682 results about "Vertebral body" patented technology

The invention provides an L1-L4 lumbar vertebra segment-oriented multi-feature fusion diagnosis system and method, and the system comprises an image preprocessing module which is used for receiving a lumbar vertebra CT image sequence of a patient; a centrum anatomy partition module; the multi-dimensional image feature extraction module is used for extracting four types of quantitative features from each sub-region; the clinical multi-modal data coding module is used for independently acquiring and processing three types of clinical data: a multi-modal graph attention fusion network; and the segment-level diagnosis output module outputs diagnosis results of three levels. Through a parallel processing architecture and an optimized feature extraction algorithm, the whole diagnosis process only needs 45 seconds from data input to report generation, time is saved compared with manual film reading, and the consistency of diagnosis results is remarkably improved.

The invention provides an osteoporosis automatic diagnosis method and system based on position specific attention, and the method comprises the steps: carrying out the dual-channel enhancement preprocessing of a lumbar CT image, and generating an enhanced image taking the bone mineral density and the bone trabecula structure characteristics into consideration; inputting the enhanced image into a deep convolutional neural network for multi-scale feature extraction to obtain a feature map containing spatial semantic information; on the basis of the anatomical position index information, generating attention weighted features which highlight the key diagnosis area of the vertebral body; global pooling is carried out on the attention weighted features, and then comprehensive diagnosis features containing anatomical priori knowledge are constructed; and inputting the comprehensive diagnosis features into a classifier to realize centrum-level accurate diagnosis. According to the invention, the workload of radiologists can be effectively relieved, and the efficiency and coverage of osteoporosis screening can be improved. Especially under the condition that primary medical institutions are lack of experienced radiologists, the primary medical service level can be improved.

The embodiment of the invention provides a spine image recognition method and related equipment. The spine image recognition comprises the following steps: acquiring a spine image to be detected, and preprocessing the spine image to be detected to obtain a target spine image; the target spine image is input into a key point recognition model, position information output by the key point recognition model for each section of vertebral body in the target spine image is obtained, and the position information is marked on the target spine image and at least comprises positioning frame information, a vertebral body name and angular point coordinates; the key point identification model comprises a CBAM module; correcting and adjusting the position information to obtain corrected position information; and performing intervertebral disc positioning and vertebra identification according to the corrected position information. According to the technical scheme, the improved key point recognition model is adopted, the positioning frame, the cone name and the angular point coordinates are directly output without depending on a segmentation model, the process is simplified, and the detection speed and robustness are improved.

The embodiment of the invention is suitable for the technical field of computer-aided medical treatment and image processing, and provides an automatic planning device and equipment for a pedicle screw and a computer program product. Extracting vertebral body outer layer point cloud data of a to-be-planned single vertebral body from the spine image data; the prediction model is used for processing the centrum outer layer point cloud data and outputting prediction coordinates, and the prediction coordinates comprise entry point coordinates and exit point coordinates; and the planning unit is used for planning the placement position of the pedicle screw based on the entry point coordinate and the exit point coordinate. By adopting the device, the planned position of the pedicle screw can be quickly and accurately predicted by using the deep learning model based on the point cloud data of the outer layer of the vertebral body, the data volume needing to be processed in the planning process is reduced, and the planning efficiency is improved.

The invention provides a cortical bone screw automatic planning method and device based on a statistical morphology model. The method comprises the following steps: acquiring CT image data of any object; based on the CT image data, segmenting point cloud information of a vertebral body to be subjected to screw placement; acquiring a statistical shape model and cortical bone screw planning information corresponding to the serial number; and registering the statistical shape model to the point cloud information, and determining a cortical bone screw plan of the vertebral body to be subjected to screw placement. In the application, the preset screw placement planning of the cortical bone screw is performed through the statistical shape model, and the preset screw placement planning is mapped to the current spinal column three-dimensional model through registration, so that the preset screw placement planning only needs to be performed on the statistical shape model, and a screw placement model is not needed, thereby solving the problem that a large number of cases need to be collected to realize the screw placement model; therefore, the problem of nail placement of the cortical bone can be solved.

The invention specifically discloses an automatic generation method for a cervical vertebra disease rehabilitation prescription, and the method comprises the steps: constructing a cervical vertebra image feature automatic measurement system based on computer vision and deep learning, so as to monitor the training motion quality of a patient in real time, and obtaining the kinematics parameters of rehabilitation exercise training; acquiring a medical image and clinical data of a patient, and standardizing the medical image to construct a standard space of a multi-modal medical image; performing automatic segmentation and anatomical structure calibration on a vertebral body-intervertebral disc based on the standard space to obtain fusion image features; and constructing a multi-modal hierarchical decision model fusing the image features, the kinematics parameters and the clinical data to carry out quantitative analysis on pathological feature parameters, and outputting a standardized illness state assessment result conforming to international clinical guidelines. The dynamic optimization of the treatment scheme can be realized through a feedback mechanism, and the treatment effect is improved.

The invention provides a spine centrum compression fracture recognition method and system based on artificial intelligence, and the method comprises the steps: receiving original spine CT sequence data, and outputting a preprocessed standardized image; inputting the preprocessed image into a three-dimensional U-Net + + network to obtain a centrum segmentation probability graph; outputting the segmented centrum set and the position code thereof; for each segmented centrum, extracting a corresponding area based on a centrum mask, and splicing all features to form a comprehensive feature vector of each centrum; inputting the three-dimensional image block of each vertebral body into an image flow network to extract visual semantic features; and automatically generating a structured PDF report. According to the spine centrum compression fracture recognition method and system based on artificial intelligence, the problem of image quality difference caused by different CT devices and scanning parameters is effectively solved through the multi-scale residual enhancement technology and self-adaptive window level adjustment, and standardized processing of images is achieved.

An expandable interbody with a modular endplate has an outer column, an inner column threadedly coupled and translatable relative to the outer column along the longitudinal axis, and an expansion ring to adjust a body length of the expandable interbody. The expansion ring has a plurality of teeth, and the outer column has at least one arm for engaging a tooth of the plurality of teeth to lock the expansion ring. The inner column and / or outer column can include a connector for connection to a modular endplate that has a substantially hollow core. The modular endplate includes a plate with a set screw entrapped therein. The modular endplate has an aperture to receive the connector of the inner and / or outer column.

The invention discloses a CT-based osteoporosis intelligent diagnosis method and system, and relates to the technical field of medical image diagnosis, and the method comprises the steps: carrying out the positioning of a lumbar region in an abdomen or thoracic and abdominal CT image through a deep learning model; digitally modeling the shape and the internal structure of the vertebral body; and automatic diagnosis of osteoporosis is completed. According to the method, full-automatic positioning, accurate segmentation and intelligent diagnosis of osteoporosis of the lumbar region in a conventional abdomen or thoracic and abdominal CT image are realized, the accuracy and efficiency of diagnosis are remarkably improved, and the problems of strong subjectivity and poor repeatability caused by dependence on manual sketching or simple threshold segmentation in a traditional method are solved; the method can be directly operated based on clinical conventional CT data, is beneficial to large-scale osteoporosis screening and early intervention, and has remarkable clinical popularization significance and technical progress value.

The invention provides a multi-parameter feature fused vertebral CT image standardization preprocessing method and system. The method comprises the following steps: carrying out initial segmentation on an input original vertebral CT image; carrying out enhancement processing on the image by adopting an anisotropic diffusion filtering algorithm of multi-scale structure perception; establishing a tissue specificity density mapping model of multi-parameter fusion; adopting a self-adaptive segmentation histogram mapping method to map gray distribution of an original image to a standard template; and constructing a rigid-elastic mixed registration model. According to the invention, a complete quality evaluation system is established, the processing quality can be automatically detected and reported, and the reliability of an output result is ensured. By introducing a patient individualized correction mechanism, individual difference information is fully reserved while the standardization effect is ensured, and diagnosis information loss caused by excessive standardization is avoided. The multi-parameter fusion strategy ensures complete reservation of bone tissue density, texture and structure information.

The present technology includes patient-specific spinal fusion devices, which may include an interbody implant that is designed to be positioned within a disc space between two vertebral bodies and one or more fixation elements that can anchor the interbody implant to the vertebral bodies. The fusion devices include one or more retention mechanisms for retaining the fixation elements within corresponding lumens or bore holes extending through the interbody implant. Methods for designing and manufacturing patient-specific spinal fusion devices are also described herein.

The invention relates to the field of medical imaging analysis, and discloses a bone trabecula feature construction method and system, and the method comprises the steps: preferentially extracting a fragile region from an obtained vertebral image sequence, and generating an initial feature set representing the stability of a fine-grained structure; performing coherence comparison on the initial feature set in a cross-slice dimension to obtain a composite feature vector capable of reflecting the vulnerability level of the structure; based on the composite feature vector, a connectivity change curve of the bone trabecula in a loading environment is extracted by adopting a multi-layer progressive clustering mode, and candidate bone trabecula units with potential micro-damage trends are marked; classifying the candidate bone trabecula units according to risk gradients, and reconstructing a bone trabecula local topology network with weight levels; and according to the local topology network, identifying high-risk nodes showing an imbalance tendency in a specific mechanical simulation period, and generating a feature construction path finally used for micro-fracture risk prediction. The method has the advantage of improving the micro-fracture risk prediction sensitivity.

The invention relates to the technical field of bone implants for minimally invasive surgery, and particularly discloses an implant for percutaneous minimally invasive thoracolumbar vertebral fracture, which comprises a vertebral body forming body, the vertebral body forming body comprises a vertebral body forming body head and a plurality of blade parts arranged at the rear end of the vertebral body forming body head in a surrounding manner, the vertebral body forming body head is provided with a needle guide hole penetrating along the axial direction, and the needle guide hole is communicated with the blade parts; a containing cavity is defined by the blade parts; the front end of the threaded guide rod and the head of the cone forming body are integrally formed, the needle guide hole penetrates through the threaded guide rod in the axial direction, and the rear end of the threaded guide rod extends out of the containing cavity; the pedicle screw is provided with a threaded hole penetrating in the axial direction, the threaded hole is in threaded connection with the threaded guide rod, the pedicle screw comprises a screw head and a threaded part arranged at the rear end of the screw head, and the screw head is arranged in the containing cavity and expands the blade part. According to the implant for the percutaneous minimally invasive thoracolumbar vertebral fracture, surgical wounds are reduced, the vertebral restoration effect is good, the stability of a vertebral formed body is guaranteed, and the surgical time can be saved.

The utility model discloses a 3D printing porous pedicle screw which comprises a screw body part and a screw cap part, the screw body part comprises a cortical bone thread area close to one end of the screw cap part and a cancellous bone thread area far away from one end of the screw cap part, and a porous structure area is arranged at one end, not connected with the screw cap part, of the screw body part. The porous structure area comprises an inner core column extending in the axial direction of the nail body part, at least one reinforcing beam and a porous structure, the reinforcing beams extend outwards from the periphery of the inner core column, and the porous structure is annularly distributed on the outer periphery of the inner core column. The porous structure can efficiently induce bone tissue to grow in, the screw and a vertebral body are connected into a whole, stress is effectively dispersed, the stability of the screw is improved, the porous structure is arranged on the vertebral body at the front end of the screw, screw breakage caused by stress concentration of the screw in a vertebral pedicle area can be avoided, meanwhile, the stability of the screw can be better improved through the reinforcing beam, and the service life of the screw is prolonged. The possibility of fracture of a porous area of the screw is reduced, generalization performance is better, and the use experience feeling is improved.

This invention relates to a treatment device suitable for combined operative procedure of vertebroplasty and pediculoplasty. A treatment device includes a cylindrical driver capable of driving a screw into bone, an inner sleeve capable of being inserted into the driver, and a guide pin capable of being inserted into the inner sleeve, and is configured as follows. The screw includes on an outer wall (outer circumference) a thread that can tap into bone or cement, and a through hole that allows the inner sleeve to pass from a head to a tip. The driver can fit onto the head of the screw and when moved along the central axis and be joined to the screw, so as to transmit torque about the central axis to the screw. The inner sleeve includes a notch which protrudes, when the inner sleeve is inserted from the distal end of the driver in a state in which the screw and the driver are joined together, protrudes more proximally than a tip of the screw, preventing removal of the screw.

Minimally-invasive spinal surgery methods, devices, and systems for advancing a spinal implant through an oblique anterolateral retroperitoneal operative corridor to an intervertebral disc space located between the L5 and S1 vertebral bodies of a subject positioned in a lateral decubitus position are described. An example spinal implant system includes a retractor sized and shaped to establish at least a portion of the oblique anterolateral retroperitoneal operative corridor, a spinal implant sized and shaped to pass between the first and second unitary retractor blades of the retractor in connection with the spinal implant being introduced into the intervertebral disc space via the oblique anterolateral retroperitoneal operative corridor, and an introducer instrument configured to pass between the first and second unitary retractor blades of the retractor in connection with the introducer instrument introducing the spinal implant into the intervertebral disc space via the oblique anterolateral retroperitoneal operative corridor.

The invention discloses an image processing method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining to-be-processed three-dimensional medical image data, carrying out the spinal segmentation of a spinal region in the three-dimensional medical image data, and obtaining vertebral mask data; and performing cone identification processing on the cone mask data to obtain a target end cone mask corresponding to the Cobb angle, constructing a space vector model for the target end cone based on the target end cone mask, and determining a Cobb angle value for the target end cone based on the space vector model. According to the method, the Cobb angle is calculated by introducing space vector modeling, so that the measurement error of measurement of the Cobb angle can be remarkably reduced, and the accuracy of measurement of the Cobb angle is improved.

Expandable fusion devices, systems, instruments, and methods thereof. The expandable fusion implant may include an upper endplate and a lower endplate configured to engage adjacent vertebrae, an actuation gear configured to adjust a height of the upper endplate, an interface collar configured to attach to an inserter instrument at multiple orientations for a desired surgical approach, and an expansion and orientation lock configured to lock the orientation of the interface collar and lock the height of the upper endplate. The expandable fusion device is attachable to the inserter instrument to secure the interface collar and disengage the lock from the actuation gear to permit expansion of the upper endplate.

The utility model discloses a detachable bone drill for centrum forming. The detachable bone drill comprises a handle, a drill rod and a limiting piece. Wherein the handle is provided with a mounting groove, the handle is further provided with a first limiting hole, and the first limiting hole is communicated with the mounting groove; the drill rod comprises a drill bit, a drill rod main body and a fixing part which are integrally connected, the drill bit is used for cone drilling, the fixing part is detachably mounted in the mounting groove and provided with a limiting structure, the limiting structure is used for limiting rotation of the fixing part relative to the handle, and the limiting piece is detachably mounted in the first limiting hole; the limiting piece is used for limiting the fixing part to move in the first direction relative to the handle. According to the detachable bone drill for centrum forming, the handle and the drill rod can be conveniently assembled and disassembled, only the drill rod needs to be scrapped, and the handle can be repeatedly used, so that the difficulty of a scrap treatment process and the cost of scrap treatment are reduced, and the production cost is saved; rotation or movement of the drill rod is limited through the limiting structure and the limiting piece, and therefore the cone drilling effect is guaranteed.

The present invention relates to a spinal fusion cage which is inserted between vertebral bodies in a state where the cage has the lowest height, is height-adjustable in the inserted state, and can simplify a height adjustment mechanism, thus making it possible to replace cages having heights in a certain range by a single cage. Therefore, manufacturers can reduce product groups that need to be produced, and can also reduce product stock. Further, in contrast to the conventional cages having predetermined heights at regular intervals, the height of the inventive cage can be linearly adjusted according to the distance between the vertebral bodies of a patient, and thus a surgery can be performed using the cage adjusted to an optimum height according to the patient's condition.

The invention relates to a spine bone structure and bone mineral density automatic measurement method based on a CT image. The method comprises the following steps: performing CT scanning on a phantom with known bone mineral density to obtain a real bone mineral density calculation formula; all CT images in the DICOM format are read, DICOM analysis is carried out, and three-dimensional CT value data and other main information of all the images are obtained; performing outer contour segmentation on the whole spine in the CT image by using a deep learning network to obtain an outer contour of each vertebral body in the image; the method comprises the following steps: carrying out preliminary segmentation on cortical bones and cancellous bones by adopting a dynamic threshold method aiming at each vertebral body, selecting a preliminarily segmented cancellous bone region, using a maximum connected domain algorithm in a three-dimensional direction, retaining a maximum connected region, and further measuring the bone mineral density, namely calculating overall topology parameters, the bone mineral density and the bone mineral content of the current vertebral body; calculating the rubbing parameters, the bone mineral density and the bone mineral content of the current vertebral cortical bone and cancellous bone; and measuring the content of the cross section of the cone.

A method of providing a guidance device for guiding a bone removal instrument for the removal of bone from a cervical vertebra and providing a vertebral body replacement device for placement into a void in a cervical spine between two endplates of a single vertebra during the course of an anterior spinal surgical procedure upon the cervical spine wherein the vertebral body replacement device has been given a PLR product code from the Food and Drug Administration (FDA).

Proposed is a vertebral cage including a body which is inserted between a vertebra and a neighboring vertebra, and is provided with a space part that can be filled with bone powder; a blade which is rotatably provided on an inner side surface of the body. The cage also includes a locking means which fixes the blade, which has or has not been rotated on the body, on the inner side surface of the body, wherein the locking means comprises fixing protrusions and groove parts which are provided on mutually facing surfaces of the body and the blade, and coupled to each other.

The invention provides an X-ray-based scoliosis 3D intelligent automatic diagnosis system, which is characterized in that a spine area bounding frame coordinate, a hip bone bounding frame coordinate and a vertebral pedicle bounding frame coordinate are extracted from spine coronal image data, and the first 17 results are extracted to be matched with the number and spatial distribution of typical vertebral bodies of a human body; the method comprises the following steps: obtaining a spine region sub-graph, a hip bone region sub-graph and a vertebral pedicle region sub-graph, converting the sub-graphs into tensors to obtain a bounding box, four angular point coordinates and corresponding confidence of each vertebral body, storing the bounding box, the four angular point coordinates and the corresponding confidence as a structured record, performing Cobb angle calculation according to the structured record, and converting the structured record into an anatomical segment identifier; cutting is conducted according to the spine area, the hip bone area and the vertebral pedicle area subgraph, segmented vertebral pedicles and hip bones are obtained, the major curvature type, the pelvis height and the rotation direction are judged according to anatomical segment identifiers, and the patient age is determined according to the midpoints of the upper edges and the lower edges of the vertebral bodies, the arrangement angle of the adjacent vertebral bodies, spine major curvature core parameters and the age of the patient. And outputting a scoliosis 3D intelligent automatic diagnosis result.

Described herein are various implementations of systems and methods for treating back pain (e.g., chronic low back pain) caused by different (e.g., independent) sources of pain, such as pain originating or stemming from intervertebral discs, from vertebral endplates, and / or from intraosseous locations within one or more vertebral bodies. For example, methods for treating back pain (e.g., chronic low back pain) may involve both vertebral fusion (e.g., arthrodesis or spondylodesis to fuse adjacent vertebrae) and neuromodulation (for example, ablation of nerves within or surrounding one or more of the adjacent vertebrae). The neuromodulation may facilitate treatment of pain that is generated by insertion of fusion hardware.

A system and method for predicting spinal motion and vertebral locations and movement in surgeries through training and using predictive models generated using biomedical profiles of patient spines and surgical patient-specific features. A trained predictive model is used in combination with patient-specific features associated with a surgical patient such that during a real-time surgery the patient-specific features are provided to the trained predictive model and a segmental motion model is created. Using this real-time surgical data and interoperative data, the trained predictive model is updated which then used for updating the segmental motion model such that the updated segmental motion model may be used for producing a series of vertebral location predictions specific to movements and location of the spine of the surgical patient that may be provided to a surgical guidance system for use in performing the real-time surgery in accordance with a surgical plan.

A system for surgical planning and assessment of spinal pathology or spinal deformity correction in a subject, the system comprises a control unit configured to align one or more vertebral bodies of a biomechanical model to one or more vertebral bodies of the radiograph. The control unit is configured to receive one or more spinal correction inputs. The control unit is configured to, based on the received one or more spinal correction inputs, simulate the biomechanical model in a predetermined posture. The control unit is configured to provide for display one or more characteristics of the simulated biomechanical model.

The invention discloses a patient-specific finite element model-based vertebroplasty optimization method and a related device. The method comprises the following steps of: constructing a patient-specific three-dimensional spine model according to a vertebral bone structure and a vertebral soft tissue structure; discretizing the patient-specific three-dimensional spine model into tetrahedral finite element grids, endowing each finite element unit with bone material attributes according to pixel values of CT scanning images, and endowing intervertebral disc and ligament soft tissue structures with soft tissue material attributes; determining an optimal bone cement injection path and an optimal bone cement injection amount of the tetrahedral finite element mesh; and simulating the vertebroplasty in the tetrahedral finite element mesh, predicting the stress distribution of the vertebrae, the rigidity of the vertebrae and the stress change of the adjacent vertebrae after the operation, and presenting the simulation result of the simulated vertebroplasty in a three-dimensional visual form. According to the method, personalized optimization and prediction of preoperative simulation of the vertebroplasty are realized by constructing the patient-specific finite element model, and an efficient auxiliary reference operation scheme is provided for an operator.

The invention relates to a spinal degenerative disease grading early warning and rehabilitation management system and method, and belongs to the technical field of medical equipment. The system comprises a system control module, a first-stage detection module, a second-stage detection module, a third-stage detection module, a data processing module, an evaluation module and a rehabilitation management module. The first-stage detection module is used for acquiring foot pressure distribution data of a patient; the secondary detection module collects electromyographic signal data of muscles around the spine of the patient; the third-stage detection module is used for collecting vertebral bone mineral density data of the patient. The data processing module is used for preprocessing and analyzing the collected data; the evaluation module is used for carrying out grading evaluation on the spinal degenerative lesion; and the rehabilitation management module formulates a personalized rehabilitation scheme according to the evaluation result. The system adopts a logic mechanism of hierarchical detection and hierarchical intervention, automatically adjusts intervention measures according to different evaluation indexes, and realizes accurate rehabilitation management. The risk of spinal degenerative diseases is found in an early stage, a targeted rehabilitation scheme is provided, and spinal diseases are effectively prevented and managed.