235 results about "Surgical planning" patented technology

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.

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.

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 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.

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.

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.

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.

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 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.

A method for visualizing a patient shoulder anatomy is provided. The method includes receiving image data of the patient shoulder anatomy, identifying a boundary of a lesion on a humerus based on the image data, generating one or more 3D models based on a segmentation of the image data, determining a location of a glenoid track corresponding to a contact between the humerus and a glenoid based on the one or more 3D models, generating a first virtual object based on the location of the glenoid track, and displaying: at least a portion of a rendering of the one or more 3D models, the boundary of the lesion, and the first virtual object.

The invention relates to the technical field of medical auxiliary diagnosis, and discloses a hypospadias penis curvature measuring method based on physical simulation inversion. The invention aims to solve the technical pain point that the penile erection curvature and the internal fibrosis focus distribution are difficult to quantify noninvasively and accurately before the operation in the existing hypospadias diagnosis and treatment. According to the method, a standard white mold containing fine anatomical partitions is constructed, personalized geometric mapping is realized by using a static look-around image, and constraint physical parameter inversion is performed in combination with a multi-attitude dynamic stress image, so that the digital twin with real biomechanical properties is reconstructed in a virtual environment. According to the method, the erection bending form can be accurately predicted in the non-erection state, the mechanical property abnormal area range is positioned, operation planning is assisted, experience medical treatment is spanned to accurate digital medical treatment, and the wound diagnosis and treatment and operation risks are remarkably reduced.

The invention discloses a personalized cerebral aneurysm rupture risk assessment and operation planning system, and relates to the technical field of cerebral aneurysm treatment. The three-dimensional reconstruction module assists a doctor in performing surgical path planning and simulation, assists the doctor in performing surgical path planning, simulates different intervention schemes and visualizes adjacent key structures, so that surgical decisions are optimized, operation risks are reduced, and the treatment success rate is improved; the risk assessment module integrates the rupture probability data and the key morphological parameters, generates a personalized risk assessment report, and provides operation intervention priority suggestions in combination with clinical guidelines so as to enhance the personalized accuracy of assessment; the operation planning simulator simulates an operation process, provides an interactive virtual environment, provides a multi-scheme comparison function, allows a doctor to test various intervention strategies in the virtual environment, and automatically generates a structured operation scheme report for direct calling of the decision support module, thereby realizing whole-process closed-loop optimization.

The invention relates to the technical field of medical image processing and three-dimensional reconstruction, and particularly discloses a reconstruction and analogue simulation method based on a cardiac image. The method comprises the following steps: firstly, preprocessing an input CT or MRI medical image, and automatically segmenting a heart multi-tissue structure by using an nnUNetv2 model, including a plurality of anatomical regions such as atrium, ventricle, myocardial tissue and blood pool; and then performing topology repair, smoothing processing and label resampling on the segmentation result to obtain a three-dimensional label body with a continuous structure and a complete boundary. And based on the optimized tag body, constructing a heart three-dimensional surface model by adopting a Marching Cubes algorithm, and generating a multi-material volume grid suitable for finite element analysis. According to an electrode position and a radio frequency parameter set by a user, a radio frequency ablation simulation model based on a Pennes biological heat conduction equation and an Arrhenius model is established, a temperature field and a tissue thermal damage range are calculated, and a simulation result is displayed in a three-dimensional mode in an overlapping mode. According to the method, the integrated process from medical image automatic segmentation to heart three-dimensional reconstruction and thermal simulation is realized, the segmentation precision, the modeling efficiency and the simulation reliability are improved, and the method can be applied to application scenes such as surgical planning, preoperative evaluation and medical teaching.

A system and method for predicting spinal motion and vertebral locations and movement in surgeries through training and using predictive models generated using biomedical profiles of patient spines and surgical patient-specific features. A trained predictive model is used in combination with patient-specific features associated with a surgical patient such that during a real-time surgery the patient-specific features are provided to the trained predictive model and a segmental motion model is created. Using this real-time surgical data and interoperative data, the trained predictive model is updated which then used for updating the segmental motion model such that the updated segmental motion model may be used for producing a series of vertebral location predictions specific to movements and location of the spine of the surgical patient that may be provided to a surgical guidance system for use in performing the real-time surgery in accordance with a surgical plan.

A system for surgical planning and assessment of spinal pathology or spinal deformity correction in a subject, the system comprises a control unit configured to align one or more vertebral bodies of a biomechanical model to one or more vertebral bodies of the radiograph. The control unit is configured to receive one or more spinal correction inputs. The control unit is configured to, based on the received one or more spinal correction inputs, simulate the biomechanical model in a predetermined posture. The control unit is configured to provide for display one or more characteristics of the simulated biomechanical model.

This invention belongs to the field of medical image processing technology, specifically relating to a method for abdominal multi-organ medical image segmentation based on a state-space model. Addressing the shortcomings of existing technologies such as the difficulty of CNNs in modeling long-distance dependencies, the high computational complexity of Transformers, and the large semantic gaps, incomplete segmentation contours, and easy organ encroachment issues in VM-UNet skip connections, this solution makes key improvements: It constructs an improved VM-UNet-Skip architecture, placing skip connections before downsampling to reduce the semantic gap between the small decoder features; it introduces a multi-scale global-local information aggregation module, capturing global anatomical dependencies through multi-head Mamba units and enhancing local detail representations with a convolutional gated feedforward network; and it relies on the VMamba encoder-decoder to achieve efficient feature extraction and reconstruction. The method flow includes: constructing initial feature representations through patch embedding layers, extracting multi-scale hierarchical features through the encoder, enhancing features through an information fusion module, and fusing and mapping the enhanced features to obtain the segmentation result through the decoder. This invention effectively improves the segmentation accuracy of abdominal multi-organs, solves the problems of insufficient contour integrity and organ encroachment, while reducing the number of model parameters and computational complexity, providing reliable technical support for clinical diagnosis and surgical planning.

The invention discloses a respiratory movement tracking method and system, computer equipment and a medium thereof, which are applied to the technical field of medical treatment, and the method comprises the following steps: inputting a CT image sequence into a network model pre-constructed based on a conditional diffusion model, identifying the morphological change of a target area along with respiration, and generating a sequential deformation field changing along with respiration; selecting representative tracking points such as organ edge special position points and focus area center points from a target area, tracing position information at different moments according to a time sequence deformation field, calculating displacement and forming a displacement track; irrelevant frequency interference in displacement track data is filtered out through a band-pass filtering technology, breathing movement related signals are highlighted, phase information is extracted through Hilbert transform, a breathing movement curve is drawn, visual presentation and tracking of breathing movement are achieved, doctors can be helped to more accurately grasp the breathing law of a patient, and the accuracy of breathing movement tracking is improved. Errors caused by respiratory movement are avoided in advance in surgical planning.

The present invention provides a deep learning-based automated planning method and system for simulated knee joint surgery. The method comprises: acquiring a medical image of the knee joint and converting pixels in the image into actual lengths; selecting key area images of the knee joint image, performing target detection on the key area images, and extracting key points; using the coordinates of the extracted key points, annotating the key points and force lines, calculating the correction angle, and then calculating the rotation angle, simulating bone cutting and rotation to obtain a surgical planning image, and automatically planning two types of surgeries: high tibial osteotomy and distal femoral osteotomy. The present invention uses deep learning technology to predict the locations of key points and calculate the angles of force lines in lower limb X-rays. The surgeon can select from eight surgical options based on the displayed angles. The system automatically plans and simulates the options, eliminating the need for manual operation and significantly improving work efficiency.

The present application relates to a method for extracting an acetabular facies lunata model, in particular to a method for extracting an acetabular facies lunata model based on mixed surface fitting, which solves the technical problem of low precision and robustness of the existing method for extracting an acetabular facies lunata model. The present application realizes rough extraction of the acetabular facies lunata model through spherical surface fitting, and then realizes accurate extraction of the acetabular facies lunata model in combination with ellipsoidal surface fitting, which combines the stability of spherical surface fitting and the anatomical fidelity of ellipsoidal surface fitting. In particular, in the case of complex pathologies such as hip dysplasia, the present application can still maintain high extraction accuracy, and improve the accuracy and reliability of clinical diagnosis and surgical planning. Meanwhile, in the iteration process of ellipsoidal surface fitting, an adaptive fault tolerance threshold is introduced, which effectively solves the problems of sensitivity to noise and strong parameter dependence of traditional methods, and has better robustness in processing complex acetabular morphology.

A surgical robotic system for executing a bone implant surgical plan—includes a surgical robot. The surgical robot includes a first robotic arm for manipulating a surgical tool during a surgical procedure at a surgical site. A control unit of the surgical robotic system includes a processor programmed to direct the surgical robot to position the surgical tool. The processor program includes instructions for executing an act of defining the location of the surgical tool with respect to the surgical site. The processor program also includes instructions for executing further acts of moving the surgical tool to a bone located within the surgical site, the location of which being predefined within the surgical plan, and of marking the bone with the surgical tool, the marking corresponding to the position of a bone implant to be implanted in the bone according to the surgical plan.

This application discloses a method and electronic device for predicting intraocular lens (IOL) selection and rotation implantation, relating to the field of computer technology. This application acquires the user's ocular biological measurement parameters and constructs an intraocular geometric constraint region. The IOL is abstracted as a rectangular geometries, generating a set of candidate size-axis positions. Each candidate option satisfies the geometric constraints of the patient's intraocular anatomy in terms of implantation position and rotation angle. Based on this, by combining the geometric fit indices of the candidate options with individualized ocular biological parameters, the postoperative arch height, the probability of abnormal arch height, and postoperative refractive results are predicted. After post-processing and calibration, outputs with confidence intervals or risk probabilities are provided. This eliminates reliance on experience or rough estimates for surgical planning, effectively reducing the risk of arch height deviation or postoperative refractive errors, providing the optimal IOL option, and achieving individualized, quantifiable, and predictable implantation planning.

The present disclosure provides a force control method, device, equipment and medium of a mechanical arm end power tool. The method comprises: determining the relative position relationship of the power tool end coordinate system in the surgical planning plane area coordinate system at the current moment based on the visual signal information and the current moment mechanical arm pose information; acquiring the force signal when the power tool is subjected to external force, and converting the force signal into the end force signal in the power tool end coordinate system; determining the position control amount corresponding to the power tool end based on the end force signal and the relative position relationship; judging the boundary of the position coordinate of the power tool end at the next moment according to the position control amount and the virtual boundary corresponding to the surgical planning plane area, and adjusting the position control amount according to the judgment result. The present disclosure improves the accuracy of surgical operation, shortens the operation time and reduces the operation risk.

A method comprises outputting a user interface of a surgical planning system, wherein the user interface represents a patient-specific glenoid prosthesis at a planned implantation position on a scapula of a patient; and determining a bone-facing surface of the patient-specific glenoid prosthesis having a native-facing portion and a modified-facing portion, wherein the native-facing portion is shaped to conform to an unmodified bone surface of the scapula and the modified-facing portion is shaped to conform to a modified bone surface of the scapula.