21 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 an MRI (Magnetic Resonance Imaging) image and CT (Computed Tomography) image registration method, which comprises the following steps of: S1, acquiring an MRI original image of an affected part of a patient before an operation, and performing vertebral segment segmentation on the MRI original image to obtain an MRI vertebral segment image; s2, acquiring a CT original image of an affected part of a patient before an operation, performing vertebral segment segmentation on the CT original image to obtain a CT vertebral segment image, and performing coarse registration on the CT vertebral segment image and the MRI vertebral segment image obtained in the S1; s3, according to the coarse registration in the S2, CT target slice images corresponding to all slice images in the MRI vertebral section image are intercepted from the CT vertebral section image; and S4, performing fine registration on the MRI image and the CT image based on a two-dimensional slice texture similarity description registration method by taking the coarse registration in the S2 as a reference and combining the S1 and the S3. According to the invention, skeleton and soft tissue information can be effectively fused, and real-time navigation support is provided for spine surgery.

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 discloses a spine spinous process distraction device, comprising: a distraction member comprising a seat body, a pair of side arms respectively protruding from two opposite sides of the seat body to form a first interface end, a shaft hole penetrating through the seat body, at least a positioning groove concavely arranged on the seat body, and a release hole penetrating through the shaft hole in a radial direction; the retaining piece comprises a first plate body part and a second plate body part which are parallel, two sides of the first plate body part and the second plate body part are respectively connected through an elastic arm, a second interface end is formed between the two elastic arms, and shaft parts are respectively arranged on the first plate body part and the second plate body part in a protruding manner and are used for penetrating into two opposite ends of the shaft hole; at least one positioning part is convexly arranged on the first plate body part or the second plate body part; a conical section is formed at the front end of the tripping rod, and the conical section is inserted into the tripping hole. The vertebral arch support can be attached between spinous processes and at the bottom of two adjacent vertebral sections in a better fit mode, supporting force between the two spinous processes is provided, and the supporting strength between the spinous processes and a vertebral arch plate is effectively improved.

The invention discloses a three-dimensional image data splicing method and device. The method comprises the steps that first image data and second image data are obtained, the first image data comprise image data of a first area of a target spine, the second image data comprise image data of a second area of the target spine, and the first area and the second area have an overlapping part; respectively and correspondingly segmenting image data of each vertebral segment in the first region and image data of each vertebral segment in the second region from the first image and the second image; comparing the image data of each vertebral segment in the first region with the image data of each vertebral segment in the second region, and determining a target vertebral segment; and according to the target vertebral segment, splicing the first image data and the second image data to obtain target image data. According to the method, registration and splicing are carried out by taking the segmented overlapped vertebral segments as guidance, so that the registration precision and the splicing effect of the image data can be improved.

The present disclosure relates to an apparatus and a method for measuring muscles for each part and detecting vertebral segments in a medical image. The apparatus comprises: a memory in which at least one process for performing muscle measurement for each part for an L3 slice in a CT image is stored; and a processor for performing an operation according to the process, wherein the processor generates each of a first muscle mask and a second muscle mask, marks an intersection region of the first muscle mask and the second muscle mask as an actual muscle, and divides the actual muscle into a plurality of regions to indicate the quality of the muscle for each region.

This paper proposes a deep learning-based method for vertebral center point detection in CT images. This model consists of two stages: a coarse segmentation stage and a center point detection stage. This two-stage model can detect the center points of any vertebra in spinal CT data at high resolution, without relying on manual operations such as selecting vertebral segments, thus achieving automated vertebral center point detection. Compared to other models, the proposed model offers significant advantages in detection accuracy and greater robustness.

The present invention relates to a vertebral system comprising a vertebral implant (2) and a plurality of inserts, said implant being designed to be implanted in a vertebral segment composed of at least two vertebrae and including a body (20) the walls whereof delimit a cavity (23) leading to the outside of the body (20) through at least one opening in at least one of said walls, at least one passage (21) passing through the implant (2) from the periphery to an upper or lower surface to receive a bone-anchoring device (1) capable of anchoring the implant (2) in at least one of said vertebrae, the system being characterized in that it includes at least two inserts selected from among the following inserts:at least one graft insert (3, 3A, 3B, 4, 5A, 5B, 6A, 6B, 6C, 6D, 202, 250) capable of being colonized by bone tissue and / or receiving at least one bone tissue graft and / or at least one substitute;and / orat least one bone-anchoring insert (210) comprising said passage (21) capable of receiving said bone-anchoring device (1).

The invention discloses a pedicle screw channel planning method and device. The method comprises the following steps: segmenting first image data of a target object to obtain image data of a target vertebral section, the first image data comprising image data of a spine area; performing three-dimensional surface reconstruction on the image data of the target vertebral section to obtain point cloud data of the target vertebral section; according to the point cloud data of the target vertebral section and a vertebral pedicle minimum section search algorithm, a target plane is positioned, and the target plane is the vertebral pedicle narrow portion minimum section of the target vertebral section; according to the target plane, determining a vertebral pedicle channel calibration point location of the target vertebral section; and determining spatial characteristics of the vertebral pedicle channel in the target vertebral section according to the vertebral pedicle channel calibration point location. According to the method, the planning scheme of the pedicle screw channel can be automatically generated according to the image data of the spine area, and the automation degree, adaptability and stability of an operation are improved.

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.

The invention relates to a vertebral segment image registration method and device, computer equipment and a storage medium. The method comprises the steps of obtaining a coarse registration transformation relation between a target vertebral segment segmentation result and a to-be-registered vertebral segment segmentation result according to the to-be-registered sagittal plane contour data of the target vertebral segment segmentation result and the to-be-registered vertebral segment segmentation result; performing pixel alignment on the target vertebral segment segmentation result and the to-be-registered vertebral segment segmentation result after coarse registration through a pixel alignment model, and setting a model evaluation standard, the model evaluation standard optimizes the coarse registration transformation relation according to the target vertebral section area loss value and the corresponding target vertebral section area weight of the pixel alignment model and the non-target vertebral section area loss value and the corresponding non-target vertebral section area weight of the pixel alignment model so as to perform fine registration on the preoperative three-dimensional image and the intraoperative three-dimensional image. According to the method, the global optimal solution can be quickly converged in the registration process, and the registration precision is improved.

The present disclosure relates to an apparatus and a method for measuring muscles for each part and detecting vertebral segments in a medical image. The apparatus comprises: a memory in which at least one process for performing muscle measurement for each part for an L3 slice in a CT image is stored; and a processor for performing an operation according to the process, wherein the processor generates each of a first muscle mask and a second muscle mask, marks an intersection region of the first muscle mask and the second muscle mask as an actual muscle, and divides the actual muscle into a plurality of regions to indicate the quality of the muscle for each region.

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.

A translaminar pedicle anchor suspension system (referred as T-PAS system) applicable to vertebral surgeries is disclosed. The T-PAS system comprises: at least one pedicle anchor capable of being fixed to a pedicle of a lower vertebral segment, at least one suspension ligament having one end thereof fixed to the pedicle anchor, and at least one washer capable of fixing the other end of the suspension ligament to a contralateral side of a lamina of an upper vertebral segment. By using the suspension ligament to suspend the upper vertebral segment via a tunnel drilled on the lamina, not only the spine can be dynamically stabilized, but also the use of traditional pedicle screws and bone fusion can be avoided.

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.