28 results about "Tissue deformation" patented technology

The embodiment of the invention provides a method and equipment for dynamically adjusting a motion control mode based on an intraoperative visual field environment, a medium and a program product, and relates to the field of intelligent medical treatment. The method comprises the following steps: acquiring an intraoperative view image and a preset basic force threshold value according to the tissue type of a to-be-operated site; calculating an intraoperative tissue real-time deformation rate based on the intraoperative view image, and calculating a real-time force safety threshold according to a preset basic force threshold and the tissue real-time deformation rate; receiving real-time contact force of the instrument and the tissue, comparing the real-time contact force with a real-time force safety threshold value, and if the real-time contact force is smaller than or equal to the real-time force safety threshold value, outputting an instruction of damping force in direct proportion to the real-time contact force; if the real-time contact force is larger than the real-time force safety threshold value, an emergency braking program instruction is output. According to the method, factors, such as tissue deformation and illumination change, which cause instability of the surgical field of view in the surgical environment are introduced, so that the environmental adaptability and dynamic adjustment of the field of view mechanism in the robot-assisted surgical operation process are improved.

The invention relates to the technical field of remote single-hole robot operation guidance and demonstration, and discloses a system and a method for remote single-hole robot operation guidance and demonstration, which realize efficient, stable and secure transmission of remote force feedback signals and control instructions through a low-delay secure communication link based on SRv6 + TSN and a national password SM9 encryption technology. The problem that transparency and real-time performance are difficult to consider in remote operation is effectively solved, experts can seamlessly perceive interaction force of local instruments and tissues and carry out accurate remote intervention, and through dynamic modeling of a cloud twinning service module and Transformer and graph neural network algorithms, the interaction force between the local instruments and the tissues can be accurately and remotely intervened. Real-time prediction of risks such as bleeding and perforation in the operation and accurate matching of tissue deformation are achieved, a visual and fused AR guidance interface is provided for experts in combination with a mixed reality guidance engine, and the accuracy of remote guidance and operation safety are remarkably improved.

The invention discloses a four-dimensional dynamic image guided dose optimization system for tumor radiotherapy, and belongs to the technical field of medical imaging and radiotherapy. The system comprises a real-time image acquisition module, a dynamic anatomical model construction module, an organ deformation prediction module, a motion compensation engine, a four-dimensional dose accumulation calculation module, a self-adaptive treatment plan generation module and a dose delivery control module. A patient-specific four-dimensional dynamic anatomical model is constructed based on a deep neural network, an autoregression algorithm is adopted to predict organ motion trails, motion compensation parameters are calculated in real time, cumulative dose distribution considering tissue deformation is accurately calculated, a treatment plan is automatically adjusted, and dose delivery with millimeter-level precision is achieved. According to the system, the target area coverage deviation is reduced by 62%, the normal tissue irradiation dose is reduced by 37%, and the precision and safety of thoracic and abdominal tumor radiotherapy are remarkably improved.

The invention discloses a sequence image relative pose estimation method, device and equipment and a medium, and relates to the technical field of image processing, the method accurately estimates inter-frame poses through deep learning, so that ultrasonic three-dimensional reconstruction can be realized under the condition of not using external tracking equipment such as electromagnetic tracking and the like; therefore, various possible complex medical environments can be adapted more flexibly, and medical workers can be helped to perform examination and diagnosis better. And meanwhile, the method eliminates the dependence of ultrasonic three-dimensional reconstruction on external equipment such as optical / magnetic tracking equipment, so that the system architecture is simpler and more compact, the hardware cost and complexity are remarkably reduced, and the method is favorable for adapting to various different clinical application scenes. Besides, through rotation isovariant convolution and multi-scale cross attention, the method can better adapt to factors such as angle change and tissue deformation in the acquisition process, and the robustness of the method is improved.

This invention relates to the field of biomedical technology, and more particularly to a real-time lesion AR annotation method for endoscopic systems based on augmented reality. The method first acquires and preprocesses a real-time video stream from the endoscope; then, a two-stage cascaded model is used to detect and segment lesions in the preprocessed video stream, identifying suspicious lesion areas, generating a segmentation mask, and removing interfering areas in the endoscopic scene; real-time pose data of the endoscope is acquired using an electromagnetic-visual fusion positioning method; based on the segmentation mask and real-time pose data, two-dimensional lesion information is mapped to three-dimensional space to construct a three-dimensional lesion model, which is then completed by combining anatomical structural features and adjusted according to tissue deformation; finally, the adjusted three-dimensional lesion model is back-projected onto the endoscopic field of view to generate AR annotation information, which is then fused with the real-time endoscopic image and output. This invention enables real-time and accurate annotation of endoscopic lesions, providing auxiliary support for endoscopic diagnosis and treatment.

There is provided an accelerated coupled filtering method for tissue deformation analysis. The method includes initializing, by a first processing device, a plurality of first motion parameters; applying, by a second processing device, a first filter on a pre-deformation image of a tissue to obtain a filtered pre-deformation image, wherein the second processing device is different from the first processing device; applying, by the second processing device, a second filter on a post-deformation image of the tissue to obtain a filtered post-deformation image, wherein the filtered pre-deformation image and the filtered post-deformation image are correlated by a first motion matrix comprising the plurality of first motion parameters, and wherein the plurality of first motion parameters comprise at least three fundamental first motion parameters, each of the three fundamental first motion parameters represents movement of the tissue along an axial direction relative to the axial direction, an elevational direction and a lateral direction, respectively; estimating, by the second processing device, a respective value for each of the plurality of first motion parameters, wherein each of the estimated respective values represents a difference between the pre-deformation and post-deformation filtered images; and in response to determining that at least one of the estimated respective values meets at least one predefined criterion, updating the at least one of the estimated respective values as an optimal value for at least one corresponding first motion parameter of the plurality of first motion parameters.

A surgical robotic system for automatic port repositioning includes a robotic arm coupled to an access port inserted through an incision, the access port is equipped with sensors to detect tissue deformation. Using imaging or force sensors, the system monitors tension around the port and calculates motion vectors to perform micro-adjustments, or "port burping," to relieve strain without disrupting surgery. The robotic arm executes these adjustments gradually, ensuring smooth operation. Additionally, the system monitors task and workspace volumes to keep instruments within safe zones, using algorithms like SLAM and bump detection. If instruments approach workspace limits, the system autonomously adjusts the port's position to expand the task space, minimizing manual intervention and enhancing surgical efficiency.

This invention provides a method and system for soft tissue collaborative surgery control based on a humanoid robot. It relates to the fields of medical robotics, computer vision, and remote teleoperation. The method includes: displaying, via a display terminal, image stream information acquired in real time by the humanoid robot for the surgical operation area, wherein the surgical operation area includes the area where a first instrument held by a first robotic hand of the humanoid robot is located; in response to detecting a grasping operation representing soft tissue grasped by the first instrument, obtaining the tissue deformation rate of the grasped soft tissue; generating, based on the tissue deformation rate of the grasped soft tissue, a prompt message for indicating the tissue stretching state on the display terminal; and sending the prompt message to the display terminal for display.

This invention discloses an intelligent puncture path planning method for interventional surgical robots, belonging to the field of interventional robot path planning technology. The method acquires multimodal medical images of the patient's puncture site, completes organ tissue segmentation and three-dimensional reconstruction, generates a digital twin anatomical model, and calibrates basic puncture parameters; constructs a respiratory phase tracking model, combines the basic puncture parameters to lock the respiratory cycle and real-time respiratory phase, and outputs the three-dimensional predicted coordinates of the puncture target point for a pre-set duration; acquires needle insertion force data through a six-dimensional force sensor, calculates tissue compression deformation and needle body flexible bending offset in real time, and generates a feedforward compensation vector; fuses the three-dimensional predicted coordinates and the feedforward compensation vector to generate a dynamic puncture path, performing continuous needle insertion without interruption throughout the entire process. This invention improves upon the shortcomings of traditional static path planning, which cannot adapt to respiratory displacement and tissue deformation, effectively improving puncture positioning accuracy and is suitable for minimally invasive interventional puncture surgery scenarios.

This invention discloses a method and apparatus for predicting feedback force during virtual surgery, belonging to the technical field of feedback force prediction during virtual surgery. The feedback force prediction method includes: in response to collision detection during virtual surgery, acquiring data required for prediction and data required for updating; based on the data required for updating, dynamically updating a trained TCN-Transformer parallel enhanced temporal fusion model using a lightweight online learning strategy; inputting the data required for prediction into the model to obtain predicted tissue deformation values ​​and predicted feedback force values; calculating the tissue deformation prediction error based on the predicted tissue deformation values ​​and the calculated tissue deformation values; if the tissue deformation prediction error is less than a preset decision threshold, then the predicted feedback force value is used as the final prediction result. This invention significantly reduces the feedback force output delay by replacing calculation with prediction, and maintains prediction accuracy by dynamically updating to adapt to sudden operational changes.

The utility model discloses a medical suture belongs to medical supplies technical field. The medical suture includes suture body and the tail end setting of its stop flab, and stop flab width is greater than suture body, and is equipped with at least two orifices that can pass through suture body along suture body extension direction. When the above -mentioned medical suture is used to carry out tissue suture, by the abutment of stop flab and the tissue to be sutured, suture body is connected with tissue again after setting aperture, can make suture force evenly dispersed on stop flab, thereby dispersing force to greater area, significantly reduce the stress of tissue at the suture, reduce tissue deformation and breakage risk, especially suitable for the suture of fragile tissue, provide good environment for tissue healing. Meanwhile, stop flab increases the contact area with tissue, provides more stable support and fixed.

This invention provides a digital intelligent MSE automatic design method based on biomechanical simulation, belonging to the field of biomechanical simulation technology. The method includes: acquiring three-dimensional morphological data and physiological load data of the target anatomical structure and mapping them to obtain a load distribution matrix; performing tensor operations on the load distribution matrix and tissue mechanical response characteristics to obtain a stress prediction field; identifying high-stress concentration areas and low-stiffness weak areas based on the stress prediction field; extracting contour curves and calculating the normal gradient to determine the expansion constraint direction; minimizing the stress distribution variance and the total tissue deformation energy and determining the spatial configuration parameters of the MSE device; using the spatial configuration parameters as boundary conditions to iteratively calculate the displacement field and strain field; correcting the spatial configuration parameters based on the difference between the cumulative deformation and a preset physiological threshold and the iterative deformation energy change rate; and outputting the corrected configuration parameters as design instructions when the convergence condition is met.

The application provides a pathological section and MRI image registration method and device based on biomechanical elastic deformation, which comprises the following steps: obtaining a three-dimensional digital twin of a tumor region, obtaining a digital resection region in the three-dimensional digital twin based on a preset surgical margin; performing ex vivo dynamics simulation on the digital resection region to obtain a tissue deformation result; obtaining an optimal deformation section with maximum mutual information in the tissue deformation result and a pathological section; obtaining an inverse transformation deformation field between the optimal deformation section and the three-dimensional digital twin, and projecting a tumor region edge of the pathological section to the three-dimensional digital twin based on the inverse transformation deformation field. The scheme realizes fine local nonlinear adaptation of the section by constructing an ex vivo dynamics finite element simulation technology of a volume shrinkage function and performing local deformation with the pathological section edge information as a constraint, quantitatively restoring the global non-uniform shrinkage of the ex vivo tissue and the differential local deformation of the tumor and normal tissue.

The invention relates to the technical field of neurosurgery, and provides a tissue dynamic grid updating method in neurosurgery simulation, which comprises the following steps: S1, initializing grids and physical parameters, creating an independent copy of original vertex coordinates as deformation reference data, and initializing an instantaneous movement speed array of each vertex; s2, multi-mode deformation parameter input and processing are carried out, deformation action point coordinates, force values and action modes input externally are received, and deformation action force is applied to a single vertex, a predefined vertex set and all vertexes according to action mode selection; s3, carrying out vertex motion real-time calculation, and calculating displacement vertex by vertex based on a spring-damping physical model; s4, dynamic scaling self-adaptive correction is carried out, a space scaling coefficient of the nervous tissue is obtained in real time, and normalization processing is carried out on displacement and speed in tissue deformation calculation; and S5, carrying out grid data synchronization and physical updating. And efficiency and precision collaborative optimization is realized, and sub-millisecond response is realized.

This invention discloses a modular VR / AR surgical teaching system and method based on a local large-scale model. The local large-scale model training module is deployed in a local computing environment, storing structured medical knowledge and dynamically generating teaching scripts and assessment question banks. A lightweight VR / AR hardware group collects multi-dimensional user operation data and provides multi-sensory feedback. A full-process training control module, with a built-in physical simulation engine and evaluation logic, constructs a virtual surgical scene, simulates tissue mechanical changes in real time, compares user operations with standard surgical procedure models and generates error correction guidance, and generates a quantitative ability assessment report based on the entire process data. A multi-scene data mapping interface adopts a modular architecture based on a standardized intermediate communication protocol, achieving low-coupling logical isolation and dynamic integration between functional modules through a unified data exchange format and abstract interface specifications. This application adopts an edge-side deployment strategy to protect patient privacy and ensure real-time force feedback and tissue deformation rendering in the VR / AR scene.

This invention discloses a puncture actuator integrating force feedback and active rotation functions, including a puncture needle assembly, a force feedback unit, a rotation drive unit, a control module, and a path planning unit. The force feedback unit is used to detect the contact force between the puncture needle and soft tissue in real time. The rotation drive unit is used to actively drive the puncture needle to rotate during puncture. The control module dynamically adjusts the puncture speed and rotation speed based on the force feedback information. The path planning unit dynamically corrects the puncture path by combining tissue characteristics and physiological motion information. This invention enables real-time perception and adaptive control of the tissue's mechanical state during puncture, effectively reducing errors caused by tissue deformation, needle tip deviation, and target displacement, significantly improving puncture accuracy and efficiency, while enhancing operational safety, and has high clinical application value.

The utility model discloses an animal tissue storage device with shockproof structure relates to animal tissue storage technical field. The utility model discloses a arc bottom plate and fixed clamping plate, arc bottom plate top is provided with fixed frame, and the outer wall of fixed frame is provided with elastic link, and fixed clamping plate sets up at elastic link one end, and the outer wall of fixed clamping plate is provided with push slide, and the inside of fixed frame is provided with adjusting sliding slot, and the inside of adjusting sliding slot is provided with adjusting slide plate. The utility model discloses setting up the protection mechanism, not only can when test tube is placed to the inside of the placing groove, the test tube is fixed with clamping, can avoid because the road surface is uneven and drives test tube and the animal tissue sample in test tube to shake, makes animal assembly sample and test tube inner wall to collide and causes animal tissue deformation, rupture or cell damage to animal assembly sample, and can adjust the clamping strength of protection mechanism to test tube according to the clamping demand of test tube, can guarantee the stability of test tube in the transportation process.

The present application relates to the technical field of puncture path planning, in particular to a puncture path planning method for severe acute pancreatitis abdominal puncture drainage. First, a three-dimensional model of the abdominal cavity is constructed by fusing CT images and MRI images and tissue regions (organ regions, blood vessel regions, lesion regions) are segmented, and candidate paths are generated based on target positions and preset body surface entry points. Then, risk coefficients are calculated based on the geometric characteristics (angle, length, and proximity to tissue regions) of the candidate paths, and the preliminary optimal paths are screened. Further, the puncture body position and the direction of the gravity component are determined in combination with the sagittal / coronal position relationship, the tissue density distribution is analyzed, and the tissue deformation interference index is quantified. Finally, the risk coefficients and the deformation index are fused to realize the re-screening of the paths, determine the optimal and alternative paths, so as to effectively avoid key tissue structures and reduce the risk of intraoperative displacement, and improve the puncture accuracy and stability.

The invention provides a pathological section and MRI image registration method and device based on biomechanical elastic deformation, and the method comprises the following steps: obtaining a three-dimensional digital twinborn body of a tumor region, and obtaining a digital excision region in the three-dimensional digital twinborn body based on a preset surgical incision edge; performing in-vitro dynamic simulation on the digital resection area to obtain a tissue deformation result; obtaining an optimal deformation section with the maximum mutual information with the pathological section in the tissue deformation result; and obtaining an inverse transformation deformation field between the optimal deformation section and the three-dimensional digital twinborn body, and projecting the tumor area edge of the pathological section into the three-dimensional digital twinborn body based on the inverse transformation deformation field. According to the scheme, local deformation is carried out by constructing an in-vitro dynamic finite element simulation technology of a volume shrinkage function and taking pathological section edge information as a constraint, global non-uniform shrinkage of in-vitro tissues and differential local deformation of tumors and normal tissues are quantitatively reduced, and refined local nonlinear adaptation of sections is realized.

The utility model provides a pathological tissue embedding forceps, including first forceps main part and pressure application spare, wherein, first forceps main part includes first clamping arm and second clamping arm, one end fixed connection of first clamping arm and second clamping arm, the other end forms first clamping end, pressure application spare installs on second clamping arm, has pressure surface, and pressure surface is stainless steel plane. When using, hand -held forceps press in first clamping arm and second clamping arm simultaneously, make first clamping end clamping tight tissue, then transfer tissue to mould, place tissue well, rotate wrist and adjust the angle of forceps, make pressure application spare turn to the angle of vertical pressing tissue, then use pressure surface and press tissue downward, until tissue is even and adheres mould bottom. The embedding forceps of the utility model can ensure that tissue is uniformly stressed by pressing tissue downward with the pressure surface, avoid tissue deformation or fragmentation during the pressing process, and is simple, convenient and efficient to operate, suitable for continuous processing of large quantities of tissue samples.

The present application relates to a meningioma infiltration boundary resection strategy optimization method, which uses the stress and strain response difference during intraoperative tissue traction and suction operation to mark the biomechanical abnormal area in space; constructs a mechanical residual atlas; extracts the local tissue compliance critical point as the physiological landmark of the infiltration boundary; identifies the high adaptability channel in the three-dimensional tissue atlas; makes partition modeling for the structural impedance of different regions; constructs a boundary evolution stability hot area map, maps the boundary prediction result back to the current operation scene, and is used to judge whether the resection range needs to be expanded; after each tissue stripping or resection, the corresponding regional tissue deformation rate, blood supply flow rate and temperature diffusion mode indicators are collected as the reflection of the intraoperative boundary stress response, which is used to evaluate whether the high-risk area has been touched by the resection behavior; once the boundary stress index exceeds the preset threshold, the system freezes the path segment, calculates the alternative path, improves the accuracy of boundary identification, and reduces the damage to the functional area and the recurrence risk.

The application relates to the technical field of robot control, and discloses a motion trajectory planning system for a needle knife robot, which comprises a sensor module, a kinematics modeling module, a path generation and correction module, an optimization module and an intelligent control module; the path generation and correction module and the optimization module are arranged, the basic trajectory is obtained by dynamically correcting the path in combination with a tissue deformation prediction model, real-time force feedback and tissue deformation data are combined, the dynamic adaptability is improved, trajectory deviation is effectively prevented, a smooth speed curve is generated based on the basic trajectory by adopting a quintic polynomial interpolation method, the smoothness of the trajectory and the continuity of acceleration are ensured, impact control is performed on the needle knife robot by a dynamic compensation algorithm, mechanical vibration caused by acceleration mutation of the needle knife robot in a surgical process is prevented, surgical risks are reduced, and surgical safety is improved.

The invention relates to the technical field of image processing, in particular to a cervical pathology multi-mode slice image recognition method and system. Comprising the following steps: acquiring two different staining section images of the same cervical tissue sample, respectively performing semantic structure recognition to extract biological structure types and geometric positions thereof, and generating two groups of feature point sets with structure type labels according to the biological structure types and the geometric positions thereof; respectively analyzing the spatial relationship between the feature points to construct topological descriptions, and determining the corresponding matching of the cross-modal feature points by combining the two groups of topological descriptions under the constraint of the consistency of the structure types; sparse deformation information is calculated through the matching point pairs, a dense deformation field representing mapping from the second image to the first image is generated through interpolation, a fine deformation field is obtained through further iterative optimization, and geometric transformation is conducted on the second slice image to achieve alignment with the first slice image. The technical problem of fusion analysis errors caused by difficulty in accurate alignment of multi-modal slice images due to tissue deformation in a pathological slice preparation process is solved.

The invention relates to the technical field of medical image analysis, and discloses an intelligent evaluation method and system for excision cleanliness in breast tumor minimally invasive rotary atherectomy, and the method comprises the steps: firstly obtaining preoperative and intraoperative ultrasonic images of a patient, matching a region of interest through a structural similarity index, and respectively intercepting a main image and a local patch; then, respectively extracting global features of the main image and texture features of local patches by using a deep neural network; performing spatial collaborative attention processing on the global features to establish spatial association between the preoperative image and the intraoperative image, and performing multi-instance pooling operation on the local features to aggregate key details; and the global and local features are adaptively fused through a gating network and then input into a classifier to output an evaluation result. The system further introduces a sample source weighting strategy and a man-machine cooperation closed-loop mechanism to optimize model training. According to the method, the problem of feature alignment caused by soft tissue deformation in an operation is effectively solved, and the objectivity and accuracy of excision cleanliness evaluation are remarkably improved.

The invention discloses a contact type ultrasonic deep tissue pressure measuring instrument and a deep tissue pressure monitoring method, and relates to the technical field of medical instruments. The pressure measuring instrument comprises an ultrasonic probe body, a grip strength detection module, a data processing module and a wireless transmission module. A deep learning model is arranged in the data processing module, and non-invasive, accurate and real-time measurement of deep tissue pressure is achieved by synchronously fusing grip signals of an operator and tissue deformation data in an ultrasonic image. The method comprises the steps of synchronous acquisition of grip strength and ultrasonic images, signal preprocessing, multi-modal deep learning fusion calculation and result wireless transmission and display. The problem of accurate monitoring of deep tissue pressure is solved, and the method is suitable for pressure treatment scenes such as lower limb deep vein thrombosis prevention and the like.

The invention provides an ultrasonic device and a prostate elasticity measurement method, and the method comprises the steps: transmitting a first ultrasonic wave to a prostate part of a to-be-measured object, and receiving a first ultrasonic echo signal of the first ultrasonic wave; generating a B ultrasonic image of the prostate part according to the first ultrasonic echo signal; obtaining an outer gland area of the prostate part based on the B ultrasonic image; transmitting a second ultrasonic wave for generating an acoustic radiation force to the outer gland region to cause tissue deformation of the outer gland region; transmitting a third ultrasonic wave for detecting the tissue deformation to the external gland area, and receiving a third ultrasonic echo signal of the third ultrasonic wave; and obtaining an elasticity measurement result of the outer gland area according to the third ultrasonic echo signal. The tissue is deformed by generating acoustic radiation force, so that an elasticity measurement result of a larger area can be obtained.

This invention discloses a method, system, device, and medium for processing multimodal skin detection data, relating to the field of data processing technology. The method includes: acquiring pre-collected multispectral image data of a target skin region under pressure detection conditions and corresponding tissue deformation parameter data; extracting apparent blood flow feature values ​​from the multispectral image data, which characterize the blood emptying state of the target skin region due to pressure; performing inverse calculation on the apparent blood flow feature values ​​based on the tissue deformation parameter data and a preset microvascular emptying compensation model to obtain the true blood flow feature values ​​of the target skin region under non-pressure conditions; acquiring deep structural echo data of the target skin region under pressure detection conditions, and fusing the deep structural echo data with the true blood flow feature values ​​for output. This invention eliminates the distortion of blood flow optical characteristics caused by contact detection pressure, achieving accurate fusion output of the true surface blood flow state and deep tissue structure data.