316 results about "Surgical planning" patented technology

This application is directed to systems, methods, and devices for image based analysis of plaque. In some embodiments, the approaches herein can be used for developing treatment plans, which can include local treatment, systemic treatment, or both. In some embodiments, the approaches herein can be used for stent selection. In some embodiments, the approaches herein can be used for surgical planning, which can include robotic surgical planning. In some embodiments, the approaches herein can be used for image normalization. In some embodiments, the approaches herein can be used for identifying plaque calcification thresholds. In some embodiments, the approaches herein can be used for identifying thin cap fibroatheroma. In some embodiments, the approaches herein can be used for coronary artery tree reconstruction. Some embodiments are directed to coronary artery disease risk stratification.

This application is directed to systems, methods, and devices for image based analysis of plaque. In some embodiments, the approaches herein can be used for developing treatment plans, which can include local treatment, systemic treatment, or both. In some embodiments, the approaches herein can be used for stent selection. In some embodiments, the approaches herein can be used for surgical planning, which can include robotic surgical planning. In some embodiments, the approaches herein can be used for image normalization. In some embodiments, the approaches herein can be used for identifying plaque calcification thresholds. In some embodiments, the approaches herein can be used for identifying thin cap fibroatheroma. In some embodiments, the approaches herein can be used for coronary artery tree reconstruction. Some embodiments are directed to coronary artery disease risk stratification.

The invention relates to the technical field of medical image processing, in particular to an artificial intelligence assisted intraoperative imaging method, which comprises the following steps: S1, preprocessing a multi-modal medical image, segmenting and recognizing an anatomical structure by a deep learning model according to the preprocessed image, measuring anatomical parameters based on a segmentation and recognition result, and generating an operation planning path by artificial intelligence according to the anatomical parameters; s2, collecting a C-shaped arm perspective image stream in real time, dynamically tracking space coordinates of a surgical instrument, comparing the position of the instrument with a surgical planned path, calculating offset, and when the offset is greater than an offset threshold, outputting correction guidance through an AR superposition layer; and S3, monitoring an image quality index in real time, dynamically adjusting exposure parameters through a reinforcement learning model, and when a metal implant is detected, switching a dual-energy-spectrum mode and executing an artifact suppression algorithm. According to the method, preoperative precise planning and intraoperative assistance are realized through artificial intelligence, the problems of poor image quality and high radiation risk are solved through technical optimization, and the method has important clinical application value.

A process for tissue modelling from a medical image of a subject, for forming a three-dimensional (3D) model of a region of interest (ROI) of a subject with one or more tissue types, said process including the steps of (i) utilising a rule-based method that automatically generates the weak annotation, initial seed area from a medial image (210b); (ii) utilising a proposal generation method that integrates the multi-scale image features and anatomical prior (220b); and (iii) a comprehensive loss for CNN training that optimizes the pixel classification and feature distribution simultaneously (230).

A surgical planning system for use in surgical procedures to repair an anatomy of interest includes a preplanning system to generate a virtual surgical plan and a mixed reality system that includes a visualization device wearable by a user to view the virtual surgical plan projected in a real environment. The virtual surgical plan includes a 3D virtual model of the anatomy of interest. When wearing the visualization device, the user can align the 3D virtual model with the real anatomy of interest, thereby achieving a registration between details of the virtual surgical plan and the real anatomy of interest. The registration enables a surgeon to implement the virtual surgical plan on the real anatomy of interest without the use of tracking markers.

A computer-implemented method of pre-operatively evaluating bone structure for use of a bone graft in a surgical procedure can comprise generating a three-dimensional bone model of a bone of a patient for output in a video display unit, determining a volume of interest (VOI) on the three-dimensional bone model where a bone defect exists, adding an internal bone property for bone matter of the bone structure to the three-dimensional bone model at the volume of interest, analyzing the internal bone property in the volume of interest relative to a treatment for a bone defect, and outputting indicia on the video display unit that indicates utility of a bone graft for the treatment. A surgical planning system can comprise memory having instructions for implementing the computer-implemented method.

The invention relates to the technical field of orthopedic surgery, in particular to a system for automatically planning a screw channel range, which comprises a medical image acquisition module used for receiving and preprocessing CT, MRI and other medical images from medical equipment; the three-dimensional reconstruction module is used for performing three-dimensional reconstruction on the preprocessed two-dimensional medical image to generate a three-dimensional skeleton model; the multi-constraint path planning module is used for planning a candidate path set meeting anatomical and mechanical constraints in the three-dimensional skeleton model; the parameter calculation module is used for calculating path information of the candidate path set; and the visualization module draws a screw channel based on the path information and displays related parameters. The method has the advantages that the candidate path set meeting various anatomy and mechanical constraints can be planned in the three-dimensional skeleton model, the path length and the path included angle are calculated according to the candidate path set, the screw channel is drawn based on the path information, and the accuracy and safety of surgical planning are improved.

The invention discloses an artificial intelligence-assisted standard artificial temporomandibular joint automatic placement method. The method comprises the following steps: training a three-dimensional reconstruction model used for extracting a mandible and zygomatic bone zygomatic arch joint prosthesis placement area; based on an improved 3D U-Net neural network, carrying out segmentation extraction on the interested areas of the glenoid fossa and the mandibular branch, and obtaining a space geometric structure for prosthesis installation; the method comprises the following steps: extracting outer bone surface point cloud data of a zygomatic arch and a mandibular ramus on the basis of a space geometric structure of prosthesis installation, identifying anatomical key points, and generating a standard prosthesis fitting surface through geometric fitting and constrained optimization; determining the relative position relation between the maxillary joint fossa prosthesis and the mandibular branch prosthesis, and determining the installation direction, the hole position definition and the assembly reference point; and determining a contact area, a posture direction and a placement position of the prosthesis, and completing three-dimensional positioning and posture matching of the prosthesis in the patient model as a surgical planning scheme.

A personalized fixation system includes a surgical planning software tool configured to adjust relationships of relevant anatomy of a subject, at least one bone anchor, a plate having a shape that does not conform to a single plane, the plate configured to accept the at least one bone anchor, wherein the shape of the plate is at least partially determined by the surgical planning software tool, and wherein the plate includes at least one node having a hole configured to receive the at least one bone anchor, and a locking element configured to connect the at least one bone anchor to the plate, wherein the plate is manufactured using additive manufacturing.

The invention relates to the technical field of operation planning, in particular to an adaptive drainage basin segmentation and operation planning system based on deep learning, which comprises a chest imaging data modal layer used for acquiring chest imaging data modal information including lung lobes, lung segment boundaries and lung blood vessels; the end-to-end multi-task deep learning model layer is in communication connection with the chest imaging data modal layer and comprises a blood vessel segmentation module used for performing blood vessel segmentation on the chest imaging data modal; the hierarchical drainage basin segmentation module is used for carrying out hierarchical drainage basin segmentation based on the blood vessel segmentation result; the topological basin network module is used for analyzing the topological relation of the vascular structure; the drainage basin visualization module is used for generating visualization results of lung lobes and lung segments; the path planning module is used for generating an operation scheme; the evaluation and decision-making module is used for carrying out evaluation and decision-making analysis on the operation scheme; according to the invention, full-process automatic processing from medical image input to surgical scheme output is realized.

The invention proposes a thoracic surgery intelligent planning system based on multi-modal image fusion, and relates to the technical field of surgery planning, and the system comprises an image processing module which is used for receiving multi-modal medical image data, carrying out the preprocessing and cross-modal registration of the medical image data, and generating fused image data; the three-dimensional reconstruction module is used for segmenting the key anatomical structure in the thoracic cavity based on the fused image data and constructing a three-dimensional model; the operation planning module is used for generating a candidate operation path scheme according to a multi-objective optimization algorithm based on the three-dimensional model; the interaction adjustment module is used for determining a final operation path scheme and updating a risk assessment result in real time; and the report generation module is used for generating a surgical planning report. The method can solve the problems that the existing multi-modal image registration precision is insufficient, the sensitivity of three-dimensional reconstruction to a tiny anatomical structure is low, and the surgical path planning is lack of dynamic risk assessment and real-time interaction adjustment capability, and realizes the generation and optimization of a high-precision and high-safety thoracic surgery planning scheme.

The invention provides a dynamic simulation model construction algorithm for implanting a crystalline lens MPL in the ophthalmology department, and relates to the technical field of dynamic simulation models.The dynamic simulation model construction algorithm comprises the steps that microscopic dynamic data of the crystalline lens in the eye are collected in real time through a nanoscale microsensor array, and the crystalline lens micro-deformation degree (CTMD) and the interaction force (CTIS) of the crystalline lens and an intraocular structure are calculated; the collected microscopic data is transmitted to a central processing unit and is efficiently processed by a high-frequency data processing module; calculating the three-dimensional deformation and focal length change of the crystalline lens in real time based on a multi-physics field coupling algorithm in combination with a physics model; a highly dynamic simulation model is generated through the central processing unit to simulate the performance of the implanted MPL and optimize the surgical planning and design. According to the method, the precision and adaptability of the dynamic simulation model of the implanted crystalline lens MPL in the ophthalmology department can be effectively improved, and more accurate simulation and support are provided for ophthalmology operations.

The invention relates to an oral implant positioning method and system based on deep learning. According to the method, three-dimensional point cloud data of an oral cavity is obtained and preprocessed, and a pre-trained three-dimensional deep learning segmentation model is utilized to automatically and accurately segment tooth, gingiva and alveolar bone structures. And based on the segmentation result, extracting key form and spatial relationship characteristics of the alveolar bone, and matching with an implant database to primarily select a candidate scheme. By integrating geometric constraint verification and biomechanical simulation, the candidate schemes are optimized and decided, and the optimal implant implantation position and posture meeting the safety and biomechanical requirements are calculated. And finally, automatically generating digital operation guide plate data completely matched with the gingival form of the patient according to the optimal scheme. According to the method, automation and intellectualization of the whole process from data collection to surgical guide plate generation are achieved, the defects that a traditional method depends on artificial experience, is high in subjectivity and low in efficiency are effectively overcome, and the precision, efficiency and reliability of implantation surgical planning are remarkably improved.

A surgical planning system is disclosed which provides computer assisted navigation for spinal surgery. The surgical planning system includes a computer platform operative to obtain images of at least two different postures of a patient's spine, and to measure displacement of anatomical features of the patient's spine between the images of the at least two different postures of the patient's spine. The computer platform is further operative to estimate stiffness of the patient's spine based on the measurements of displacement, and to generate a patient-specific kinematic model of the patient's spine based on the estimated stiffness, and provides a surgical plan based on the patient-specific kinematic model of the patient's spine.

The invention relates to the technical field of liver surgery, and discloses a liver surgery planning system based on data fusion. The system comprises an image data fusion module, a three-dimensional model construction module, an operation path planning module, a risk assessment module and a scheme optimization module. The image data fusion module integrates CT and MRI images to generate a standardized image fusion model; a three-dimensional model building module generates a liver three-dimensional visual model according to the three-dimensional model; the operation path planning module plans an optimal resection path to form a preliminary operation path scheme; the risk assessment module assesses the surgical risk and generates a report; the scheme optimization module generates a final surgical planning scheme based on the report adjustment parameters. According to the system, through the multi-source data fusion and three-dimensional visualization technology, the liver structure and the tumor position are accurately presented, the operation path is scientifically planned, the operation risk is evaluated and avoided, the operation scheme is optimized, and accurate implementation of the liver operation is assisted.

The invention discloses a liver and gall part segmentation method and device based on deep learning, equipment and a medium, and belongs to the technical field of artificial intelligence. In the embodiment of the invention, the three deep learning models are used to carry out three-stage image segmentation on the original image containing the liver and gall part, and the position of each human tissue structure of the liver and gall part in the medical image is automatically identified and segmented. Surgical navigation is provided for clinicians during hepatobiliary disease and surgical planning, the deep learning technology is applied, the method is more accurate and faster, the method can be suitable for disease diagnosis, surgical formulation and radiotherapy plans of clinicians in more departments, the applicability of the method is improved, and the method has general clinical value and is worthy of popularization and application. The three-stage segmentation module can realize more accurate segmentation, can give consideration to global information and local information, better conforms to the reading habit of clinicians, and improves the segmentation precision and accuracy.

A system for surgical registration. The system may include at least one computing device in communication with a surgical navigation system and the surgical device. The at least one computing device: a) receiving external bone registration data corresponding to locations on the exterior surface of the femur; b) calculating a first registration transform based on the external bone registration data; c) transforming a first bone removal plan of a surgical plan to the operative coordinate system based on the first registration transform; d) receiving internal bone canal registration data corresponding to at least one of location or orientation data from the inner canal of the femur; e) calculating a second registration transform based on both of the external and internal bone canal bone registration data; and f) transforming a second bone removal plan of the surgical plan to the operative coordinate system based on the second registration transform.

The embodiment of the invention is suitable for the technical field of computer-aided medical treatment and surgical planning, and provides a single-condyle surgical prosthesis planning method and device and computer device.The method comprises the steps that parameter information of a prosthesis to be planned is obtained, and the parameter information comprises the osteotomy amount; according to the parameter information, determining a placement position of the prosthesis in a pre-constructed three-dimensional model; calculating a coverage rate between a prosthesis section and a corresponding bone section in the three-dimensional model when the prosthesis is located at the placement position; according to the coverage rate, a target prosthesis is determined from the multiple to-be-planned prostheses, and preoperative planning of the unicompartmental condyle operation is carried out based on the target prosthesis. By the adoption of the method, the posture of the prosthesis can be automatically planned according to the osteotomy amount of the prosthesis, then the optimal prosthesis is selected for preoperative planning through calculation of the coverage rate of the section of the prosthesis, and the precision and safety of single-condyle surgery prosthesis planning are guaranteed.

Planning cardiac surgery is a complex task. Current heart models are mostly static and provide no functional information or personalization apart from structural information from imaging modalities like MRI, CT etc. The embodiments of present disclosure addresses unresolved problem of generating a personalized four dimensional cardiac model that integrates blood flow velocity, pressure profile and volume on three-dimensional cardiac structure, providing a comprehensive tool for pre or post-surgical planning and analysis. Unlike existing techniques, which often rely on separate assessments of cardiac anatomy and hemodynamics, using invasive methods, the present disclosure provides a 4D cardiac model that captures the person specific dynamic interaction between cardiac structures and blood flow throughout the cardiac cycle. Further, the 4D cardiac model enables clinicians to visualize and quantify complex flow patterns and pressure distributions within the region of interest in the heart, facilitating precise surgical planning and outcome prediction especially in pediatric heart surgery.

The invention discloses a medical image artifact identification and elimination method based on a big data technology, and relates to the technical field of medical image processing, and the method comprises the steps: carrying out the preprocessing of collected image data based on gray normalization, and then carrying out the semantic segmentation and ROI positioning of the image content; and performing lesion segmentation on the positioned image content, selecting lesion features for quantification and fusion, performing model verification, and performing distributed deployment on the verified lesion segmentation model. According to the method, the problems of high missed detection rate of small nodules and high missed diagnosis risk of malignant lesions are solved through the lesion detection model, the false positive rate is reduced, the recall rate of the malignant lesions is improved, and through the lesion segmentation model, the segmentation adaptability to lesions of different sizes is improved, clear segmentation boundaries are obtained, surgical planning is assisted, and boundary positioning errors are reduced.

The invention provides a percutaneous puncture accurate dynamic matching and navigation method and system based on an AI surgical robot, and the method comprises the steps: obtaining a preoperative medical image, and generating surgical planning data based on the medical image; determining an ablation path and an ablation area according to the surgical planning data; puncture operation is executed through the robot system, and ablation treatment of the target area is completed; the step S3 further comprises the steps of obtaining real-time image data in the operation for multiple times, and dynamically adjusting the ablation path and the ablation parameters in real time based on the real-time image data in the operation each time. The method comprises the following steps: acquiring and analyzing preoperative and intraoperative medical image data of a patient to generate puncture positioning and navigation puncture schemes in different stages; the purpose of capturing tissue deformation in real time in percutaneous puncture is achieved, the purpose of dynamically optimizing the puncture path is further achieved based on the tissue deformation state captured in real time, the motion trail of the robot is adjusted in real time based on real-time generation of the dynamic puncture path, and therefore the precise navigation and dynamic matching degree of the percutaneous puncture operation is improved, and the accuracy of the percutaneous puncture operation is improved. And the purpose of precise puncture is achieved.

The invention relates to a medical image three-dimensional reconstruction and visual display method and device, equipment and a medium. According to the method, automatic construction from an original medical image to a functional three-dimensional anatomical model is realized in a mode of combining deep learning and a knowledge graph. Firstly, an original image is preprocessed and segmented, function labeling is carried out in combination with an anatomical knowledge graph, then a global structure is optimized through a graph neural network, and finally, a three-dimensional anatomical model is generated by fusing function connection information among tissues. According to the method, the automation degree and accuracy of three-dimensional anatomical modeling are improved, organic combination of anatomical structures and functions is achieved, and powerful support is provided for precise medical treatment and surgical planning.

The embodiment of the invention discloses a brain deep part electrical stimulation operation planning system and method based on a human brain network and a Lead-DBS technology, and the system and method are applied to operation planning of neuropsychiatric diseases. The data preprocessing module is used for denoising, correcting and standardizing the patient data to generate preprocessed data; the brain network model construction module is used for determining a functional connection matrix and a structural connection matrix based on the preprocessed data so as to construct an individualized brain network model; the electrode positioning module is used for generating an implantation target spot of a DBS electrode based on an individualized brain network model; the stimulation parameter optimization module optimizes stimulation parameters of the DBS based on the individualized brain network model and the electrophysiological data; the postoperative evaluation module compares the postoperative image with the preoperative plan to verify the actual implantation position and stimulation effect of the DBS electrode; the dynamic adjustment module is used for dynamically adjusting stimulation parameters.

Methods and systems for guiding interventional surgery are provided. The method includes receiving a plurality of intracardiac echocardiography (ICE) images of a target object acquired during a preset period, analyzing of the plurality of ICE images to obtain image analysis results, and generating an interventional surgical plan based on the image analysis results to guide the interventional surgery. This method conducts image analysis on ICE image before puncture to plan the interventional surgery, thus identifying the optimal puncture angle, depth, and timing for the interventional surgery. The method can help conduct real-time detection and tracking of the puncture process, identifying and mitigating potential risks during the surgical process to improve the success rate of the surgery. Furthermore, continuous assessment and management of possible complications can be carried out through postoperative evaluation to comprehensively reduce the risk of the interventional surgery and enhance its effectiveness and safety.

To provide a program, etc., with which it is possible to present an appropriate surgery plan from medial images in which the affected area of a patient is captured.SOLUTION: The program causes a computer to execute the processing of: acquiring a medical image in which the affected area of a patient is captured; inputting a prompt including the medical image to a language model so as to acquire surgery plan information indicating a surgery plan of surgical operation from the language model; and displaying the surgery plan information on a display unit. Preferably, the surgery plan information is obtained from the language model by acquiring clinical record data of the patient diagnosed by a doctor and inputting the medical image and a prompt including the clinical record data to the language model.SELECTED DRAWING: Figure 5

The invention relates to the technical field of medical positioning, in particular to a spine surgery positioning intelligent guiding system which comprises an image obtaining and processing module, an operation plan and display module, a quantum dot self-adaptive navigation module, a positioning guiding module and a feedback and adjustment module. The image acquisition and processing module is used for acquiring spine image data of a patient and generating a spine three-dimensional model; the operation plan and display module formulates an operation plan based on the spine three-dimensional model; the quantum dot self-adaptive navigation module provides a real-time image and carries out positioning and navigation on a surgical instrument; the positioning and guiding module monitors and guides the position and angle of the surgical instrument in real time; and the feedback and adjustment module feeds back the position and the operation state of the surgical instrument in real time. According to the invention, a clearer real-time image with a higher contrast ratio is provided, so that the accuracy and safety of surgical operation are improved.

The invention discloses an intraocular light field simulation method and system based on physiological constraint and pathology traceability, the system takes a Physics Informed Kolmogorov-Arnold Net (PI-KAN) network as a core, namely physical information KAN, the method comprises the following steps: obtaining personalized parameters of eyeballs; 5-dimensional light field parameters including space, wavelength and time are input into a pre-trained PI-KAN model for light field solving, a three-layer network architecture including an input layer, a hidden layer and an output layer is established, a physical information edge function is constructed, and training is performed through fusion of a Helmholtz equation and a loss function of boundary conditions; generating an OCT image based on the light field solved by simulation; by analyzing side function mapping, visualization and pathological traceability of a light field propagation physical mechanism are realized. According to the method, the sparsity and interpretability of PI-KAN are utilized, the problems that a traditional method is low in calculation efficiency, difficult in high-dimensional modeling, weak in physical constraint and poor in interpretability are solved, millisecond-level, high-precision and interpretable simulation of the eye light field is achieved, and the method is suitable for ophthalmic clinical auxiliary diagnosis, surgical planning and equipment optimization.

The invention discloses a weak supervision orthopaedic three-dimensional reconstruction method based on geometric constraint and comparative learning regularization, and aims to solve the problems of high labeling cost and poor robustness of a weak supervision model in the existing orthopaedic three-dimensional reconstruction technology. According to the method, a coarse threshold segmentation result automatically generated by a Mimics tool is used as a weak supervision label, manual fine adjustment is not needed, and the labeling cost is remarkably reduced. The method comprises the following steps: acquiring and registering a CT sample; generating an enhanced sample through significance guide mixing and random shielding; feature extraction and segmentation prediction are carried out by using the 3DUNet sharing the weight; designing a multi-loss function fusing consistency regularization loss, geometric constraint loss and threshold guide feature comparison loss, and strengthening geometric consistency and feature distinguishing capability; and finally, high-precision and high-generalization skeleton three-dimensional reconstruction is realized through training optimization and reasoning, and the method is suitable for scenes such as clinical diagnosis and surgical planning.

The invention belongs to the technical field of DSA, and discloses a DSA platform-based multi-state real-time multi-mode image accurate fusion method. After an angiography image is collected on the basis of DSA equipment under the motion condition, accurate DSA blood vessel subtraction image enhanced display is achieved, meanwhile, hepatic artery extraction in a three-dimensional image in preoperative CT is completed, dynamic intelligent fusion of a precise anatomical structure in a preoperative multi-mode CT image and intraoperative local blood vessel development is combined, and the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion is achieved. The intrahepatic lesions and important blood vessels are accurately and visually displayed, operation planning is completed, fusion of three-dimensional information and two-dimensional DSA is utilized, and transvascular and percutaneous interventional operations are accurately guided.