11 results about "Vertebral segment" patented technology

The application relates to a spine structure image template generation method, a spine image analysis method and device, and the method comprises the following steps: acquiring a set of vertebral region image data; registering each vertebral region image in the set of vertebral region image data in sequence to obtain target image data corresponding to each vertebra; and based on the position of the vertebra in the vertebral segment, the target image data is summarized to obtain a spine structure image template. Compared with the prior art, the technical scheme based on the application can obtain a spine structure image template with higher efficiency, and the spine structure image template obtained based on the technical scheme of the application can more accurately reflect the vertebral structure distribution.

The present invention provides an image data processing method, a device, and a storage medium. In the present invention, the problem of registering a whole spinal segment medical image is decomposed into segmentation, pose transformation, and stitching processing of a plurality of vertebral segments, significantly reducing the computational complexity and technical overhead of direct registration of the whole segment. In the process, a first modality medical image and a second modality medical image are utilized, each having respective characteristics in bone and soft tissue imaging, to achieve precise segmentation of the vertebral segments; a pose transformation information set is determined on the basis of a segmentation result, and calculation of a transformation matrix is further optimized, ensuring the efficiency and accuracy of a registration process; and finally, weighted fusion stitching is performed on a transformed segmentation data set to generate a complete registered image, overcoming the defect of excessive computational burden caused by overall processing in related technologies, so that the method has the characteristics of strong real-time performance and wide applicability, and is particularly suitable for application scenarios of intraoperative real-time registration.

The invention discloses a centrum collapse end plate area identification method, which comprises the following steps: S1, acquiring a vertebral section image of a single vertebral section, and performing centrum hole center segmentation along the left-right direction of a human body to obtain a centrum image; s2, recognizing the front and rear edge end face directions of the vertebral body according to the vertebral body image obtained in the S1; s3, respectively defining a front edge plane and a rear edge plane according to the front edge end face direction and the rear edge end face direction of the cone and a point on the front edge plane and the rear edge plane obtained in the S2, and respectively translating a set distance into the cone along the corresponding normal directions by taking the defined front edge plane and the defined rear edge plane as references to obtain a front edge interception plane and a rear edge interception plane; and S4, respectively obtaining areas formed by points on the front end plate and the rear end plate of the cone obtained in the step S3, wherein the distance between the points and the corresponding front edge interception plane and the rear edge interception plane is greater than a set collapse distance threshold value, and the areas are corresponding collapse areas of the front end plate and the rear end plate. According to the invention, the corresponding front and rear end plate collapse areas on the front and rear end plates of the vertebral body can be automatically identified, the operation efficiency can be effectively improved, the treatment effect is optimized, and the pain of a patient is relieved.

The invention provides an image data processing method and device and a storage medium. According to the method, the medical image registration problem of the whole segment of the spine is decomposed into segmentation, pose transformation and splicing processing of a plurality of vertebral segments, so that the calculation complexity and the technical overhead of direct registration of the whole segment are remarkably reduced. According to the method, accurate segmentation of vertebral segments is realized by utilizing respective characteristics of a first modal medical image and a second modal medical image on bone imaging and soft tissue imaging; a pose transformation information set is determined based on a segmentation result, calculation of a transformation matrix is further optimized, and high efficiency and accuracy of the registration process are ensured; finally, the complete registration image is generated by performing weighted fusion splicing on the transformed segmented data set, so that the defect of overweight calculation burden caused by overall processing in the related technology is overcome, and the method has the characteristics of high real-time performance and wide applicability, and is particularly suitable for an application scene of real-time registration in an operation.

This invention discloses an anisotropic piezoelectric film for nerve repair and its preparation method, belonging to the field of biomedical materials technology. The anisotropic piezoelectric film for nerve repair provided by this invention has a surface with parallel, periodically repeating wavy folds; the wavelength of the wavy folds is 30-50 μm, and the height difference between the peaks and troughs is 10-30 μm; the anisotropic piezoelectric film is an organic piezoelectric polymer film with a thickness of 5-100 μm. The anisotropic piezoelectric film for nerve repair provided by this invention has a regular structure and high orderliness and anisotropy, which can accurately simulate the parallel arrangement of nerve fiber bundles in vivo, exhibiting excellent biomimetic effects. This facilitates the bridging growth of new axons along the injured vertebral segment, avoiding disordered axonal growth.

This invention discloses a method for segmenting vertebral body point clouds in three-dimensional images, comprising: converting a three-dimensional image containing the spine into a three-dimensional point cloud, and filtering to obtain point clouds of vertebral body regions; projecting the point clouds of vertebral body regions along the left-right direction of the human body, sampling a set distance from the vertebral body direction to the spinous process direction on the projected image to obtain a sampling image range, filtering the three-dimensional point cloud with the sampling image range and generating a projected image, thereby obtaining the minimum bounding rectangle of the vertebral body region of each vertebral segment; and extending and filtering the three-dimensional point cloud according to the minimum bounding rectangle to obtain the point clouds of each vertebral body. This invention can quickly complete the segmentation of multiple vertebral body three-dimensional regions in a three-dimensional image, which is more convenient for surgical path planning and surgical registration and positioning operations, and has a wide range of applications in the field of orthopedic surgical assistance planning.

This invention discloses a method for designing and fabricating a personalized artificial intervertebral disc prosthesis, belonging to the field of artificial intervertebral disc prosthesis technology. The invention aims to solve the problems of poor mechanical adaptability, lack of biomimetic structure, and design-manufacturing disconnect in existing prostheses. The steps include: S1, collecting kinematic and dynamic data of the lumbar spine under healthy conditions to obtain the torque-rotation curve of the target vertebral segment; S2, establishing and validating a finite element model based on MRI / CT, ​​with motion deviation within 5%; S3, constructing a biomimetic intervertebral disc including a biomimetic nucleus pulposus, transition zone, annulus fibrosus, and endplate, wherein the number, diameter, stiffness gradient, and arrangement of biomimetic fibers are adjustable; S4, establishing a quadratic regression equation with the target curve as the optimization target to obtain optimal parameters with a matching degree ≥90%; S5, using multi-material additive manufacturing for integrated molding. This invention achieves individualized stiffness matching and biomimetic structure reproduction, improves fatigue and shear resistance, and is suitable for personalized customization of the lumbar spine.

The invention provides a training method and device of a lightweight multi-mode spine model with centrum segment perception, a terminal, a medium and an analysis method. According to the invention, low-cost localization deployment is realized by constructing the lightweight multi-mode architecture. Meanwhile, through specific data input and a progressive three-stage training strategy, a lightweight model with the spine specialized ability is constructed and trained, and then a more accurate spine image analysis result is obtained.

This disclosure relates to the field of medical device technology, specifically to an intervertebral fusion device, comprising a base plate, the base plate including a first base plate and a second base plate, the first base plate and the second base plate being disposed vertically opposite each other; a first connecting post, the first connecting post being pivotally connected to one of the base plates in a vertically floating manner to provide a degree of freedom of relative vertical movement between the first base plate and the second base plate, and a degree of freedom of rotation relative to a pivot axis along a plane parallel to the first base plate. It can adjust different heights and angles for patients with different intervertebral spaces, can rotate appropriately with the patient's vertebral body movement, has a strong bonding force with the vertebral body, and can be stably fixed between vertebral segments, ultimately achieving a balance between segmental fusion and segmental freedom.

This invention relates to the field of fracture risk prediction technology, and more particularly to a risk prediction system for osteoporotic vertebral compression fractures based on DES-DXA-MRI fusion. The data acquisition module acquires the patient's DES image data, DXA detection data, MRI image data, and clinical risk factor data. The data fusion module generates a multimodal fusion feature set containing both image modality features and clinical modality features. The risk prediction module calls a pre-trained multimodal fracture risk prediction model to predict the fracture risk probability, risk contribution factors, and development trends of each vertebral segment, generating a risk assessment result set. The network construction module constructs a vertebral fracture risk assessment network based on the assessment results, including the vertebral segment topology, risk factor association weights, and time-series evolution paths. The risk warning module generates a fracture risk warning instruction set and sends it to a clinical decision support platform to achieve accurate prediction and personalized intervention.

The invention discloses a method for evaluating lumbar vertebra aging based on a lumbar vertebra age estimation network of slice contrast learning, mainly solving the problem that the prior art cannot meet individualized and continuous quantitative early warning of precision medical treatment, and the scheme comprises the following steps: obtaining a lumbar vertebra MRI image and dividing the image into a training set and a test set; training and testing an existing segmentation network to obtain a segmentation result of the lumbar anatomical structure, and performing grouping cutting on the segmentation result according to lumbar segments to obtain a lumbar anatomical structure image data set; dividing the cut images of the first lumbar vertebra, the second lumbar vertebra and the third lumbar vertebra into a training set and a test set for lumbar vertebra age estimation; constructing a lumbar vertebra age estimation network of slice contrast learning, and training the lumbar vertebra age estimation network by using a lumbar vertebra age estimation training set; inputting the lumbar vertebra age estimation test set into the trained lumbar vertebra age estimation model, and outputting a predicted age result and a lumbar vertebra age estimation significance heat map; and according to an age prediction result, evaluating a degenerative aging risk result of different anatomical regions of the lumbar vertebra. According to the method, automatic segmentation of the lumbar intervertebral disc anatomical structure and estimation of the lumbar vertebra age can be realized, and the method can be used for lumbar vertebra age and senescence risk assessment and early risk early warning.