration and fine registration on the CT image information and the MRI image information, it also includes: preprocessing the CT image information and the MRI image information; the preprocessing includes noise removal, standardization and slice alignment.

[0020] Exemplarily, the initial registration and fine registration of the CT image information and the MRI image information respectively include: respectively obtaining feature point information corresponding to the CT image information and the MRI image information; rigidly transforming the CT image information and the MRI image information according to the feature point information to complete the initial registration of the CT image information and the MRI image information; and performing thin plate spline transformation on the CT image information and the MRI image information to complete the fine registration.

[0021] Exemplarily, the segmentation information includes voxel data, a binary image, and local feature data; generating a CT three-dimensional model and an MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information, respectively, includes: acquiring a surface mesh from the binary image; adjusting the density of the surface mesh according to the local feature data; and generating the CT three-dimensional model and the MRI three-dimensional model according to the voxel data and the surface mesh corresponding to the CT image information and the MRI image information, respectively, based on a ray casting algorithm.

[0022] Exemplarily, the label information corresponds to a local area in the CT three-dimensional model or the MRI three-dimensional model; the fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the label information, including: obtaining the structure identifier corresponding to each of the label information; determining the fusion weight corresponding to the local area according to the structure information; if the structure identifier is bone, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is greater than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; if the structure identifier is soft tissue, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is less than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; and the fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the fusion weight.

[0023] In some embodiments, the electromagnetic tracking module includes a magnetic field generator and an electromagnetic tracking sensor, the electromagnetic tracking sensor is arranged at the front end of the endoscope module, and the magnetic field generator is arranged on the outside of the fresh corpse head to generate an external magnetic field; the calculation of the corresponding spatial position of the electromagnetic tracking module in the three-dimensional model based on the magnetic field information includes: obtaining distribution information corresponding to the external magnetic field; calculating the spatial position based on the distribution information and magnetic field information.

[0024] Exemplarily, calculating the spatial position according to the distribution information and the magnetic field information includes: obtaining the generator position and the magnetic moment of the magnetic field generator; constructing a magnetic field strength model corresponding to the electromagnetic tracking sensor according to the generator position and the magnetic moment of the magnetic field generator; and calculating the spatial position by inversely solving the magnetic field strength model according to the magnetic field information.

[0025] It should be noted that, in some embodiments, the calculating the spatial position by reverse solving in the magnetic field strength model according to the magnetic field information includes: obtaining the corresponding magnetic field strength value according to the magnetic field information; calculating the spatial position by reverse solving in the magnetic field strength model according to the distribution information and the magnetic field strength value; the expression of the magnetic field strength model includes:

[0026] ;

[0027] ;

[0028] in, is the magnetic field strength model, is the magnetic field strength value, is the spatial position corresponding to the electromagnetic tracking sensor, is the generator position, is the difference coefficient between the spatial position and the generator position, is the vacuum permeability, is the magnetic moment.

[0029] In a second aspect, the present application provides a multi-modal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device for a fresh cadaver head, comprising:

[0030] An endoscope module, the front end of which is used to extend into the nasal cavity of a fresh cadaver head to be measured;

[0031] An electromagnetic tracking module, which is disposed at the front end of the endoscope module and is used to measure the magnetic field information of the nasal cavity;

[0032] A control module, the control module comprising a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and implement the steps of the multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement method of a fresh cadaver head as described in the first aspect above when executing the computer program.

[0033] The present application discloses a multi-modal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device and method for fresh cadaver heads. The multi-modal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement method for fresh cadaver heads mainly includes the following steps and technical points:

[0034] First, multimodal image information of the fresh cadaver head to be measured is collected, and the image information includes at least CT images and MRI images. These two imaging technologies can provide complementary information. CT images can clearly show the bone structure, while MRI images have better resolution for soft tissues, blood vessels and nerves.

[0035] Then, the multimodal image data obtained above is used to generate a detailed three-dimensional anatomical model through computer processing. This model will serve as the basis for subsequent navigation and can intuitively display the specific location and morphological characteristics of the target area (such as the nasal cavity, paranasal sinuses, blood vessels and nerves).

[0036] Furthermore, the key anatomical parts that need to be focused on are identified and marked in the constructed 3D model, such as specific sinuses, important blood vessels or sensitive nerves, and their exact coordinates are recorded. When the endoscope module is inserted into the nasal cavity of the corpse's head, the electromagnetic tracking device at its front end starts working, continuously monitoring the changes in the magnetic field in the surrounding environment and transmitting the collected data to the control system.

[0037] Furthermore, based on the signals received from the electromagnetic sensor, the system can accurately calculate the spatial coordinates of the current location of the front end of the endoscope and map it to the previously established three-dimensional digital model.

[0038] Finally, based on the relative relationship between the current position and the predetermined target, the system automatically generates corresponding navigation suggestions, telling the operator which direction to move next and how far to go to reach the destination. The position of the endoscope is adjusted according to the guidance information provided until it successfully reaches the designated location to complete the measurement task.

[0039] The method provided combines multiple imaging techniques to create a high-precision 3D reconstruction model and uses advanced electromagnetic positioning technology to achieve precise spatial positioning, thereby greatly improving the ability to identify subtle structures during the operation. Compared with traditional methods that rely on static image data, this solution can provide instant feedback during the operation, helping to avoid the risk of accidentally injuring important organs or tissues. The entire process is highly automated, reducing errors caused by human factors, making even complex and delicate operations easier to master.

[0040] At the same time, for users, the equipment used in the provided methods can not only help them better understand human anatomy knowledge, but also allow them to fully practice before actual operation.

[0041] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0043] Figure 1 This is a schematic flow chart of the steps of a multi-modal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement method for a fresh cadaver head provided in an embodiment of the present application;

[0044] Figure 2 It is a schematic diagram of a scenario corresponding to the method provided in an embodiment of the present application;

[0045] Figure 3 It is a schematic structural diagram of a multi-modal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device for a fresh cadaver head provided in one embodiment of the present application;

[0046] Figure 4 It is a schematic block diagram of the structure of a control module provided in one embodiment of the present application.

[0047] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0049] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0050] It should be understood that, in order to facilitate the clear description of the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, the words "first", "second", etc. are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art can understand that the words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not necessarily limit the difference.

[0051] It should be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0052] It should also be understood that the term “and / or” used in the specification and appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0053] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0054] In the field of modern medicine, especially in otolaryngology and neurosurgery, endoscopic endoscopic approach (EEA) has become an important minimally invasive surgical technique. EEA enters the skull base through the nasal cavity and can be used to treat a variety of diseases, such as pituitary tumors and meningiomas. However, due to the complex anatomical structure of the nasal cavity and paranasal sinuses and the large individual differences, a highly accurate navigation and positioning system is required during the operation to ensure the safety and effectiveness of the operation.

[0055] Traditional navigation systems mainly rely on preoperative imaging data (such as CT and MRI) for positioning, but these systems have the following limitations:

[0056] 1. Low image registration accuracy: The registration error between image data of different modalities is large, which affects the navigation accuracy.

[0057] 2. Insufficient real-time feedback: Traditional systems lack real-time dynamic update capabilities and cannot adjust according to changes during the surgical process.

[0058] 3. Complex operation: Key anatomical structures need to be manually marked, which increases the workload of doctors.

[0059] 4. Security issues: In a complex environment, the stability and reliability of the system are difficult to guarantee.

[0060] Therefore, there is an urgent need for a multi-modal electromagnetic navigation-assisted fresh cadaver head transnasal endoscopic anatomical measurement device and method to solve at least one of the above problems.

[0061] To solve the above problems, please refer to Figure 1 , Figure 1This is a schematic flow chart of a method for multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement of a fresh cadaver head provided in an embodiment of the present application. The method is applied to a control module of a multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device for a fresh cadaver head. The multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device for a fresh cadaver head also includes an endoscope module and an electromagnetic tracking module. The front end of the endoscope module is used to extend into the nasal cavity of the fresh cadaver head to be measured. The electromagnetic tracking module is arranged at the front end of the endoscope module to measure the magnetic field information of the nasal cavity.

[0062] To solve the above problems, please refer to Figure 1 Specifically, Figure 1 As shown, the provided method includes steps S101 to S107. The details are as follows:

[0063] S101. Obtain multimodal image information corresponding to a fresh cadaver head to be measured, where the multimodal image information at least includes CT image information and MRI image information.

[0064] Specifically, first, detailed imaging data of fresh cadaver heads are obtained through imaging technologies such as CT (computed tomography) and MRI (magnetic resonance imaging). These imaging data can provide anatomical information of different levels and types, such as bone structure, soft tissue distribution, and the location of blood vessels and nerves. For example, a high-resolution CT scanner is used to obtain detailed bony structure images of the nasal cavity and surrounding areas; at the same time, an MRI device is used to obtain soft tissue images of the same area, including sinuses, blood vessels, and nerves. Multimodal image information can provide more comprehensive and detailed anatomical structure information, which helps to improve the accuracy of three-dimensional model construction in subsequent steps.

[0065] S102. Generate a three-dimensional model corresponding to the fresh corpse head based on the multimodal image information.

[0066] Specifically, the image data of different modalities obtained from S101 are fused and processed, and a comprehensive three-dimensional anatomical model is generated using medical image processing software or algorithms (such as methods based on deep learning). For example, advanced image registration technology is used to align and merge CT and MRI data to generate a three-dimensional model containing structures such as bones, soft tissues, blood vessels and nerves. The three-dimensional model provides an intuitive and accurate reference for subsequent surgical planning, improving the safety and accuracy of the surgery.

[0067] For example, based on DICOM data from CT / MRI, the Marching Cubes algorithm or deep learning model (such as 3D U-Net) is used to generate a fused 3D model containing bones, blood vessels, and nerves. Mesh smoothing and topology repair are performed through MeshLab. By reconstructing the 3D model of the nasopharynx, it can be interactively rotated and scaled, and the distance between the internal carotid artery and the optic canal can be marked. This replaces manual labeling, provides a panoramic anatomical view, and reduces the cognitive load of doctors.

[0068] For example, CT bone segmentation uses the threshold method to extract voxels ≥200HU (corresponding to bone tissue). MRI blood vessel segmentation uses the Frangi filter to enhance the tubular structure and extracts blood vessels in combination with the region growing method. Surface reconstruction uses the Marching Cubes algorithm on CT data, and the isosurface threshold is set to 150HU. 3D Residual U-Net is used to perform topological repair on MRI blood vessels, and the STL format mesh is output. The triangle patch size is ≤0.1mm, and the curvature smoothing is iterated 5 times. The diameter error of the reconstructed three-dimensional model of the internal carotid artery is ≤0.15mm (compared with microanatomical measurements). Multi-tissue fusion modeling is achieved, and the vascular modeling accuracy reaches sub-millimeter level, supporting precise avoidance during surgery.

[0069] S103. Obtain a target position corresponding to a preset key anatomical structure in the three-dimensional model; the key anatomical structure includes at least one or more of the nasal cavity, paranasal sinuses, blood vessels and nerves.

[0070] Specifically, on the constructed 3D model, professionals or automatic recognition algorithms mark the key anatomical structures that need to be focused on and their specific location coordinates. For example, doctors manually or with the help of intelligent tools mark key points such as the nasal entrance, each sinus opening, important blood vessel paths, and nerve directions in the 3D model. Clarifying the target location is conducive to formulating a more accurate operation plan and ensuring that important organs are not damaged during the actual operation.

[0071] S104. When the endoscope module enters the nasal cavity of the fresh corpse, the magnetic field information sent by the electromagnetic tracking module is obtained.

[0072] Specifically, when the front end of the endoscope is inserted into the patient's nasal cavity, the electromagnetic sensor installed on it starts working, continuously monitoring the changes in the magnetic field in the environment, and transmitting the collected data to the control system in real time. As the endoscope goes deeper into the nasal cavity, the micro-electromagnetic sensor carried on its front end continuously detects changes in the magnetic field strength and direction in the surrounding space. By monitoring the magnetic field information in real time, the system can accurately grasp the specific location of the endoscope, thereby realizing the dynamic positioning function.

[0073] At the same time, if Figure 2 As shown, the method utilizes a flexible navigation probe ( Figure 2The red part of the probe corresponding to mark 4 in the figure) If you mark the left and right endpoints of the anterior communicating artery, the distance between the probe and the anterior communicating artery can be automatically generated.

[0074] S105. Calculate the spatial position corresponding to the electromagnetic tracking module in the three-dimensional model according to the magnetic field information.

[0075] Specifically, based on the received magnetic field data and in combination with the pre-established magnetic field distribution map, a specific algorithm is used to calculate the exact coordinates of the electromagnetic tracking device relative to the three-dimensional anatomical model. Assuming that the standard magnetic field value at a fixed point A is known to be B0, and the actual value currently measured is B1, the relative displacement Δx, Δy, Δz between the current position P and A can be inferred from the difference between the two. This process enables a high level of position tracking accuracy to be maintained even in complex environments, enhancing the overall reliability of the system.

[0076] S106. Generate navigation information corresponding to the endoscope module according to the spatial position and the target position, where the navigation information includes direction information and distance information.

[0077] Specifically, the difference between the current position of the endoscope and the previously set target position is compared to generate a navigation guide including the direction of travel and distance prompt. If the target point is 5 cm to the right in front, the command "turn right 10 degrees and continue forward 5 cm" is output. Clear and concise navigation guidance helps the operator reach the predetermined destination quickly and accurately, reducing the risks of blind groping.

[0078] Navigation information can be generated by improving the A* algorithm, the cost function is:

[0079] ;

[0080] is the cost function, is the risk weight, the risk function Calculated based on blood vessel / nerve proximity, Represents from the starting node to the current node The actual cost (or cost) of the node. This value is usually calculated by accumulating the actual cost of each step from the starting point to the current node. Indicates that from the current node Estimated cost to reach the goal node (heuristic function).

[0081] Indicates the current node The risk value is used to evaluate the safety of passing through the node. The risk value can be calculated based on factors such as the proximity of anatomical structures and tissue types. Its expression can include:

[0082] .

[0083] Is a node With distance to key anatomical structures, is a small constant (such as 0.01) that prevents the denominator from being zero.

[0084] S107. Move the endoscope module to the target position according to the navigation information.

[0085] Specifically, the posture and route of the endoscope are adjusted according to the navigation suggestions provided by S106 until the designated target anatomical part is reached. According to the arrow direction and distance value on the display screen, the angle and length of the endoscope are gradually fine-tuned until the tip of the endoscope finally contacts the pre-calibrated key structure. The entire process achieves an effective connection from static planning to dynamic execution, greatly improving the efficiency and success rate of the operation.

[0086] In some embodiments, generating a three-dimensional model corresponding to the fresh corpse head according to the multimodal image information includes: performing initial alignment and fine alignment on the CT image information and the MRI image information; inputting the CT image information and the MRI image information into a pre-trained multi-task segmentation model, respectively, to complete automatic segmentation of the CT image information and the MRI image information, and respectively obtain segmentation information corresponding to the CT image information and the MRI image information; generating a CT three-dimensional model and a MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information; generating multiple label information corresponding to the CT three-dimensional model and the MRI three-dimensional model based on natural language processing technology; completing the fusion of the CT three-dimensional model and the MRI three-dimensional model according to the label information, and obtaining the three-dimensional model corresponding to the fresh corpse head.

[0087] Before performing initial registration and fine registration, the CT image information and MRI image information are preprocessed. The preprocessing steps include: Noise removal: Use filtering techniques (such as median filtering, Gaussian filtering, etc.) to remove noise in the image and improve image quality. Standardization: Adjust the image data of different modalities to a uniform grayscale range or intensity range for subsequent processing. Slice alignment: Ensure that the slices of CT and MRI images are spatially aligned to avoid registration errors caused by inconsistent slice positions.

[0088] By removing noise, interference factors can be reduced and images can be made clearer. Standardization processing makes data from different modalities comparable, facilitating subsequent registration and fusion. Slice alignment ensures the spatial correspondence between images of different modalities and improves the accuracy of registration.

[0089] Exemplarily, before respectively performing initial registration and fine registration on the CT image information and the MRI image information, it also includes: preprocessing the CT image information and the MRI image information; the preprocessing includes noise removal, standardization and slice alignment.

[0090] Key feature points are extracted from CT image information and MRI image information, which are usually significant points in the anatomical structure. According to the extracted feature point information, the CT image information and MRI image information are rigidly transformed (translated and rotated) to complete the initial registration. Based on the initial registration, the thin plate spline transformation (a nonlinear transformation method) is further used to finely align the CT image information and MRI image information to eliminate the errors caused by local deformation.

[0091] Through feature point matching and rigid transformation, the approximate correspondence between the two modal images can be quickly found. Thin plate spline transformation can more finely adjust the correspondence of local areas, further improve the registration accuracy, and thus generate a more accurate 3D model.

[0092] Exemplarily, the initial registration and fine registration of the CT image information and the MRI image information respectively include: respectively obtaining feature point information corresponding to the CT image information and the MRI image information; rigidly transforming the CT image information and the MRI image information according to the feature point information to complete the initial registration of the CT image information and the MRI image information; and performing thin plate spline transformation on the CT image information and the MRI image information to complete the fine registration.

[0093] The segmentation information includes voxel data, binary image and local feature data. The surface mesh is extracted from the binary image to represent the surface of the anatomical structure. The density of the surface mesh is adjusted according to the local feature data to better reflect the details of the anatomical structure. Based on the ray casting algorithm, the voxel data and surface mesh are combined to generate the CT 3D model and the MRI 3D model respectively.

[0094] By combining voxel data with surface meshes, more detailed and accurate 3D models can be generated. Adjusting the mesh density can be optimized according to the importance of different areas to improve the detail performance of the model. The ray casting algorithm is an efficient 3D reconstruction method that can generate high-quality 3D models in a short time.

[0095] Exemplarily, the segmentation information includes voxel data, a binary image, and local feature data; generating a CT three-dimensional model and an MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information, respectively, includes: acquiring a surface mesh from the binary image; adjusting the density of the surface mesh according to the local feature data; and generating the CT three-dimensional model and the MRI three-dimensional model according to the voxel data and the surface mesh corresponding to the CT image information and the MRI image information, respectively, based on a ray casting algorithm.

[0096] The segmentation information includes voxel data, binary image and local feature data. The surface mesh is extracted from the binary image to represent the surface of the anatomical structure. The density of the surface mesh is adjusted according to the local feature data to better reflect the details of the anatomical structure. Based on the ray casting algorithm, the voxel data and surface mesh are combined to generate the CT 3D model and the MRI 3D model respectively.

[0097] By combining voxel data with surface meshes, more detailed and accurate 3D models can be generated. Adjusting the mesh density can be optimized according to the importance of different areas to improve the detail performance of the model. The ray casting algorithm is an efficient 3D reconstruction method that can generate high-quality 3D models in a short time.

[0098] Exemplarily, the label information corresponds to a local area in the CT three-dimensional model or the MRI three-dimensional model; the fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the label information, including: obtaining the structure identifier corresponding to each of the label information; determining the fusion weight corresponding to the local area according to the structure information; if the structure identifier is bone, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is greater than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; if the structure identifier is soft tissue, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is less than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; and the fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the fusion weight.

[0099] The label information corresponds to a local area in the CT three-dimensional model or the MRI three-dimensional model. The structural identifier (such as bone, soft tissue, etc.) corresponding to each label information is obtained. If the structural identifier is bone, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is greater than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model. If the structural identifier is soft tissue, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is less than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model. According to the fusion weight, the CT three-dimensional model and the MRI three-dimensional model are fused to generate a comprehensive three-dimensional model.

[0100] Through different fusion weights, the advantages of each modality can be better preserved, such as the advantages of CT in bone imaging and MRI in soft tissue imaging. The comprehensive three-dimensional model can provide more comprehensive and detailed anatomical information, which helps to improve the accuracy of surgical planning and navigation. The fused model can better meet clinical needs and provide a more reliable and practical reference.

[0101] In some embodiments, the electromagnetic tracking module includes a magnetic field generator and an electromagnetic tracking sensor, the electromagnetic tracking sensor is arranged at the front end of the endoscope module, and the magnetic field generator is arranged on the outside of the fresh corpse head to generate an external magnetic field; the calculation of the corresponding spatial position of the electromagnetic tracking module in the three-dimensional model based on the magnetic field information includes: obtaining distribution information corresponding to the external magnetic field; calculating the spatial position based on the distribution information and magnetic field information.

[0102] The electromagnetic tracking module includes a magnetic field generator and an electromagnetic tracking sensor. The specific configuration is as follows: Magnetic field generator: set outside the fresh cadaver head, used to generate an external magnetic field. Electromagnetic tracking sensor: set at the front end of the endoscope module, used to measure the magnetic field information in the nasal cavity.

[0103] The distribution model of the external magnetic field is constructed by using the known position and magnetic moment of the magnetic field generator. The precise position of the electromagnetic tracking sensor in the three-dimensional model is calculated using the magnetic field distribution information and the actual measured magnetic field information.

[0104] Through the cooperation of external magnetic field generator and internal sensor, high-precision spatial positioning can be achieved. It can monitor the position change of endoscope in real time, provide dynamic update capability, and improve the accuracy of surgical navigation. It reduces the workload of manual marking and adjustment, and improves the efficiency and safety of surgery.

[0105] Exemplarily, calculating the spatial position according to the distribution information and the magnetic field information includes: obtaining the generator position and the magnetic moment of the magnetic field generator; constructing a magnetic field strength model corresponding to the electromagnetic tracking sensor according to the generator position and the magnetic moment of the magnetic field generator; and calculating the spatial position by inversely solving the magnetic field strength model according to the magnetic field information.

[0106] By determining the specific position and magnetic moment of the magnetic field generator, a magnetic field strength model corresponding to the electromagnetic tracking sensor is constructed according to the position and magnetic moment of the magnetic field generator. Based on the actual measured magnetic field information, the spatial position of the electromagnetic tracking sensor is calculated by reverse solving the magnetic field strength model.

[0107] By building a detailed magnetic field strength model, the magnetic field distribution can be described more accurately and the positioning accuracy can be improved. The inverse solution method can infer the specific position of the sensor from the actual measurement value to ensure the accuracy of positioning. This method supports real-time calculation and can dynamically adjust the position of the endoscope during surgery, improving the flexibility and reliability of navigation.

[0108] It should be noted that, in some embodiments, the calculating the spatial position by reverse solving in the magnetic field strength model according to the magnetic field information includes: obtaining the corresponding magnetic field strength value according to the magnetic field information; calculating the spatial position by reverse solving in the magnetic field strength model according to the distribution information and the magnetic field strength value; the expression of the magnetic field strength model includes:

[0109] ;

[0110] ;

[0111] in, is the magnetic field strength model, is the magnetic field strength value, is the spatial position corresponding to the electromagnetic tracking sensor, is the generator position, is the difference coefficient between the spatial position and the generator position, is the vacuum permeability, is the magnetic moment.

[0112] The actual measured magnetic field strength value is obtained from the electromagnetic tracking sensor. Based on the magnetic field distribution information and the actual measured magnetic field strength value, the spatial position of the electromagnetic tracking sensor is calculated by reverse solving in the magnetic field strength model. Through a specific mathematical model, the spatial position of the electromagnetic tracking sensor can be accurately calculated. The reverse solution method based on the magnetic field strength model can achieve high-precision spatial positioning and reduce errors. This method supports real-time calculation and can dynamically adjust the position of the endoscope during surgery, improving the real-time and accuracy of navigation. The use of mathematical models makes the positioning process more stable and reliable, reducing the impact of environmental factors on the positioning results.

[0113] See also Figure 3 As shown, Figure 31 is a schematic diagram of the structure of a multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device 200 for a fresh cadaver head provided in an embodiment of the present application. The multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device 200 for a fresh cadaver head is used to execute the steps of the multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement method for a fresh cadaver head shown in the above-mentioned embodiments. The multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device 200 for a fresh cadaver head can be a single server or a server cluster, or the multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device 200 for a fresh cadaver head can be a terminal, which can be a handheld terminal, a laptop computer, a wearable device or a robot, etc.

[0114] like Figure 3 As shown, the multi-modal electromagnetic navigation-assisted fresh cadaver head transnasal endoscopic anatomical measurement device 200 comprises:

[0115] A multi-modal acquisition unit 201 is used to acquire multi-modal image information corresponding to a fresh cadaver head to be measured, wherein the multi-modal image information at least includes CT image information and MRI image information;

[0116] A three-dimensional generation unit 202, configured to generate a three-dimensional model corresponding to the fresh corpse head according to the multimodal image information;

[0117] A position acquisition unit 203 is used to acquire a target position corresponding to a preset key anatomical structure in the three-dimensional model; the key anatomical structure includes at least one or more of a nasal cavity, a paranasal sinus, a blood vessel, and a nerve;

[0118] An information acquisition unit 204 is used to acquire magnetic field information sent by the electromagnetic tracking module when the endoscope module enters the nasal cavity of the fresh cadaver head;

[0119] A space acquisition unit 205, configured to calculate a spatial position corresponding to the electromagnetic tracking module in the three-dimensional model according to the magnetic field information;

[0120] A navigation generating unit 206, configured to generate navigation information corresponding to the endoscope module according to the spatial position and the target position, wherein the navigation information includes direction information and distance information;

[0121] The target moving unit 207 is used to move the endoscope module to the target position according to the navigation information.

[0122] In some embodiments, generating a three-dimensional model corresponding to the fresh corpse head according to the multimodal image information includes: performing initial alignment and fine alignment on the CT image information and the MRI image information; inputting the CT image information and the MRI image information into a pre-trained multi-task segmentation model, respectively, to complete automatic segmentation of the CT image information and the MRI image information, and respectively obtain segmentation information corresponding to the CT image information and the MRI image information; generating a CT three-dimensional model and a MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information; generating multiple label information corresponding to the CT three-dimensional model and the MRI three-dimensional model based on natural language processing technology; completing the fusion of the CT three-dimensional model and the MRI three-dimensional model according to the label information, and obtaining the three-dimensional model corresponding to the fresh corpse head.

[0123] Exemplarily, before respectively performing initial registration and fine registration on the CT image information and the MRI image information, it also includes: preprocessing the CT image information and the MRI image information; the preprocessing includes noise removal, standardization and slice alignment.

[0124] Exemplarily, the initial registration and fine registration of the CT image information and the MRI image information respectively include: respectively obtaining feature point information corresponding to the CT image information and the MRI image information; rigidly transforming the CT image information and the MRI image information according to the feature point information to complete the initial registration of the CT image information and the MRI image information; and performing thin plate spline transformation on the CT image information and the MRI image information to complete the fine registration.

[0125] Exemplarily, the segmentation information includes voxel data, a binary image, and local feature data; generating a CT three-dimensional model and an MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information, respectively, includes: acquiring a surface mesh from the binary image; adjusting the density of the surface mesh according to the local feature data; and generating the CT three-dimensional model and the MRI three-dimensional model according to the voxel data and the surface mesh corresponding to the CT image information and the MRI image information, respectively, based on a ray casting algorithm.

[0126] Exemplarily, the label information corresponds to a local area in the CT three-dimensional model or the MRI three-dimensional model; the fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the label information, including: obtaining the structure identifier corresponding to each of the label information; determining the fusion weight corresponding to the local area according to the structure information; if the structure identifier is bone, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is greater than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; if the structure identifier is soft tissue, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is less than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; and the fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the fusion weight.

[0127] In some embodiments, the electromagnetic tracking module includes a magnetic field generator and an electromagnetic tracking sensor, the electromagnetic tracking sensor is arranged at the front end of the endoscope module, and the magnetic field generator is arranged on the outside of the fresh corpse head to generate an external magnetic field; the calculation of the corresponding spatial position of the electromagnetic tracking module in the three-dimensional model based on the magnetic field information includes: obtaining distribution information corresponding to the external magnetic field; calculating the spatial position based on the distribution information and magnetic field information.

[0128] Exemplarily, calculating the spatial position according to the distribution information and the magnetic field information includes: obtaining the generator position and the magnetic moment of the magnetic field generator; constructing a magnetic field strength model corresponding to the electromagnetic tracking sensor according to the generator position and the magnetic moment of the magnetic field generator; and calculating the spatial position by inversely solving the magnetic field strength model according to the magnetic field information.

[0129] It should be noted that, in some embodiments, the calculating the spatial position by reverse solving in the magnetic field strength model according to the magnetic field information includes: obtaining the corresponding magnetic field strength value according to the magnetic field information; calculating the spatial position by reverse solving in the magnetic field strength model according to the distribution information and the magnetic field strength value; the expression of the magnetic field strength model includes:

[0130] ;

[0131] ;

[0132] in, is the magnetic field strength model, is the magnetic field strength value, is the spatial position corresponding to the electromagnetic tracking sensor, is the generator position, is the difference coefficient between the spatial position and the generator position, is the vacuum permeability, is the magnetic moment.

[0133] It should be noted that, those skilled in the art can clearly understand that, for the sake of convenience and brevity of description, the specific working processes of the multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device for a fresh cadaver head and each unit described above can refer to the corresponding processes in the multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement embodiments of a fresh cadaver head described in the above-mentioned embodiments, and will not be repeated here.

[0134] The above-mentioned multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement of fresh cadaver head can be implemented in the form of a computer program. The computer program can be used in Figure 3 Run on the device shown.

[0135] An embodiment of the present application provides a multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device for a fresh cadaver head, comprising: an endoscope module, the front end of which is used to extend into the nasal cavity of a fresh cadaver head to be measured; an electromagnetic tracking module, the electromagnetic tracking module is arranged at the front end of the endoscope module, and is used to measure the magnetic field information of the nasal cavity; a control module, the control module comprises a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and implement any of the methods described above when executing the computer program.

[0136] The front end of the endoscope module is designed to be inserted into the nasal cavity of a fresh cadaver head, and is usually equipped with a high-definition camera and lighting system to provide clear visual feedback during surgery. The endoscope module is used to observe the internal structure of the nasal cavity and transmit real-time images to the control module through the camera.

[0137] The electromagnetic tracking module is set at the front end of the endoscope module, usually a small sensor. It is used to measure the magnetic field information in the nasal cavity. This magnetic field information is generated by an external magnetic field generator, and the sensor determines its position in three-dimensional space by detecting this magnetic field information.

[0138] The control module is used to store computer programs, multimodal imaging data, three-dimensional models and other information. The processor executes the computer program stored in the memory to achieve the following functions: Acquire multimodal imaging information (such as CT and MRI) and generate a three-dimensional model. Mark the target position of key anatomical structures in the three-dimensional model. Calculate its spatial position in the three-dimensional model based on the magnetic field information sent by the electromagnetic tracking module. Generate navigation information, including direction information and distance information. Control the endoscope module to move to the target position.

[0139] For example, a high-resolution CT scanner is used to obtain detailed bony structure images of the nasal cavity and surrounding areas, while an MRI device is used to obtain soft tissue images of the same area. The CT and MRI image data are preprocessed, including noise removal, standardization, and slice alignment, and then initial registration and fine registration are performed.

[0140] Feature point information is extracted from CT and MRI images, and initial registration is completed by rigid transformation, and then fine registration is completed by thin plate spline transformation. CT 3D model and MRI 3D model are generated based on segmentation information (voxel data, binary image and local feature data), and finally a comprehensive 3D model is generated by fusion.

[0141] The external magnetic field generator generates a magnetic field with a known distribution, and the electromagnetic tracking sensor at the front end of the endoscope measures the actual magnetic field information. The magnetic field strength model is constructed based on the position and magnetic moment of the magnetic field generator, and the spatial position of the sensor is calculated by inverse solution. Based on the spatial position of the sensor and the pre-marked key anatomical structure target position, navigation information is generated, including direction information and distance information. The posture and route of the endoscope module are adjusted according to the navigation information until the predetermined target position is reached.

[0142] The three-dimensional model and electromagnetic tracking technology generated by multimodal imaging data can achieve high-precision spatial positioning and reduce errors during surgery. The electromagnetic tracking module can monitor the position changes of the endoscope in real time, provide dynamic update capabilities, and ensure the timeliness and accuracy of navigation information. Automated image processing and navigation information generation reduce the workload of manual marking and adjustment, and improve operational efficiency. High-precision positioning and real-time feedback help avoid damage to important organs and improve the safety and success rate of surgery. Multimodal imaging data provides more comprehensive and detailed anatomical structure information, which helps to formulate more accurate operation plans. By dynamically adjusting the position of the endoscope, the stability and reliability of the system can be maintained in complex environments to adapt to different surgical needs.

[0143] The multimodal electromagnetic navigation-assisted fresh cadaver transnasal endoscopic anatomical measurement device achieves high-precision, real-time feedback and automated surgical navigation through the collaborative work of the endoscope module, electromagnetic tracking module and control module. This device not only improves the safety and success rate of surgery, but also simplifies the operation process and reduces the workload of doctors, and has broad application prospects.

[0144] See also Figure 4 , Figure 4 : is a schematic block diagram of the structure of a control module provided in an embodiment of the present application. The control module includes a processor, a memory and a network interface connected via a device bus, wherein the memory may include a storage medium and an internal memory.

[0145] The storage medium can store an operating device and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can perform any multi-modal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement of a fresh cadaver head.

[0146] The processor is used to provide computing and control capabilities and support the operation of the entire control module.

[0147] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can perform any multi-modal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement of a fresh cadaver head.

[0148] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the terminal to which the scheme of the present application is applied. The specific control module may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0149] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0150] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0151] Acquire multimodal image information corresponding to the fresh cadaver head to be measured, wherein the multimodal image information at least includes CT image information and MRI image information;

[0152] Generating a three-dimensional model corresponding to the fresh corpse head according to the multimodal image information;

[0153] Acquire a target position corresponding to a preset key anatomical structure in the three-dimensional model; the key anatomical structure includes at least one or more of a nasal cavity, a paranasal sinus, a blood vessel, and a nerve;

[0154] When the endoscope module enters the nasal cavity of the fresh cadaver head, obtaining magnetic field information sent by the electromagnetic tracking module;

[0155] Calculating the spatial position corresponding to the electromagnetic tracking module in the three-dimensional model according to the magnetic field information;

[0156] Generate navigation information corresponding to the endoscope module according to the spatial position and the target position, the navigation information including direction information and distance information;

[0157] The endoscope module is moved to the target position according to the navigation information.

[0158] In some embodiments, generating a three-dimensional model corresponding to the fresh corpse head according to the multimodal image information includes: performing initial alignment and fine alignment on the CT image information and the MRI image information; inputting the CT image information and the MRI image information into a pre-trained multi-task segmentation model, respectively, to complete automatic segmentation of the CT image information and the MRI image information, and respectively obtain segmentation information corresponding to the CT image information and the MRI image information; generating a CT three-dimensional model and a MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information; generating multiple label information corresponding to the CT three-dimensional model and the MRI three-dimensional model based on natural language processing technology; completing the fusion of the CT three-dimensional model and the MRI three-dimensional model according to the label information, and obtaining the three-dimensional model corresponding to the fresh corpse head.

[0159] Exemplarily, before respectively performing initial registration and fine registration on the CT image information and the MRI image information, it also includes: preprocessing the CT image information and the MRI image information; the preprocessing includes noise removal, standardization and slice alignment.

[0160] Exemplarily, the initial registration and fine registration of the CT image information and the MRI image information respectively include: respectively obtaining feature point information corresponding to the CT image information and the MRI image information; rigidly transforming the CT image information and the MRI image information according to the feature point information to complete the initial registration of the CT image information and the MRI image information; and performing thin plate spline transformation on the CT image information and the MRI image information to complete the fine registration.

[0161] Exemplarily, the segmentation information includes voxel data, a binary image, and local feature data; generating a CT three-dimensional model and an MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information, respectively, includes: acquiring a surface mesh from the binary image; adjusting the density of the surface mesh according to the local feature data; and generating the CT three-dimensional model and the MRI three-dimensional model according to the voxel data and the surface mesh corresponding to the CT image information and the MRI image information, respectively, based on a ray casting algorithm.

[0162] Exemplarily, the label information corresponds to a local area in the CT three-dimensional model or the MRI three-dimensional model; the fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the label information, including: obtaining the structure identifier corresponding to each of the label information; determining the fusion weight corresponding to the local area according to the structure information; if the structure identifier is bone, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is greater than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; if the structure identifier is soft tissue, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is less than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; and the fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the fusion weight.

[0163] In some embodiments, the electromagnetic tracking module includes a magnetic field generator and an electromagnetic tracking sensor, the electromagnetic tracking sensor is arranged at the front end of the endoscope module, and the magnetic field generator is arranged on the outside of the fresh corpse head to generate an external magnetic field; the calculation of the corresponding spatial position of the electromagnetic tracking module in the three-dimensional model based on the magnetic field information includes: obtaining distribution information corresponding to the external magnetic field; calculating the spatial position based on the distribution information and magnetic field information.

[0164] Exemplarily, calculating the spatial position according to the distribution information and the magnetic field information includes: obtaining the generator position and the magnetic moment of the magnetic field generator; constructing a magnetic field strength model corresponding to the electromagnetic tracking sensor according to the generator position and the magnetic moment of the magnetic field generator; and calculating the spatial position by inversely solving the magnetic field strength model according to the magnetic field information.

[0165] It should be noted that, in some embodiments, the calculating the spatial position by reverse solving in the magnetic field strength model according to the magnetic field information includes: obtaining the corresponding magnetic field strength value according to the magnetic field information; calculating the spatial position by reverse solving in the magnetic field strength model according to the distribution information and the magnetic field strength value; the expression of the magnetic field strength model includes:

[0166] ;

[0167] ;

[0168] in, is the magnetic field strength model, is the magnetic field strength value, is the spatial position corresponding to the electromagnetic tracking sensor, is the generator position, is the difference coefficient between the spatial position and the generator position, is the vacuum permeability, is the magnetic moment.

[0169] It should be noted that, those skilled in the art can clearly understand that, for the sake of convenience and brevity of description, the specific working process of the processor described above can refer to the corresponding process in the multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement of fresh cadaver head described in the above embodiments, and will not be repeated here.

[0170] A computer-readable storage medium is also provided in an embodiment of the present application, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and the processor executes the program instructions to implement the steps of the multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement method of a fresh cadaver head provided in the above-mentioned embodiments of the present application.

[0171] The computer-readable storage medium may be an internal storage unit of the control module described in the above embodiment, such as a hard disk or memory of the control module. The computer-readable storage medium may also be an external storage device of the control module, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the control module.

[0172] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A multi-modal electromagnetic navigation-assisted fresh cadaver head transnasal endoscopic anatomical measurement device and method, characterized in that: A control module applied to a multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device for a fresh cadaver head, wherein the multimodal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device for a fresh cadaver head further comprises an endoscope module and an electromagnetic tracking module, wherein the front end of the endoscope module is used to extend into the nasal cavity of the fresh cadaver head to be measured, and the electromagnetic tracking module is arranged at the front end of the endoscope module to measure the magnetic field information of the nasal cavity; the method comprises: Acquire multimodal image information corresponding to the fresh cadaver head to be measured, wherein the multimodal image information at least includes CT image information and MRI image information; Generating a three-dimensional model corresponding to the fresh corpse head according to the multimodal image information; Acquiring a target position corresponding to a preset key anatomical structure in the three-dimensional model; the key anatomical structure includes at least one or more of a nasal cavity, a paranasal sinus, a blood vessel, and a nerve; When the endoscope module enters the nasal cavity of the fresh cadaver head, obtaining magnetic field information sent by the electromagnetic tracking module; Calculating the spatial position corresponding to the electromagnetic tracking module in the three-dimensional model according to the magnetic field information; Generate navigation information corresponding to the endoscope module according to the spatial position and the target position, the navigation information including direction information and distance information; The endoscope module is moved to the target position according to the navigation information.

2. The method according to claim 1, characterized in that Generating a three-dimensional model corresponding to the fresh corpse head according to the multimodal image information includes: Performing initial registration and fine registration on the CT image information and the MRI image information; Inputting the CT image information and the MRI image information into a pre-trained multi-task segmentation model respectively, completing automatic segmentation of the CT image information and the MRI image information, and obtaining segmentation information corresponding to the CT image information and the MRI image information respectively; Generate a CT three-dimensional model and an MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information respectively; Generate multiple label information corresponding to the CT three-dimensional model and the MRI three-dimensional model respectively based on natural language processing technology; The CT three-dimensional model and the MRI three-dimensional model are fused according to the label information to obtain a three-dimensional model corresponding to the fresh corpse head.

3. The method according to claim 2, characterized in that Before respectively performing initial registration and fine registration on the CT image information and the MRI image information, the method further includes: The CT image information and the MRI image information are preprocessed; the preprocessing includes noise removal, standardization and slice alignment.

4. The method according to claim 2, characterized in that: The performing initial registration and fine registration on the CT image information and the MRI image information respectively includes: Respectively obtaining feature point information corresponding to the CT image information and the MRI image information; Performing a rigid transformation on the CT image information and the MRI image information according to the feature point information to complete initial registration of the CT image information and the MRI image information; The CT image information and the MRI image information are subjected to thin plate spline transformation to complete the fine registration.

5. The method according to claim 2, characterized in that: The segmentation information includes voxel data, binary images and local feature data; and generating a CT three-dimensional model and an MRI three-dimensional model according to the segmentation information corresponding to the CT image information and the MRI image information, respectively, includes: Obtaining a surface mesh from the binary image; adjusting the density of the surface grid according to the local feature data; The CT three-dimensional model and the MRI three-dimensional model are generated based on the voxel data and the surface mesh corresponding to the CT image information and the MRI image information respectively based on a ray casting algorithm.

6. The method according to claim 2, characterized in that The label information corresponds to a local area in the CT three-dimensional model or the MRI three-dimensional model; The fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the label information, including: Obtaining a structure identifier corresponding to each of the tag information; Determine the fusion weight corresponding to the local area according to the structural information; if the structure is identified as bone, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is greater than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; if the structure is identified as soft tissue, the fusion weight corresponding to the local area of ​​the CT three-dimensional model is less than the fusion weight corresponding to the local area of ​​the MRI three-dimensional model; The fusion of the CT three-dimensional model and the MRI three-dimensional model is completed according to the fusion weight.

7. The method according to claim 1, characterized in that The electromagnetic tracking module includes a magnetic field generator and an electromagnetic tracking sensor, wherein the electromagnetic tracking sensor is disposed at the front end of the endoscope module, and the magnetic field generator is disposed outside the fresh corpse head to generate an external magnetic field; the method of calculating the corresponding spatial position of the electromagnetic tracking module in the three-dimensional model according to the magnetic field information includes: Acquiring distribution information corresponding to the external magnetic field; The spatial position is calculated according to the distribution information and the magnetic field information.

8. The method according to claim 7, characterized in that The calculating the spatial position according to the distribution information and the magnetic field information comprises: Obtaining a generator position and a magnetic moment of the magnetic field generator; Constructing a magnetic field intensity model corresponding to the electromagnetic tracking sensor according to the generator position and magnetic moment of the magnetic field generator; The spatial position is calculated by reversely solving the magnetic field strength model according to the magnetic field information.

9. The method according to claim 8, characterized in that The calculating the spatial position by inversely solving the magnetic field strength model according to the magnetic field information includes: Acquire a corresponding magnetic field strength value according to the magnetic field information; The spatial position is calculated by reversely solving the magnetic field strength model according to the distribution information and the magnetic field strength value; the expression of the magnetic field strength model includes: ； ； in, is the magnetic field strength model, is the magnetic field strength value, is the spatial position corresponding to the electromagnetic tracking sensor, is the generator position, is the difference coefficient between the spatial position and the generator position, is the vacuum permeability, is the magnetic moment.

10. A multi-modal electromagnetic navigation-assisted transnasal endoscopic anatomical measurement device for fresh cadaver heads, characterized in that: include: An endoscope module, the front end of which is used to extend into the nasal cavity of a fresh cadaver head to be measured; An electromagnetic tracking module, which is disposed at the front end of the endoscope module and is used to measure the magnetic field information of the nasal cavity; A control module, the control module comprising a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and implement the method as claimed in any one of claims 1 to 9 when executing the computer program.

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