2753 results about "Soft tissue" patented technology

The invention discloses a multi-modal large model assisted laparoscope soft tissue registration surgical navigation method and system. The method comprises the following steps: acquiring a preoperative CT (Computed Tomography) or MRI (Magnetic Resonance Imaging) image and an intraoperative laparoscope image, and converting to obtain a multi-modal feature sequence; inputting the obtained multi-modal feature sequence into a large model for fusion to obtain a cross-modal matching matrix; random sampling is carried out by using an RANSAC random sampling consensus algorithm, an error between corresponding point sets of two data is measured by using an Euclidean distance, an analytical solution is obtained through SVD decomposition, and a feature matching error is introduced to obtain an optimal rigid body transformation pose; performing non-rigid deformation local fitting adjustment on the optimal rigid body transformation pose residual error by adopting a parameterized deformation model in combination with learning prediction deformation, and performing loop execution to obtain a soft tissue organ real-time registration image; automatic, high-timeliness and high-precision real-time registration of soft tissues is realized under the multi-mode and multi-variable conditions, and reliable navigation and positioning support is ensured to be provided in a complex operation environment.

The invention discloses a medical image enhancement method and system based on multi-modal fusion, and the method comprises the steps: obtaining medical image data which comprises a CT image, an MRI image, a PET image and an ultrasonic image; calculating a mutual information value of each semantic tag in the cross-modal feature vocabulary, and generating an inter-modal feature correlation matrix; performing non-rigid space registration on the unified dimension image set to generate a geometrically consistent multi-modal image set; extracting skeleton region features, soft tissue region features and high metabolism region features from the multi-modal image set, and generating a core feature set; a deep learning algorithm is adopted to train the core feature set, and a segmented image set containing a segmentation mask is generated; and dynamically adjusting the fusion weight according to the regional features of the segmented image set, and generating a fusion enhanced image. According to the invention, through feature extraction, spatial registration and deep learning fusion of the multi-modal medical image, effective integration of different-modal medical image information is realized.

The invention provides a multi-angle photographing and three-dimensional reconstruction method and system for soft tissue, and relates to the technical field of soft tissue three-dimensional reconstruction, and the method comprises the steps: analyzing soft tissue features based on deep learning, generating a bulb tube motion track and sampling interval data, and controlling a mechanical arm to drive a bulb tube to collect projection images at multiple angles; screening an optimal image sequence by using an image quality evaluation network, and performing preprocessing such as material decomposition, feature extraction, space registration and image optimization; and inputting the optimized image and the material features into a reconstruction model, performing iterative calculation in combination with an anatomical structure template to generate density distribution data, performing curved surface reconstruction and intelligent tissue segmentation based on graph convolution based on the density distribution data, and finally generating a three-dimensional model containing tissue layering information.

Presented herein are systems and methods that provide for automated analysis of three-dimensional (3D) medical images of a subject in order to automatically identify specific 3D volumes within the 3D images that correspond to specific anatomical regions (e.g., organs and / or tissue). Notably, the image analysis approaches described herein are not limited to a single particular organ or portion of the body. Instead, they are robust and widely applicable, providing for consistent, efficient, and accurate detection of anatomical regions, including soft tissue organs, in the entire body. In certain embodiments, the accurate identification of one or more such volumes is used to automatically determine quantitative metrics that represent uptake of radiopharmaceuticals in particular organs and / or tissue regions. These uptake metrics can be used to assess disease state in a subject, determine a prognosis for a subject, and / or determine efficacy of a treatment modality.

Presented herein are systems and methods that provide for automated analysis of three-dimensional (3D) medical images of a subject in order to automatically identify specific 3D volumes within the 3D images that correspond to specific anatomical regions (e.g., organs and / or tissue). Notably, the image analysis approaches described herein are not limited to a single particular organ or portion of the body. Instead, they are robust and widely applicable, providing for consistent, efficient, and accurate detection of anatomical regions, including soft tissue organs, in the entire body. In certain embodiments, the accurate identification of one or more such volumes is used to automatically determine quantitative metrics that represent uptake of radiopharmaceuticals in particular organs and / or tissue regions. These uptake metrics can be used to assess disease state in a subject, determine a prognosis for a subject, and / or determine efficacy of a treatment modality.

A method for aligning 3D objects in an extended reality (XR) system involves obtaining 3D objects from a volumetric imager or surface scanner, where the volumetric imager captures a three-dimensional voxel array representing an anatomical structure and the surface scanner generates a polygonal mesh or point cloud of the same structure. The method includes detecting a set of points on the 3D objects by identifying distinct anatomical landmarks, such as facial landmarks for soft tissue or tooth landmarks for hard tissue, and assigning each point a unique identifier. A video feed from XR goggles or a prerecorded video is obtained, providing real-time or prerecorded imagery of the patient's anatomical structure from various angles. Corresponding points on the video feed that align with the set of points detected on the 3D objects are identified using image processing techniques, ensuring accurate correspondence. The registered 3D objects are rendered to match the corresponding points on the patient's anatomical structure, with the alignment switching between soft tissue points when the patient's mouth is closed and hard tissue points when the patient's mouth is open for enhanced precision.

The invention discloses a plastic effect simulation display method and system based on a 3D simulation technology, and relates to the technical field of medical information, and the method comprises the steps: collecting the facial data of a patient, and constructing a multi-level facial structure initial model; constructing a hybrid deformation model; individual characteristic parameters of a patient are extracted, and an individual biomechanical parameter set is generated through the biomechanical parameter prediction network; applying the personalized biomechanical parameter set to the mixed deformation model; operation input parameters of plastic surgery are received, and the deformation result of each layer of structure is calculated and displayed in real time based on a GPU parallel computing framework; constructing a tissue healing and recovery kinetic model, and generating appearance prediction data at different postoperative time points in combination with the deformation result; and performing three-dimensional visualization processing on the appearance prediction data. According to the method, CT / MRI, 3D structured light scanning and expression dynamic video sequences are creatively integrated, the limitation of traditional single-mode data modeling is broken through, and the soft tissue boundary recognition precision is remarkably improved.

The invention discloses a mixed collision detection method in a virtual operation simulation system. The method comprises the following steps: 1) constructing a surgical instrument and soft tissue model; 2) dividing a virtual space into grids with the same size, indexing an object model, accelerating the construction and updating of a spatial information hash table by utilizing GPU multithreading, mapping the grids occupied by all primitive bounding boxes into the hash table, and determining objects in the same space according to the spatial hash table; 3) before object intersection solving, space reduction is carried out, and hash table data is optimized; 4) constructing a hierarchical bounding box for an object which may collide, and performing intersection detection; if it is detected that a certain node or child nodes of the node intersect, the next step is executed, and otherwise, detection is pushed out; and 5) accurately judging whether the basic triangular units contained in the nodes in the step 4) are intersected or not, and completing collision detection. According to the method, the problem of missed detection and wrong detection in the existing discrete collision detection algorithm is effectively solved, and the detection algorithm has excellent accuracy and calculation efficiency.

A method and apparatus for coupling a soft tissue implant into a looking cavity formed within a bone is disclosed. A bone engaging fastener is coupled to bone. A second fastener is coupled to a suture construction. The second fastener is coupled to the first fastener. Soft tissue is coupled to the suture construction.

The invention relates to a reconstruction method of a liver, gall and pancreas three-dimensional image. According to the technical scheme, the method comprises the following steps: introducing a segmentation network for U-Net variants of the liver, the bile duct and the pancreas, and segmenting a multi-modal image by using a convolutional neural network, including separation of the liver, the bile duct and the pancreas; a boundary enhancement module is introduced in the segmentation process; performing spatial alignment on the image data of different modalities by adopting a deep learning driven non-rigid registration algorithm; carrying out registration by utilizing anatomical feature points of the organs; according to a registration result, performing multi-modal fusion on the liver image, the bile image and the pancreas image, and constructing fusion image data by comprehensively utilizing the bone and tissue contrast ratio of CT, the soft tissue resolution ratio of MRI and the real-time dynamic characteristics of ultrasound; extracting contours of liver, gall and pancreas from the segmented image, and constructing a preliminary three-dimensional mesh model; and according to the geometrical shapes of different organs, adaptive adjustment is carried out, and the distribution of grids during reconstruction is controlled to be matched with the organ shapes.

The invention relates to a biological soft tissue virtual simulation method and system and a medium, and the method comprises the following steps: constructing a three-dimensional soft tissue model based on medical image data, dispersing the three-dimensional soft tissue model into a particle system, and binding initial constraint parameters; detecting collision between the particles and the surgical instrument based on a symbolic distance field technology, if collision is not detected, outputting the positions of the particles, generating a simulation result, if collision is detected, applying repulsive force to the particles to correct a deformation path, judging whether stress is balanced or the maximum number of iterations is reached, if yes, returning to perform collision detection, and if not, returning to perform collision detection. The particle speed is updated in real time, the particle motion trend is predicted through an implicit time integration algorithm, position constraint, volume constraint, shape constraint and physical constraint are solved in a coupling mode through a Gaussian-Seidel iteration method, constraint rigidity is dynamically adjusted to be matched with real organization characteristics, and the particle position is updated. Compared with the prior art, the method has the advantage that deformation accords with a real physical change rule.

The invention relates to the technical field of medical equipment, in particular to an ultrasonic soft tissue operation accessory intelligent recognition and energy regulation and control system and method.The ultrasonic soft tissue operation accessory intelligent recognition and energy regulation and control system comprises an intelligent recognition module used for recognizing the type, specification and real-time use state of an operation accessory to serve as an output result; the energy regulation and control module is connected with the intelligent identification module and dynamically adjusts the output parameters of the ultrasonic energy according to the output result of the intelligent identification module; and the man-machine interaction module is respectively connected with the intelligent identification module and the energy regulation and control module and is used for displaying the identification result, the energy parameters and the early warning information. According to the result of the intelligent recognition module, dynamic adjustment of ultrasonic energy output parameters is achieved through the energy regulation and control module, and smooth operation is ensured; when it is detected that the accessory temperature exceeds the preset threshold value or the impedance abnormally and suddenly rises, energy supply is rapidly cut off, the surgical risk caused by energy abnormity is effectively prevented, and the safety of a patient is guaranteed.

The invention relates to the technical field of spine deformation recognition, in particular to a spine deformation recognition method and system based on image recognition, and the method comprises the following steps: S1, data collection and preprocessing: obtaining multi-view and multi-time-point spine image data of the spine of a patient; s2, soft tissue shielding correction: automatically identifying and correcting interference of the soft tissue on the spine image data; s3, dynamic change prediction of the spine: performing dynamic change prediction on the spine image data subjected to soft tissue shielding correction; and S4, deformation judgment and result output: judging the deformation condition, the deformation type and the severity of the spine, and generating a visual report containing the spine deformation condition and future change prediction. According to the method, the noise in the image is effectively removed, the definition of the spine structure is enhanced, and meanwhile, the interference problem of soft tissue on the spine image is solved.

The invention relates to the technical field of automobile safety, in particular to a human body finite element model soft tissue motion deformation non-simulation rapid calculation method. Comprising the steps of initializing a calculation structure, recognizing a skeleton-soft tissue common node NBS, and extracting a soft tissue inner surface node NSS, a near-end end face node NSP and a far-end end face node NSD. And extracting skeleton motion information, calculating node coordinate sets BS0 and BS1 based on the initial configuration B0 and the target configuration B1, and determining end face boundaries SP0 and SP1 and SD0 and SD1 by utilizing rigid body transformation. Calculating an initial displacement field D0, acting on the NSS to obtain an initial deformation inner surface SS1, and processing a penetration site to obtain SS2; and fixing the BS1, and optimizing the coordinates of the SS2 node to obtain SS3. And integrating the initial mark point sets SS0, SP0 and SD0 and the post-motion mark point sets SS3, SP1 and SD1, and calculating a final displacement field D1 through spatial interpolation. The technical scheme can quickly and accurately simulate the large deformation of the soft tissue involved in human motion.

The invention belongs to the technical field of biomedical materials, and relates to ultrasonic response adhesion integrated hydrogel as well as a preparation method and application thereof, the hydrogel comprises a hydrogel matrix, an interface anchoring agent and a functional load component; the preparation method comprises the following steps: 1, preparing a hydrogel precursor solution, and preparing a hydrogel matrix into a solution; 2, carrying out mold molding or injection crosslinking on the solution prepared in the step 1 to form hydrogel; 3, preparing an interface anchoring agent solution, and dissolving or dispersing an interface anchoring agent in a solvent to prepare the interface anchoring agent solution; the ultrasonic responsive adhesive hydrogel platform provided by the invention can provide an efficient, controllable and universal solution for tissue adhesion, targeted therapy, wearable attachment and the like in a complex microenvironment, and is suitable for a plurality of clinical scenes such as chronic wound management, surgical postoperative closure, infection control, adhesive bioelectronic fixation, soft tissue engineering and the like.

Systems and methods for calculating external bone loss for alignment of pre-diseased joints comprising: generating a three-dimensional (“3D”) computer model of an operative area from at least two two-dimensional (“2D”) radiographic images, wherein at least a first radiographic image is captured at a first position, and wherein at least a second radiographic image is captured at a second position, and wherein the first position is different than the second position; identifying an area of bone loss on the 3D computer model; and applying a surface adjustment algorithm to calculate an external missing bone surface fitting the area of bone loss.

The invention discloses a chest CT (Computed Tomography) image processing method and system, and relates to the technical field of medical image processing, and the main scheme is as follows: acquiring image data of two groups of X-rays with different energies and attenuation measurement values of pixel points by adopting dual-energy CT scanning, respectively calculating concentration values of soft tissues and blood vessels, and generating concentration maps; generating an initial image based on the soft tissue and blood vessel concentration map, calculating a pixel value, obtaining a target image pixel value through contrast stretching, segmenting the target image pixel value to obtain a binary image, and distinguishing a blood vessel region and a soft tissue region in the binary image by identifying and analyzing a connected region in the binary image; carrying out center line extraction on the blood vessel region, calculating a local diameter, and respectively comparing the local diameter with a blood vessel dilation threshold value and a blood vessel constriction threshold value to judge abnormal blood vessel dilation or constriction; extracting features from the soft tissue region to form a first feature vector, and comparing the first feature vector with a preset second feature vector to judge abnormality; abnormal conditions are automatically labeled or highlighted, so that the diagnosis accuracy and efficiency are improved.

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

The invention provides a method for predicting the vibration reduction effect of exercise compression pants, and relates to the technical field of functional costume design, and the method comprises the steps: collecting a static costume pressure value of a lower limb target muscle group and soft tissue amplitude data in exercise, constructing a pressure-amplitude mathematical model through data processing, and verifying the model; constructing a human body-clothing finite element model, inputting fabric mechanical parameters into the model, and verifying the effectiveness of the model after iterative optimization; inputting fabric mechanical parameters into the verified finite element model, inputting a pressure prediction value output by the model into the pressure-amplitude mathematical model, and predicting soft tissue amplitude in a dynamic motion scene; according to the predicted soft tissue amplitude in the dynamic motion scene, the vibration reduction effect of the motion compression trousers in the target motion scene is evaluated. The method provided by the invention solves the problem that the vibration reduction effect evaluation of the traditional sports compression pants depends on a large number of repeated physical experiments and is difficult to realize accurate quantitative prediction.

The invention relates to a biodegradable high-strength medical soft tissue adhesive as well as a preparation method and application thereof. The medical soft tissue adhesive comprises a soft segment, a hard segment and a hard segment chain extender, the soft segment is a polyethylene glycol polymer; the hard segment is isocyanate; the hard segment chain extender comprises a hard segment electrically neutral chain extender and a hard segment ionized chain extender; the molar ratio of the polyethylene glycol polymer to the isocyanate to the hard segment electrically neutral chain extender to the hard segment ionized chain extender is (1-7): (50-95): (14-20): (2-6). The preparation method comprises the following steps: mixing the polyethylene glycol polymer, the hard segment chain extender and the isocyanate, heating and reacting to obtain a mixed reaction system; cooling after the reaction is completed, adding a rheology modifier, a foaming catalyst and a stabilizer into the mixed reaction system, and uniformly mixing to obtain the biodegradable high-strength medical soft tissue adhesive which is suitable for functional composite materials.

Presented herein are systems and methods that provide for automated analysis of three-dimensional (3D) medical images of a subject in order to automatically identify specific 3D volumes within the 3D images that correspond to specific anatomical regions (e.g., organs and / or tissue). Notably, the image analysis approaches described herein are not limited to a single particular organ or portion of the body. Instead, they are robust and widely applicable, providing for consistent, efficient, and accurate detection of anatomical regions, including soft tissue organs, in the entire body. In certain embodiments, the accurate identification of one or more such volumes is used to automatically determine quantitative metrics that represent uptake of radiopharmaceuticals in particular organs and / or tissue regions. These uptake metrics can be used to assess disease state in a subject, determine a prognosis for a subject, and / or determine efficacy of a treatment modality.

Disclosed in the present invention are an image generation method and system based on oral cavity imaging. The method comprises: acquiring CT image data of an oral cavity to be processed, and constructing an oral cavity skeleton model on the basis of the CT image data; extracting skeleton features of the oral cavity skeleton model, and, by means of a preset healthy soft and hard tissue oral cavity model database and on the basis of the skeleton features, covering the oral cavity skeleton model with soft tissue to obtain a first oral cavity model; performing three-dimensional laser scanning on said oral cavity so as to construct a second oral cavity model, comparing the first oral cavity model with the second oral cavity model to obtain a soft tissue difference area of the first oral cavity model and the second oral cavity model, and marking the soft tissue difference area in the second oral cavity model; acquiring optical image information of a target acquisition area in said oral cavity, and performing soft tissue feature extraction on the optical image information; and covering the second oral cavity model with extracted soft tissue features to obtain a three-dimensional image model of said oral cavity, and then performing oral image acquisition on the three-dimensional image model so as to generate an oral cavity image.

The invention relates to the technical field of computers, discloses a tooth three-dimensional precision correction method and system based on multi-source oral data fusion, and aims to solve the problems of low registration precision, serious geometric distortion and lack of function oriented optimization of multi-modal oral data in the prior art. The method comprises the following steps: synchronously obtaining intraoral scanning, CBCT and face three-dimensional point cloud data; carrying out format conversion, denoising and grid simplification preprocessing; tooth surface morphology, root canal anatomy and soft tissue contour features are extracted and coded into uniform feature tensors; and multi-modal data space alignment is realized through staged rigid and non-rigid registration. By means of the scheme, the multi-source data fusion precision and the tooth form restoration accuracy are remarkably improved, full-process automatic efficient processing is achieved, and the clinical real-time performance and high-precision diagnosis and treatment requirements are met.

The invention relates to the technical field of artificial intelligence, and discloses a teenager scoliosis intelligent quantitative evaluation system fused with multi-modal imaging. The system comprises a multi-modal data management module, a cross-modal registration fusion module, a dynamic quantitative analysis module, a risk prediction module, a three-dimensional reconstruction module, a report generation module and a system management module, and by setting a multi-modal registration verification mechanism, accurate matching of a bony structure and soft tissue is ensured. Key parameter calculation errors caused by registration failure are reduced, the three-dimensional reconstruction precision is greatly improved compared with traditional single-mode evaluation, a dynamic respiration compensation module is introduced, in the spine deformation parameter quantification stage, spine physiologic changes in a respiration movement period are automatically captured, measured values are corrected based on an individualized dynamic model, and the accuracy of three-dimensional reconstruction is improved. Pathological progression and physiological fluctuation are distinguished, the misjudgment risk caused by neglecting breathing phase change in traditional static measurement is avoided, and the reliability of scoliosis progression risk assessment is improved.

An orthopaedic tibial prosthesis includes a tibial baseplate with an asymmetric periphery which promotes proper positioning and orientation on a resected tibia, while also facilitating enhanced kinematics, soft-tissue interaction, and long-term fixation of the complete knee prosthesis. The asymmetric baseplate periphery is sized and shaped to substantially match portions of the periphery of a typical resected proximal tibial surface, such that proper location and orientation is evident by resting the baseplate on the tibia. The baseplate periphery provides strategically positioned relief and / or clearance between the baseplate periphery and bone periphery, such as in the posterior-medial portion to prevent deep-flexion component impingement, and in the anterior-lateral portion to avoid undue interaction between the anatomic iliotibial band and prosthesis components.

The invention belongs to the technical field of hydrogel, and particularly relates to animal glue composite hydrogel as well as a preparation method and application thereof. The animal glue composite hydrogel comprises animal glue, polyvinyl alcohol, glycerol and water. The animal glue composite hydrogel provided by the invention not only has rheological and mechanical properties similar to those of natural nucleus pulposus, adapts to the mechanical environment of intervertebral discs, but also has tissue adhesion, can be adhered to soft tissues and avoid leakage, and also can inhibit lipid peroxidation of nucleus pulposus cells in the reactive oxygen species (ROS) environment, reduce cell ferroptosis and promote nucleus pulposus repair.

The invention relates to an image correction technology, and discloses a CBCT (cone beam computed tomography) image osteosclerosis artifact correction method, which comprises the following steps: acquiring a high-energy projection image and a low-energy projection image of a target object, performing image reconstruction, and calculating to obtain a primary artifact-free image; extracting a bone image and a soft tissue image from the primary artifact-free image based on threshold segmentation, calculating a bone weight, taking the artifact image of the target object as training input data, taking the bone image and the soft tissue image as reference data, and training to obtain a dual-channel artifact correction model; and outputting a preprocessed bone image and a preprocessed soft tissue image according to the to-be-processed osteosclerosis artifact image by using a dual-channel artifact correction model, and carrying out weighted fusion on the preprocessed bone image and the preprocessed soft tissue image according to a bone weight to obtain an artifact-free reconstructed image. The invention further provides a CBCT image osteosclerosis artifact correction device, electronic equipment and a storage medium. According to the invention, the image artifact correction effect can be improved.

The invention relates to the technical field of medical robot systems, and discloses a nerve plexus intelligent positioning anesthesia puncture robot system based on multi-modal fusion, which performs time-space synchronization on ultrasonic image flow and contact force data. The frequency domain analysis module extracts a main peak frequency by using optical flow field frequency domain transformation, and generates a probability mask for marking pulsatile tissues. The viscoelasticity verification module calculates phase lag parameters of visual deformation and contact force, identifies tissue rheological properties and calculates a dynamic damping coefficient. The deformation compensation module calculates a mechanical residual error based on a reference mechanical model, and inversely calculates the mechanical residual error into space deformation displacement of the tissue. The feedback control module combines the probability mask and the deformation displacement to generate a motion instruction. According to the invention, through multi-modal data fusion, precise identification of tiny blood vessels, dynamic identification of tissue attributes and real-time compensation of soft tissue conceding deformation are realized.

An orthopaedic knee prosthesis includes a tibial bearing component with articular features which operate to protect adjacent soft tissues of the natural knee, promote and / or accommodate desired articulation with an abutting femoral component, and facilitate expedient and effective implantation by a surgeon.

The invention provides a robot motion parameter determination method and device based on a puncture needle bending model, and relates to the technical field of minimally invasive surgery robots. The method comprises the steps that a puncture needle is used for puncturing a soft tissue simulation body, a medical image of the puncture needle is detected in real time, bending feature points of the puncture needle are obtained, and a bending model is established based on the obtained bending feature points; determining a conversion relation among a robot coordinate system, an image coordinate system and a bending coordinate system through calibration; and based on the puncture needle bending model, solving a forward kinematics model or an inverse kinematics model of the robot, and determining motion parameters of the robot. The problem that the puncture needle deviates from the preset track due to bending of the puncture needle in the puncture process can be solved, and the puncture accuracy is improved.