150 results about "Surgical planning" patented technology

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 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.

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 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.

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.

An intracranial procedure includes engaging a fiducial device having fiducial markers with a maxillofacial anatomy of a patient, the fiducial device arranged to communicate with a tracking arm arranged to communicate with a robotic arm having a procedure performing device engaged with a distal end of the robotic arm. A virtual surgical plan is prepared in registration with and relative to the fiducial marker for forming an aperture through the skull and into the intracranial region, and for accessing an associated intracranial anatomical structure through the aperture. Movement of the surgical performing device relative to the fiducial marker is physically adjusted via the robotic arm according to the virtual surgical plan and symmetrically with physical manipulation of the surgical performing device during formation of the aperture and during entry into the associated intracranial anatomy. If the physical manipulation of the surgical performing device deviates from the virtual surgical plan, haptic feedback is provided via the surgical performing device.

A computer-assisted surgery system allows a user to control movements of a surgical tool by providing, to a control unit, inputs in the form of measured displacements via a movable part of a handle while treating a region of interest with the tool. The control unit is configured to enable motion of the tool with respect to an anatomical structure only if a user moves the movable part, receive the measured displacement of the movable part, receive from a localization unit the relative position and orientation of the tool relative to the anatomical structure, based on the measured displacement, on the surgical plan and on the relative position and orientation of the tool relative to the anatomical structure, compute an instruction to send to a motorized joint to move a robotic arm to operate the tool according to an optimal trajectory, and send the computed instruction to the motorized joint.

The embodiment of the invention is suitable for the technical field of medical treatment, and provides a joint postoperative simulation image generation method, electronic equipment and a computer program product, and the method comprises the steps: obtaining preoperative data for a to-be-operated joint; determining a correction reference point of the preoperative original CT image; based on a preset skeleton coordinate system and the correction reference point, correcting the preoperative original CT image to obtain a corrected original CT image; based on a preset skeleton coordinate system and the correction reference point, correcting the preoperative skeleton CT image to obtain a corrected skeleton CT image; based on a preset skeleton coordinate system, the correction reference point and the virtual skeleton prosthesis, generating a correction prosthesis CT image; generating a joint postoperative simulation image according to the corrected original CT image, the corrected skeleton CT image and the corrected prosthesis CT image; the joint post-operation simulation image is an X-ray image, the X-ray effect of prosthesis implantation and image correction can be simulated, and a basis is provided for surgical planning and selection of a proper prosthesis and placement position.

Disclosed herein are systems and methods for planning a knee arthroplasty procedure. In one example, a surgical method includes intraoperative measurement of patient anatomical information of the knee and / or movement of the knee of a patient resulting from electrical stimulation of nerves or muscles to cause articulation of the knee. An electrical stimulation system may be attached to a patient to cause contraction / relaxing of muscles operative to cause articulation of the knee. Tracking elements may be associated with relevant knee anatomical structures, such as the proximal tibia, the distal femur, and / or the patella to track the movement of the knee components resulting from the electrical stimulation. Implant components may be selected, positioned, and / or orientated using the tracking information resulting from the electrical stimulation, thereby allowing for determination of a surgical plan based on intraoperative muscle-activated knee articulation, configured to emulate natural patient anatomy and kinematics.

Surgical planning based on a three-dimensional (3D) model includes obtaining a 3D model of an anatomical region, wherein the anatomical region includes the patient's anatomical features; identifying at least one deformity, wherein the at least one deformity is identified with respect to a target anatomical value of the patient's anatomical features, wherein the target anatomical value includes a desired range into which the anatomical measurement should fall; and using the anatomical measurement, determining at least one planar correction to be made to at least one anatomical structure of the patient. Generating a 3D model using two-dimensional (2D) imaging data may include performing anatomical context processing, which includes annotating the model, contours, edges, or surfaces of the anatomical structure, as well as performing 2D-to-3D reconstruction to optimize the orientation, placement, and scale of the 3D digital volume modeling the anatomical structure, resulting in a 3D anatomical representation of the anatomical region as a 3D model.

This application discloses a method and system for microvascular anastomosis modeling and effect prediction in assisted spermatic cord anastomosis, relating to the field of data processing technology. The method includes: extracting the pampiniform plexus topology and varicose vein segments from a three-dimensional vascular tree model of the spermatic veins constructed based on spermatic cord vessel images; determining candidate diversion inlet locations based on the spatial adjacency relationship between the obstructed reflux nodes identified by the varicose vein segments and the pampiniform plexus topology; spatially registering the contour of the inferior epigastric vein segmented from the superficial vein images of the inguinal region with the candidate diversion inlet locations to generate a diversion anastomosis path planning map; constructing the geometric configuration of the end-to-side anastomosis and performing hemodynamic simulation to generate a wall shear stress distribution field, assess the thrombosis tendency of the end-to-side anastomosis, and generate a postoperative patency rate prediction value. This application can predict the risk of thrombosis preoperatively through hemodynamic simulation, providing a reliable basis for surgical planning and effectively improving the success rate of the surgery.

Systems and methods for surgical guidance and image registration are provided, in which three-dimensional image data associated with an object or patient is registered to topological image data obtained using a surface topology imaging device. The surface topology imaging device may be rigidly attached to an optical position measurement system that also tracks fiducial markers on a movable instrument. The instrument may be registered to the topological image data, such that the topological image data and the movable instrument are registered to the three-dimensional image data. The three-dimensional image data may be CT or MRI data associated with a patient. The system may also co-register images pertaining to a surgical plan with the three-dimensional image data. In another aspect, the surface topology imaging device may be configured to directly track fiducial markers on a movable instrument. The fiducial markers may be tracked according to surface texture.

A system and method for registering and tracking anatomical structures during surgical procedures by leveraging continuously updated 3D topological data of objects within the surgical field. Registration allows different datasets such as preoperative CT scans and intraoperative 3D scans to be aligned, combined, and transformed into a common coordinate space, enabling more precise surgical planning and execution. Tracking involves continuously registering these datasets over time, monitoring changes in position or orientation, and keeping objects aligned within the common coordinate space, updating the spatial alignment of registered objects multiple times per second, which allows for dynamic monitoring of anatomical structures and surgical tools as they move throughout the procedure. Unlike traditional systems that rely on physical optical markers (OMs) and optical tracker constellations (OTCs), the system and method disclosed herein utilizes the data captured by a 3D scanner to perform Continuous Anatomic Auto Tracking (CAAT).

A surgical planning and assessment system is disclosed. The system may include a computing system having a processor, a data store, and a patient specific planning and analysis module. The system may be configured to store a patient specific target plan including a digital representation of a spinal rod having a target geometry and transform the digital representation into a curved line. The system may generate a spline data set comprising a plurality of spline segments that are sequentially linked to one another. The system may adjust, iteratively, each spline segment until the plurality of spline segments approximate the curved line. The system may generate a digital file comprising drawings for manufacturing a spinal rod based on the plurality of spline segments. In various embodiments, each spline segment may be defined by a corresponding arc or a corresponding line extending between a corresponding starting point and a corresponding ending point.

The application provides an aorta morphological feature automatic measurement and clinical auxiliary decision-making method and system based on artificial intelligence, which is suitable for three-dimensional medical image analysis of aorta and its main branches. The method comprises the following steps: image data acquisition and preprocessing, automatic blood vessel structure segmentation, center line extraction and key point positioning, multi-parameter automatic measurement, risk assessment and clinical auxiliary decision-making, data standardization output and system feedback optimization. The corresponding system comprises an image acquisition and processing module, a segmentation module, a center line extraction module, a parameter measurement module, an auxiliary decision-making module, a data output module and a verification and optimization module. Through a deep learning model and morphological calculation means, efficient identification and quantitative analysis of blood vessel structure are realized, and individualized risk suggestions and surgical planning are output based on statistical and machine learning models. The application improves the automation, standardization and intelligence level of blood vessel analysis, and enhances the clinical auxiliary decision-making ability under complex cases.

The invention relates to the technical field of surgical planning, in particular to a kidney tumor accurate resection path planning method and system based on three-dimensional modeling, and the method comprises the following steps: obtaining a kidney tissue tumor surface area, extracting a line segment towards a renal gate direction, extending a direction vector, constructing a passing guide line, and continuing a path to a compression direction; extracting a blood vessel crossing path section, dividing an interference area, adjusting the direction of a turning section, connecting a tumor and a renal gate, and generating a resection path planning result set. According to the method, by constructing a direction line segment set extending along a structure compression trend, advancing a path space trend segment by segment, combining a replacement mechanism of regions with inconsistent directions, depending on density division of crossing edge point segments, defining the distribution position of a traffic limited region, adjusting repeated turning segments through direction lines, and eliminating path fluctuation and turn-back interference, the traffic limited region is determined. The extending direction penetrates through the tumor center and is connected with the starting point path, the path track integrally keeps smooth extension, the space layout is more ordered, and the matching performance of the passing line segment structure is enhanced.

The embodiment of the invention discloses a three-dimensional myocardial scar visualization system. According to one specific embodiment, the system comprises a data processing end configured to perform heart structure and scar segmentation on target heart magnetic resonance data to obtain a binary tag graph for the heart and the myocardium; constructing an individualized ventricular network and a scar three-dimensional surface model based on the binary label graph; generating an initial myocardial scar three-dimensional model; generating lead implantation track information; generating a myocardial scar three-dimensional model according to the lead implantation track information; and the model application end is configured to perform model rendering on a target application page according to the model parameters corresponding to the myocardial scar three-dimensional model sent by the data processing end so as to provide an interactive operation function and generate a clinical report. According to the embodiment, accurate and visual three-dimensional visual decision support can be provided for preoperative planning and intraoperative navigation of heart diseases, so that the accuracy of surgical planning and the clinical working efficiency are remarkably improved.

An assisted surgical planning system includes a host computer, a discriminative AI module, a user navigation interface, and a generative AI module. The discriminative AI module is electrically connected to the host computer, and is configured to form plural organ segmentation images based on plural CT images. The user navigation interface is electrically connected to the host computer, and is configured to display the organ segmentation images, an initial needle insertion path, plural suggested needle insertion paths, and a final needle insertion path. The generative AI module is electrically connected to the host computer, such that the host computer connects the user navigation interface to the generative AI module. The generative AI module is configured to generate the suggested needle insertion paths based on the organ segmentation images and the initial needle insertion path, and display the suggested needle insertion paths in the user navigation interface.

This invention relates to the field of medical image processing technology, specifically disclosing a method for automatic 3D reconstruction and printing model generation based on multi-view medical image sequences. The method includes the following steps: acquiring patient medical images and importing them into a method for automatic 3D reconstruction and printing model generation based on multi-view medical image sequences, followed by preliminary verification and processing; connecting a local script and performing sparse reconstruction using COLMAP software; preprocessing the point cloud using statistical filtering and radius filtering to remove outlier noise points and estimate point cloud normals to achieve surface consistency; performing Poisson reconstruction on the cleaned point cloud to generate a 3D mesh, then simplifying the mesh and smoothing the data; and robustly reconstructing a high-precision 3D model, obtaining a printable STL file without manual intervention. This invention facilitates intuitive observation of the three-dimensional morphology of organs or lesions, providing a convenient auxiliary tool for surgical planning and medical teaching.

This invention discloses a medical image segmentation method and system based on local Moran's index residual blocks, belonging to the field of intelligent medical image segmentation technology. By introducing multi-scale local Moran's index features, this invention effectively quantifies the spatial clustering patterns of key anatomical structures in shoulder MRI images, achieving accurate characterization of eight types of structures. A residual Moran's feature module is deeply embedded in the UNet architecture, and spatial feature utilization is enhanced at each level of the encoder-decoder, improving the model's adaptability and generalization ability to complex shoulder anatomy, making the segmentation results more robust and reliable in clinical applications. The constructed segmentation model can achieve end-to-end automatic segmentation of shoulder MRI images without additional spatial statistical preprocessing, offering advantages such as convenient deployment and high computational efficiency. It is suitable for rapid clinical diagnosis and surgical planning, and has significant application value in improving the intelligent diagnosis and treatment of shoulder joint diseases.