207 results about "Preoperative 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 provides a unicompartmental knee arthroplasty robot navigation and positioning system and method. The system comprises a preoperative planning module, a positioning and navigation module and a mechanical arm control module. The preoperative planning module is used for carrying out knee joint segmentation and reconstruction according to the obtained knee joint medical image, carrying out preoperative planning and determining a unicompartmental knee arthroplasty scheme; the positioning navigation module is used for registering the intraoperative solid knee joint and the preoperative knee joint three-dimensional model according to the navigator and the tracer, and tracking the poses of the osteotomy tool and the solid knee joint in real time; and the mechanical arm control module is used for planning a motion path of the mechanical arm and controlling the mechanical arm to execute the motion path. In this way, the mechanical arm can be controlled to assist in completing the osteotomy operation of unicompartmental knee arthroplasty in a preoperative planning and intraoperative optical navigation mode, and the problems that the operation level is uneven and the operation effect is not expected due to different individuals in the current manual operation are solved.

The invention relates to a myocardial resection area determination method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a heart scanning image, and determining a heart three-dimensional model according to the heart scanning image; determining a heart short-axis section and a heart long-axis section according to the heart three-dimensional model; the clock direction angle of the scalpel is determined on the short axis section of the heart; based on the clock direction angle, the excision depth of the scalpel is determined on the long-axis section of the heart; and performing myocardial resection on the heart three-dimensional model according to the clock direction angle and the resection depth through a scalpel model, determining an updated three-dimensional model after myocardial resection, and marking a resection area on the updated three-dimensional model. According to the scheme, accurate preoperative planning guidance and comprehensive heart structure information presentation are provided for the myocardial rotary cutting operation, and therefore the accuracy and safety of the myocardial rotary cutting operation are improved.

The invention provides an implant immediate denture precise manufacturing system based on preoperative planning and three-dimensional registration. An example method includes obtaining first oral data, the first oral data including three-dimensional data of a denture model and three-dimensional data of a marker; acquiring second oral cavity data, wherein the second oral cavity data comprises scanning data of a plurality of bases fixed in the oral cavity and a marker; registering the first scanning data and the second scanning data based on the matching of the three-dimensional data of the marker and the scanning data of the marker; a denture model to be processed is generated based on a result of the registration, the denture model to be processed comprising three-dimensional data of the denture model and positioning information of a plurality of holes, each hole being for accommodating one of the plurality of abutment. According to the embodiment of the invention, the accurate positioning of the false tooth model and the abutment is realized by using a digital technology, the accurate matching of the false tooth and the abutment is ensured, and the comfort and experience of a dental implant patient are improved.

Systems and methods for fully automated anatomical analysis of an anatomical structure are provided to facilitate pre-operative planning. The computerized method may include obtaining a plurality of images, e.g., MSCT images, of patient-specific cardiovascular anatomy, and analyzing the MSCT images with a trained artificial intelligence module to identify one or more anatomical landmarks and to construct a virtual three-dimensional model of the anatomical structure. For example, the trained artificial intelligence module may execute segmentation, point detection, curve detection, or plane detection deep learning modules, independently or in combination, to identify the anatomical landmarks. The method further may include deriving anatomical measurements of the one or more identified anatomical landmarks, and displaying the virtual three-dimensional model alongside the anatomical measurements of the one or more identified anatomical landmarks.

The invention discloses a medical image intelligent diagnosis and three-dimensional visualization interaction method and system based on artificial intelligence and Unreal Engine. The system is composed of a data acquisition module, an artificial intelligence analysis module, a three-dimensional reconstruction module, a rendering interaction module and a report generation module. The method comprises the following steps: firstly, carrying out voxel normalization on a DICOM / NIfTI image; the improved 3D U-Net is combined with CBAM attention and WGAN-GP training, and a focus initial density field is output; an AI enhanced implicit voxel reconstruction (AEIVR) algorithm is proposed, an enhanced density field is generated by using position coding + MLP, and grid extraction is completed by using improved Marking Cubes of a dynamic threshold; high-fidelity real-time rendering is realized in combination with a Nand micro polygon and Lumen global illumination in Unreal Engine, and VR / AR interaction and virtual surgery (real-time updating of resection mask driving) are supported. According to the method, the problems of large artifacts and insufficient interactivity and real-time performance of existing two-dimensional output and three-dimensional reconstruction are solved, and the end-to-end segmentation-reconstruction-rendering-interaction-reporting process is realized. On typical CT / MRI data, the segmentation Dice is about 0.90-0.94, the reconstruction voxel resolution is 0.1-0.5 mm, the artifacts are reduced by about 20%-30%, the PSNR is improved by about 3-7 dB, and the rendering interaction delay lt is achieved; the system is suitable for scenes such as lung CT, brain MRI, orthopaedic X-ray and cardiac ultrasound, and can be expanded to preoperative planning, remote consultation and teaching.

Disclosed herein is a system and method for performing pre-operative planning of total joint arthroplasty. The planning tool builds a model and analyzes and visualizes movement of the joint for various selections of implant models and placement of the components on the implants on the patient's anatomy. The tool also analyzes and visualizes motions of the joint during common activities of daily living and analyzes and functional ranges. The tool provides real time clinically relevant parameters to inform pre-surgery planning. The tool provides screw orientation visualization.

The invention relates to the technical field of edge segmentation, in particular to a tumor interventional therapy preoperative planning system based on artificial intelligence image recognition, and the method comprises the steps: preliminarily screening out an infiltration edge region based on the gray distribution asymmetry condition of a sliding window in a CT image and the texture disorder condition in an MRI image; further fusing DSA blood vessel data, and screening a concerned infiltration region by analyzing the position distribution condition of the blood vessel region of the infiltration edge region; analyzing curvature mutation conditions of the tumor associated blood vessel segments on the basis of the concerned infiltration region to generate a blood vessel anomaly index; and finally, fusing the infiltration index and the blood vessel characteristics to construct a blood vessel-infiltration coupling index, and correcting the edge strength map according to the blood vessel-infiltration coupling index, so that the boundary optimization based on risk classification is realized, the accuracy of the obtained tumor region edge structure curve is higher, and the accuracy of tumor region segmentation according to the tumor region edge structure curve is improved.

The invention relates to the technical field related to ultrasonic detection, in particular to a method and a device for acquiring an angle of a transesophageal ultrasonic image in a preoperative CT image guidance operation. The method comprises the following steps: acquiring a heart and esophagus cutting model based on a CT image; the heart and esophagus cutting model comprises a heart model and an esophagus model; determining a long-axis section of the heart based on the heart model; determining an esophagus center line based on the esophagus model; selecting a point closest to the long-axis tangent plane in the central line of the esophagus as an ultrasonic irradiation position; the long-axis section of the heart is corrected based on the ultrasonic irradiation position, so that the long-axis section passes through the ultrasonic irradiation position, and the corrected long-axis section is obtained; and determining the angle of the ultrasonic probe based on the corrected long-axis tangent plane and the tangent plane of the esophageal center line at the ultrasonic irradiation position. By means of the arrangement, a doctor can obtain the intraoperative ultrasonic irradiation angle during preoperative planning, and the operation is more accurate and normative.

A multi-module collaborative real-time decision planning system for a surgical robot comprises eight modules including a data acquisition and processing module, a system modeling module, a preoperative planning module, a neural network module, a decision planning module, an execution control module, an autonomous obstacle avoidance module and an autonomous evaluation module. The system obtains robot state and operation environment information in real time through multiple sensors, and constructs an operation environment and motion model; the inverse kinematics is solved by using a neural network, and the multi-solution problem of the inverse kinematics is solved; the preoperative planning module identifies key points and generates an initial path, the decision planning module dynamically adjusts the path in combination with joint constraints, and the execution control module controls the robot to act in a closed-loop mode according to instructions and corrects the relation between force and current in real time; the autonomous obstacle avoidance module monitors the current of a driving motor to realize collision detection and path adjustment; and the autonomous evaluation module continuously evaluates the operation quality through a reward function and feeds back optimization. The system can significantly improve the real-time performance, precision and safety of the surgical robot in a complex environment, and is suitable for the fields of medical treatment, industry, space exploration and the like.

The invention discloses a hypertrophic cardiomyopathy (HCM) preoperative planning and operation effect evaluation method based on accurate digital labeling. The method comprises the following steps: performing digital labeling on the thickness of each wall of a left ventricle of a preoperative heart 3D digital model; according to the digital labeling result of the preoperative heart 3D digital model and the normal value of the thickness of the left ventricular wall, a doctor manually depicts the predicted resection range and confirms the predicted retention thickness; measuring the predicted resection volume, the predicted resection area and the left ventricular end diastolic volume after the predicted resection volume is resected; digitally marking the thickness of each wall of the left ventricle of the postoperative heart 3D digital model, and measuring the volume of the corresponding left ventricle in the end diastole; and taking the predicted resection range, the predicted retention thickness, the predicted resection volume, the predicted resection area and the predicted volume as first evaluation data, taking corresponding parameters of the postoperative heart 3D digital model as second evaluation data, and generating an operation evaluation result according to the conformity of the first evaluation data and the second evaluation data.

The invention discloses a control method and device of a surgical robot, a storage medium and electronic equipment. The method comprises the following steps: determining a plurality of simulated osteotomy surfaces of a target object according to a preoperative plan of knee joint replacement; under each simulated osteotomy surface, calculating a working space of the surgical robot to obtain a plurality of first working spaces; and determining a target working space of the surgical robot according to the plurality of first working spaces, and controlling the surgical robot to execute actions based on the target working space. By means of the method and device, the problem that in the prior art, due to kinematics constraint, an under-degree-of-freedom surgical robot cannot be adjusted to all necessary operation postures, and the accuracy of surgical robot control is low is solved.

The invention provides a preoperative planning method, device and equipment for ankle joint replacement and a computer readable storage medium. The preoperative planning method for ankle joint replacement is applied to an orthopedic surgery robot system, and the preoperative planning method for ankle joint replacement comprises the following steps: acquiring an ankle joint CT image of a patient; carrying out segmentation and three-dimensional reconstruction on the CT image of the ankle joint to obtain an ankle joint three-dimensional model; on the basis of the three-dimensional model of the ankle joint, key parameters of the ankle joint are determined, and an ankle joint prosthesis model is determined on the basis of the key parameters of the ankle joint; determining a preoperative planning method for ankle joint replacement based on the ankle joint key parameters and the ankle joint prosthesis model; wherein the preoperative planning scheme comprises a placement position and a placement angle of the ankle joint prosthesis model.

Provided are a biplanar image-based preoperative planning method and system for total knee arthroplasty. Based on a static biplanar lower-limb image of a knee joint of a target object in a standing position and a dynamic biplanar image of the knee joint during functional motion, as well as an imported three-dimensional model, functional parameters, morphological parameters, and a three-dimensional medial and lateral joint gap of the knee joint are calculated, and then iterative calculation is continuously carried out using a two-dimensional model and a three-dimensional dynamic model to obtain a dynamically optimized placement position, so that preoperative TKA prosthesis model selection for balanced joint space across full flexion angles can be achieved; meanwhile, TKA prosthesis position planning for correcting the mechanical axis of the knee joint under three-dimensional weight-bearing conditions is considered, thereby accurately restoring the real dynamic motion of a patient, and improving the prosthesis-patient matching degree.

The invention discloses an artificial cochlea implantation automatic path planning method based on multi-objective optimization, and relates to the technical field of medicine, and the method comprises the steps: S1, key structure segmentation; s2, generating a candidate path; s3, performing path evaluation; and S4, solving an optimization problem: solving a multi-objective optimization problem by using a genetic algorithm, defining a fitness function and integrating a plurality of objectives, the optimization objectives including minimizing path length, minimizing deviation with an ideal bone surface angle, minimizing bone grinding distance and maximizing the shortest distance with a key structure. According to the artificial cochlea implantation automatic path planning method based on multi-objective optimization, a key anatomical structure is segmented through deep learning, a candidate path set from mastoid to a niche is generated, a multi-objective optimization problem is solved by using a genetic algorithm, and an optimal path meeting clinical constraints is selected. When the method is applied to preoperative planning of an artificial cochlea implantation operation, the safety and accuracy of the operation can be remarkably improved.

According to an aspect, a preoperative planning method for a high-tibial knee osteotomy procedure is provided. The method includes: a) constructing a 3D model of a patient's bones; b) analyzing the 3D model to select a desired correction angle to apply to the patient's tibia bone to adjust a mechanical axis thereof; c) determining surgical steps required to apply the desired correction angle to the patient's tibia bone; d) designing a patient-specific guide to guide generic surgical tools in performing the surgical steps, the patient-specific guide being designed to conform to the anatomy of the patient's bones based on the 3D model; and e) manufacturing the patient-specific guide designed in step d). A corresponding kit, system and computer readable medium for performing the method are also provided.

The invention provides a preoperative planning method for ligament reconstruction operation based on multi-modal data. The preoperative planning method of the ligament reconstruction operation based on the multi-modal data comprises the following steps: acquiring joint medical images of multiple modals of an operation site, and performing registration and fusion processing on the acquired joint medical images of multiple modals to obtain a joint medical image multi-modal fusion result; performing segmentation processing according to the joint medical image multi-modal fusion result to obtain a joint segmentation result; performing key point detection according to the joint segmentation result to obtain a key point detection result; according to the key point detection result, a ligament reconstruction preoperative planning scheme is generated.

The present disclosure includes methods (100, 200) for improving surgical accuracy and effectiveness in medical procedures by using an augmented reality system (300). The method (100, 200) involves: generating a preoperative plan in an augmented reality environment by visualizing a holographic representation of a patient's anatomy; recording program data according to the preoperative plan; using the recorded data to update the augmented reality system; and applying the updated system to establish a continuously improved feedback loop. According to the method, by integrating real-time data feedback into the operation process, the accuracy of the operation is improved, the effect of the patient is improved, the program is optimized, and continuous improvement of medical practice is promoted.

The invention discloses a real-time operation process feedback system for a spine endoscopic operation, and the system comprises a preoperative planning module which is used for obtaining a preoperative medical image, and extracting an outer contour of a specific structure from the preoperative medical image; the channel tool module is used for exposing an operation field, and the camera assembly is used for collecting binocular images and RGB images of an operation area in real time; the image registration module is used for reconstructing a three-dimensional surface point cloud of the operation area according to the binocular image of the operation area, and registering the three-dimensional surface point cloud with the outer contour of the specific structure; and the visualization module is used for segmenting the RGB image to obtain the surgical instrument, acquiring a pose relationship between the surgical instrument and the three-dimensional point cloud according to the internal reference of the camera assembly, and rendering the pose relationship to a three-dimensional model. Through the integrated transparent structural design, the working channel and the nerve drag hook are integrated, instrument interference is avoided, nerve protection is visualized in real time, the operation safety is improved, and the operation progress and the nucleus pulposus removal condition can be fed back in real time in the operation process.

This invention provides a method and system for generating simulated laparoscopic robot operation videos, relating to the field of generative artificial intelligence technology. The method includes acquiring a single frame RGB image of the laparoscopic robot's working scene; responding to the instrument dragging path executed by the user on the laparoscopic robot's interactive screen, processing the RGB image using an image segmentation model to obtain an instrument binary mask, and generating an instrument condition sequence based on the instrument binary mask and the instrument dragging path; and processing the RGB image and the instrument condition sequence using a pre-trained video generation model to generate a simulated laparoscopic robot operation video. This application generates a simulated robot operation video by inputting the first frame image and instrument motion conditions, which can be used to simulate potential surgical procedures under different instrument operation strategies and for different target personnel, providing an intuitive reference for preoperative planning, surgical teaching, and risk assessment.

The present application relates to the technical field of medical image processing, and provides a knee femur and tibia segmentation method based on region growing, comprising the following steps: S1, acquiring knee medical images; S2, selecting a growth seed point; S3, coarsely segmenting the knee medical images to obtain knee stem data; S4, finely segmenting the knee medical images to obtain knee connection data; S5, fusing the knee stem data and the knee connection data to obtain knee femur and tibia image data with complete contours; S6, coarsely filling the knee femur and tibia image data to obtain knee femur and tibia image data after coarse filling; and S7, iteratively filling holes in the knee femur and tibia image data by using a three-dimensional sliding window, so as to obtain image data that is consistent with the surrounding data in shape, position and completeness and smoothness. The present application solves the problems of slow segmentation speed, unstable segmentation effect, incomplete segmentation and adhesion in preoperative planning of knee replacement surgery.

The present application provides a total knee arthroplasty robot auxiliary system, a control method, electronic device and a computer readable medium. The auxiliary system comprises: a preoperative planning system configured to formulate a preoperative plan, preoperative plan data including a knee joint image; an intraoperative planning system configured to formulate an intraoperative plan, wherein the knee joint image in the preoperative plan and a knee joint surface contour of the patient determined in an operation are subjected to image registration, knee joint dynamic spacing force line data at a continuous flexion-extension angle is acquired, a dynamic spacing force line data graph is visually displayed, and a prosthesis plan is adjusted according to the visual display of the dynamic spacing force line data graph to obtain the intraoperative plan; and an executing system, wherein a bone-cutting guide mounted at an operating end of a mechanical arm of a surgical robot is guided to be located in a planned predetermined position according to the intraoperative plan, and the bone-cutting guide is configured to locate a bone-cutting saw.

To provide a device, a system, and a method for a preoperative plan and an intraoperative guidance for orthopedic surgery of a fractured joint suffering bone fragmentation.SOLUTION: A surgery system can be configured to acquire image data of a joint including at least a portion of humerus, segment the image data to determine a shape of a diaphysis of the humerus, determine a shape of the humerus before it becomes the estimated pathosis on the basis of the determined shape of the diaphysis, identify one or more bone chips in the image data on the basis of the estimated shape of the humerus, and generate an output on the basis of the bone chips identified in the image data.SELECTED DRAWING: Figure 35

The embodiment of the invention is suitable for the technical field of computer-aided medical treatment and image processing, and provides a method for generating implant postoperative evaluation information and computer equipment, and the method comprises the steps: obtaining comparison image data; extracting spine point cloud from the comparison image data, wherein the spine point cloud comprises first spine point cloud data and second spine point cloud data; performing spine registration by adopting the first spine point cloud data and the second spine point cloud data to obtain a spine registration result; according to the spine registration result, registering an implant in the comparison image data to obtain an implant registration result; based on the spine registration result and the implant registration result, implant postoperative evaluation information is generated. By adopting the method, the difference between the preoperative planning and the postoperative effect can be efficiently and accurately evaluated, the postoperative condition of the implant can be independently evaluated, and the accuracy of the postoperative evaluation of the implant can be improved.

The application discloses an oval foramen automatic detection and fine segmentation method based on an anatomic landmark gravity field and a tubular topology enhancement, and specifically relates to the technical field of medical image processing. Firstly, the head CT or MRI image to be processed is subjected to multi-modal space alignment and adaptive contrast enhancement; subsequently, the image is input into an anatomic landmark gravity field network, macroscopic landmarks of a skull base are extracted, a spatial gravity field matrix is constructed, and the model attention is adaptively focused on a small oval foramen high probability area; then, a multi-view tubular structure enhancement encoder is used to extract features of a three-dimensional hole track of the oval foramen, and the interference of non-penetrating bone depressions is inhibited; finally, a three-dimensional penetrating topology constraint mechanism is introduced in the decoding stage, so that the generated three-dimensional model of the oval foramen has correct anatomic connectivity. The application can effectively solve the detection problem of the oval foramen caused by the large individual variation, the small volume and the easy confusion with surrounding holes and fissures, and significantly improves the preoperative planning accuracy of trigeminal neuralgia puncture and other surgeries.

The application provides a surgical robot system and control method for proximal femur osteotomy, the system comprises: a preoperative planning module for constructing a hip joint three-dimensional model and performing preoperative planning according to the hip joint three-dimensional model to generate a proximal femur osteotomy scheme, which is one of a femoral head rotation osteotomy scheme, a femoral neck rotation osteotomy scheme, an intertrochanteric rotation osteotomy scheme and a subtrochanteric rotation osteotomy scheme; a navigation positioning module for registering the entity femur in operation and the hip joint three-dimensional model before operation according to an optical positioner and an optical positioning frame to map the proximal femur osteotomy scheme, real-time tracking the pose of the surgical tool and the entity femur, and displaying and comparing the proximal femur osteotomy scheme and the real-time osteotomy process on a display screen. In the application, the preoperative planning-intraoperative optical positioning navigation can track the osteotomy condition of the surgical tool in real time during operation, and multiple medical imaging is avoided, thereby greatly improving the surgical effect.

Disclosed are computer visual guidance systems for guiding surgeons through arthroscopic debridement of bony pathologies, including by automatically generating annotations relating to characteristics of bony pathology in an image. The annotation may be generated in accordance with a determination as to whether a femoral head of the bony pathology is endospherical or exospherical. The annotation may be generated in accordance with a mathematical model created based on anatomies of subjects other than the patient. Further disclosed is a user interfaces for guiding a surgeon through arthroscopic debridement of a bony pathology, wherein intraoperative images are displayed simultaneously with a preoperative plan comprising interactive three-dimensional models of an anatomical feature of a patient. Further disclosed is a user interface for guiding a physician in categorizing images of a patient, wherein the interface comprises an image viewing window and an interactive checklist for different image categories to be captured.

The application provides a three-dimensional CT image reconstruction method and system for lumbar disease diagnosis, and belongs to the technical field of three-dimensional medical image reconstruction; a plurality of two-dimensional CT images are acquired to train a deep neural network; a two-dimensional CT image to be segmented is input into the trained deep neural network for segmentation, and the segmented image is used as a pre-reconstruction image; three-dimensional CT image reconstruction is performed on the pre-reconstruction image based on a VTK rendering method, so that the visualization of the three-dimensional CT image is realized. The application can accurately and efficiently simultaneously segment the vertebrae, intervertebral discs and nerve structures in the lumbar CT image, and realizes image visualization through three-dimensional reconstruction of the segmented CT image, thereby providing strong support for lumbar disease diagnosis, preoperative planning and intraoperative guidance.

The application relates to the technical field of orthopedic surgery navigation, and discloses a high-position tibial osteotomy navigation method, a system and a storage medium, and a communication method which comprises the following steps: generating a 3D bone model of a lower limb of a patient based on medical images and performing preoperative osteotomy planning; performing visual positioning system detection and spatial calibration of a surgical instrument; installing an optical marker array, collecting actual bone point cloud data, and realizing alignment of the model and the bone through a registration algorithm; in-surgery real-time calculation and display of deviation of an operation track and planning parameters; post-surgery reconstruction of a lower limb force line, and comparison and evaluation with preoperative planning and in-surgery navigation records. The system comprises a hardware execution unit and preoperative planning, calibration verification, in-surgery registration, real-time navigation and post-surgery evaluation modules. The application realizes full-process integration of preoperative accurate planning, in-surgery real-time closed-loop navigation and post-surgery quantitative evaluation, and significantly improves the precision, repeatability and predictability of clinical effects of surgery.

Disclosed are computer visual guidance systems for guiding surgeons through arthroscopic debridement of bony pathologies, including by automatically generating annotations relating to characteristics of bony pathology in an image. The annotation may be generated in accordance with a determination as to whether a femoral head of the bony pathology is endospherical or exospherical. The annotation may be generated in accordance with a mathematical model created based on anatomies of subjects other than the patient. Further disclosed is a user interfaces for guiding a surgeon through arthroscopic debridement of a bony pathology, wherein intraoperative images are displayed simultaneously with a preoperative plan comprising interactive three-dimensional models of an anatomical feature of a patient. Further disclosed is a user interface for guiding a physician in categorizing images of a patient, wherein the interface comprises an image viewing window and an interactive checklist for different image categories to be captured.