1399 results about "Vertebral body" patented technology

The invention relates to the technical field of image processing, and provides a vertebral body three-dimensional reconstruction method based on image segmentation, and a bone detection method and system.The method comprises the steps that firstly, an SAD-UNetR image segmentation model capable of achieving accurate segmentation of an image target is constructed through improvement of a Swinin-UNetR network, three-dimensional modeling is conducted on the basis of an accurate segmentation image, and a three-dimensional reconstruction model is obtained; an accurate three-dimensional model of a vertebra structure can be obtained; based on an accurate segmentation result, a bone mineral density prediction regression model is provided at the same time, bone substances are identified based on multi-instance learning and an attention mechanism, a bone substance classification result and bone mineral density data can be provided, intelligent assistance is provided for diagnosis of doctors, radiation risks, economic consumption and time consumption caused by special bone mineral density measurement are avoided, and the accuracy of bone mineral density measurement is improved. Measurement means of bone detection are expanded, and the method has a wide application prospect.

A single vertebra segmentation method, device, equipment and storage medium. The method comprises: acquiring first spine boundary information, which is boundary information of a spine in a segmentation result obtained through image segmentation of a raw CT image; acquiring first vertebra position information, which is information on the position of a single vertebra in the spine in the raw CT image; acquiring an initial image of the single vertebra according to the first spine boundary information and the first vertebra position information; marking the position of the single vertebra in the initial image of the single vertebra to generate an updated image of the single vertebra; and determining the single vertebra in a restored image corresponding to the raw CT image according to the updated image of the single vertebra. According to the present application, the spine in the CT image can be segmented on a single segment basis.

The invention belongs to the technical field of medical implant prostheses, and particularly relates to a self-stability cervical interbody fusion cage which comprises a fixing plate and a fusion cage body. An adjusting rod is mounted in the fusion cage main body, a mounting groove is formed in the fusion cage main body, the adjusting rod and a sliding block are mounted in the mounting groove, a check block is mounted on the adjusting rod, and the check block drives the sliding block to move; an adjusting groove is formed in the fusion cage body, a connecting plate and a protruding tooth rod are installed in the adjusting groove, a contact plate is installed on the connecting plate, and a top block and a sliding block are connected through a pull rope; when the interbody fusion cage is implanted, the protruding toothed rod retracts, the surface of the protruding toothed rod is kept flat and smooth, implantation of the interbody fusion cage is facilitated, extrusion, friction and scratching are avoided, then after implantation, the protruding toothed rod stretches out, friction force between the interbody fusion cage and the vertebral body end plate is increased, and it is guaranteed that the fixing effect and stability of the interbody fusion cage are good; the treatment effect is improved.

The invention discloses an in-vitro bionic mechanical testing system and method for spinal skeletal muscles, and particularly relates to the field of mechanical testing, and the system comprises a bionic construction module, a finite element modeling module, a multi-axis mechanical loading module, an iterative calculation module and a correction module; through modular design, the system comprises a vertebral body unit, an intervertebral disc simulation assembly and a skeletal muscle simulation unit, each assembly is customized according to anatomical features of a human body, a finite element modeling module is utilized to generate a three-dimensional model, a multi-directional mechanical load is applied, and response data is collected; experimental data are input into the finite element model for iterative calculation, so that stress distribution, a strain field and kinematic deviation are compared; if the error exceeds a preset threshold value, the model parameters and the physical parameters are corrected until the experiment and simulation results converge; and finally, based on the optimized finite element model, predicting a failure mechanism of the spinal skeletal muscle under a complex load, and evaluating the risks of fracture, hairline fracture, nucleus pulposus protrusion and muscle strain.

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 discloses a CT image segmentation method for spine surgery, and relates to the technical field of medical image processing, and the method comprises the steps: obtaining a spine CT image of a patient, and carrying out the preprocessing of the spine CT image; adopting a centrum gap detection method to detect a centrum gap region of a spine in the preprocessed CT image, and performing automatic segmentation on each centrum based on centrum gap region information to obtain a preliminary segmentation result of the centrum; extracting local texture features of the intervertebral disc and the nerve root in the intervertebral space area, and classifying the local texture features through a classifier to generate a preliminary segmentation result of the intervertebral disc and the nerve root; performing rigid registration and non-rigid registration on the initial segmentation results of the vertebral body, the intervertebral disc and the nerve root and the standard three-dimensional model, and identifying an abnormal region in segmentation; by extracting local texture features of the intervertebral disc and the nerve root and combining a support vector machine classifier, accurate segmentation of various structures can be realized.

The embodiment of the invention provides a scoliosis Cobb angle determination method and device based on Mama, equipment and a storage medium. The method is applied to the scoliosis prediction field. The method comprises the following steps: acquiring image information, and preprocessing the acquired image information to obtain an original image; performing multi-level local feature extraction on the original image through an encoder to obtain a first feature map; performing global feature capture on the first feature map through a Mama module to obtain a second feature map; decoding the second feature map through a decoder to obtain a target feature map; generating, by a prediction module, a central heat map, an offset map and a centripetal vector map based on the target feature map; according to the central heat map, the offset map and the centripetal vector map, extracting central point coordinates of the centripetal body, and according to the central point coordinates of the centripetal body, determining four angular point coordinates of the centripetal body; the Cobb angle is determined through a geometric algorithm according to the coordinates of the four angular points of the cone, and the measurement precision of the Cobb angle is improved.

The invention discloses a spine Cobb angle measuring method and device and electronic equipment, and the method comprises the steps: inputting a to-be-measured spine image into a body position recognition model, and obtaining a spine shooting body position of the to-be-measured spine image outputted by the body position recognition model; inputting the to-be-detected spine image into the target detection model to obtain a spine region image of a spine in the to-be-detected spine image output by the target detection model; inputting the spine area image into a key point identification model corresponding to the spine shooting body position to obtain position information output by the key point identification model to each section of vertebral body of the spine; and calculating a spine Cobb angle in the spine area image according to the position information of each section of vertebral body. A complex vertebral body recognition task is split and refined, different lightweight models are respectively trained and used for completing tasks of all stages, the tasks comprise body position recognition, spine coarse positioning and key position recognition, precise positioning of a vertebral body from coarse to fine is gradually completed in each link, and the precise positioning of the vertebral body from coarse to fine is completed. And finally, completing Cobb angle calculation based on precise positioning of the vertebral body in the image.

The invention relates to the technical field of medical instruments, and discloses an additive manufacturing bionic bone trabecula full-porous interbody fusion cage which is applied to spinal fusion surgery and is of a bionic bone trabecula full-porous structure made of medical metal through a laser melting or electron beam melting additive manufacturing technology. The interbody fusion cage comprises a front end face, a rear end face, a first side surface, a second side surface, an upper fusion face and a lower fusion face, the upper fusion face and the lower fusion face make direct contact with a vertebral body end plate of a spine, anti-skid teeth are arranged on the surfaces of the upper fusion face and the lower fusion face, and a bone grafting window penetrating through the upper fusion face and the lower fusion face is formed in the center of the interbody fusion cage. The interbody fusion cage has the structure and mechanical property similar to those of cancellous bone and trabecular bone of a human body, can improve the bone combination area and bone ingrowth space, has excellent initial and long-term stability, and can effectively reduce stress shielding so as to improve the bone fusion capability.

The invention relates to the technical field of image processing, in particular to a lumbar vertebra osteoporosis auxiliary detection method and system based on an X-ray film. The method comprises the following steps: acquiring a lumbar vertebra X-ray film image; in combination with shape distribution of edge lines in the lumbar vertebra X-ray film image, determining a vertebral body area; based on the difference condition of the position distribution of each pixel point and the similar pixel points thereof, obtaining the influence degree value of skeleton overlapping on each pixel point; obtaining a difference index corresponding to each pixel point in the centrum region according to the difference between each pixel point in the centrum region and the standard gray level of the normal centrum region; and in combination with the influence degree value and the difference index, obtaining a lumbar vertebra osteoporosis evaluation value, and further obtaining an accurate auxiliary detection result of the lumbar vertebra osteoporosis. The accuracy of the judgment result of the suspected osteoporosis condition is improved.

Various embodiments of bone ties, bone tie inserters, and methods for treating the spine are provided. The methods can include wrapping the bone tie around transverse processes of adjacent vertebrae to correct coronal plane deformity. The methods can include wrapping the bone tie around the spinous process of one vertebra and around the transverse process of a second adjacent vertebra to achieve rotational correction. The methods can include wrapping the bone tie around the lamina of adjacent vertebrae to achieve sagittal correction. The methods can include applying tension to the bone tie to set the sagittal correction. The methods can include passing the bone tie through a lumen in a vertebral body or a pedicle of the inferior vertebra and the lamina or articular process of the superior vertebra.

The invention provides a bone cement injection anti-leakage planning method, system and device for spine centrum compression fracture and a computer readable storage medium. The bone cement injection anti-leakage planning method for the spine centrum compression fracture comprises the steps that a spine CT image of a patient is acquired; performing identification and segmentation based on the spine CT image to obtain a fracture centrum CT image of the spine centrum compression fracture part; carrying out three-dimensional reconstruction on the fracture centrum CT image to obtain a fracture centrum three-dimensional model; inputting the three-dimensional model of the fractured vertebral body into a preset bone cement anti-leakage planning model, and outputting a bone cement injection anti-leakage planning scheme; wherein the bone cement injection anti-leakage planning scheme at least comprises the viscosity, the injection amount, the injection position, the injection opportunity and the injection rate of the bone cement. According to the embodiment of the invention, the anti-seepage planning of bone cement injection can be carried out quickly and accurately.

A method to treat sacroiliac joint pain includes inserting at least one ablation electrode into a patient to ablate at least one spinal nerve extending from the spinal cord in the vertebral range of the lumbar vertebrae L3, L4, or L5 or any of the sacral vertebrae; and applying pulses to the at least one ablation electrode to ablate the at least one nerve, wherein each of the pulses has a duration of no more than 500 microseconds and at least some of the pulses have a voltage of at least 1 kV or generate an electric field of at least 3 kV / cm.

A method for basivertebral nerve ablation includes inserting at least one ablation electrode into a vertebral body of a patient; and applying pulses to the ablation electrode to ablate the basivertebral nerve within the vertebral body, wherein each of the pulses has a duration of no more than 500 microseconds and at least some of the pulses have a voltage of at least 1 kV or generate an electric field of at least 3 kV / cm.

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 personalized adjustable artificial vertebral body, and belongs to the technical field of medical instruments. An end plate adjustable rod; the sliding groove is formed in the end plate adjustable rod; the external thread is fixedly connected between the inner walls of the two sides of the end plate adjustable rod, and the external thread is located in the sliding groove; the notch and the structure are designed individually, customization can be carried out according to the requirements of different patients, and better adaptability and clinical effects are provided; the angle adjusting function is achieved, and the angle of a vertebral body can be adjusted through combination of an end plate adjusting rod and an external thread; the length can be adjusted, and personalized adjustment of the length of the vertebral body is achieved through cooperation of the adjusting nut and the adjusting screw rod; the stability is high, the stability of initial implantation is provided by a spine and a support frame structure, and bone induction and long-term fixation fusion are promoted in a bone trabecula area; the operation is simple, the use method is clear, and doctors can perform surgical operations conveniently.

A vertebral body replacement system having a quick-connecting removable endplate connection mechanism.

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 discloses a pedicle screw path planning method. The pedicle screw path planning method comprises the steps of S1, performing image segmentation on a spine structure model to obtain a 3D voxel map of a target vertebral body and a pedicle; s2, determining an initial screw radial direction and an initial screw radius by combining the 3D voxel maps of the target vertebral body and the vertebral pedicle; s3, optimizing the initial screw radial direction and the initial screw radius in combination with the vertebral pedicle point cloud to obtain a screw radial parameter and a screw radius parameter; s4, calculating coordinates of a screw inlet point and a screw outlet point of the pedicle screw based on the radial parameters of the screw in combination with the centroid coordinates of the pedicle; and S5, simulating the swinging range of the universal nail head based on the coordinates of the nail outlet point to judge whether the nail rod penetrates through all the pedicle screws on the same side or not, if so, determining a planned path, and if not, iteratively executing the steps S3 to S5 until the nail rod penetrates through all the pedicle screws on the same side. According to the scheme, the problems of low efficiency and low success rate of pedicle screw placement and rod penetration operations are 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.

A system and method for planning and simulating a surgical operation to create a patient-specific spinal implant are disclosed. The system comprises a remote server configured to receive patient-specific medical image data and generate a 3D mesh model of the patient's spine using algorithms that separate vertebral bodies, remove artifacts, and smooth surfaces. A doctor's computer receives the 3D mesh model and allows real-time manipulation of intervertebral spaces to achieve a desired spinal curvature. The server generates a spinal implant design with surface-mapped endplates matching the patient's vertebral anatomy, which is transmitted to a 3D printer for manufacturing. The method includes steps of receiving image data, generating and updating the 3D mesh model based on doctor input, generating the final implant design, and transmitting it for production. The invention enables the creation of patient-specific spinal implants with improved conformity and surgical outcomes.

The invention discloses an image recognition system for constructing osteoporotic vertebral fracture healing based on artificial intelligence, and particularly relates to the technical field of orthopedic treatment, which comprises a data preprocessing module for extracting and optimizing data from an original medical image. According to the method, the advantage of discipline crossing is developed, a recognition system on medical imaging is developed based on deep learning, the advantage that the recognition system can discover detail features and hidden rules which cannot be found by human beings is utilized, and then a large amount of structured data is utilized to automatically learn and train visual feature expression of abstract data, so that the clinical missed diagnosis rate is reduced, and the clinical diagnosis efficiency is improved. The artificial intelligence architecture is trained by a rigorous and scientific means, so that the artificial intelligence architecture has clinical experience and knowledge of high-age dominant doctors and is popularized in local hospitals to achieve an auxiliary diagnosis effect, the difference of medical differentiation is reduced, the technical and experience defects of local medical personnel are made up, and the technical and experience defects of the local medical personnel are overcome. The aim of improving the definite diagnosis rate of diseases and reducing the missed diagnosis rate is one of the purposes of the invention.

The embodiments provide various interbody fusion spacers, or cages, for insertion between adjacent vertebrae. The cages may have integrated ratchet assemblies that allow the cage to change size and angle as needed, with little effort. The cages may have a first, insertion configuration characterized by a reduced size to facilitate insertion through a narrow access passage and into the intervertebral space. The cages may be inserted in a first, reduced size and then expanded to a second, larger size once implanted. In their second configuration, the cages are able to maintain the proper disc height and stabilize the spine by restoring sagittal balance and alignment. Additionally, the intervertebral cages are configured to be able to adjust the angle of lordosis, and can accommodate larger lordotic angles in their second, expanded configuration. Further, these cages may promote fusion to further enhance spine stability by immobilizing the adjacent vertebral bodies.

Intervertebral spacer implants with dynamic load spreading features responsive to external loads and having attachment mechanisms. The dynamic load spreading features having a native state and a loaded state, which complements vertebral end plate geometry and disperses load to the epiphyseal rim.

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 spine Cobb angle prediction method based on centrum segmentation. The spine Cobb angle prediction method comprises the following steps: acquiring an X-ray image of a spine to be measured; inputting the X-ray image into an encoder to obtain a feature map of the X-ray image; inputting the feature map into a spine decoder to obtain a spine segmentation mask; inputting the feature map into a vertebra decoder to obtain a vertebra segmentation mask; performing center line prediction according to the spine segmentation mask to obtain center line representation of the spine; performing feature extraction according to the vertebra segmentation mask to obtain a target feature vector; the target feature vector is used for representing the form and structure information of each vertebra; and according to the center line representation and the target feature vector, predicting to obtain a target Cobb angle corresponding to the X-ray image of the spine to be measured. According to the method, the overhigh dependence on data quality can be reduced, the prediction capability under various image qualities is improved, the time consumption of manual operation is reduced, the accuracy is improved, and the robustness and interpretability of Cobb angle prediction are enhanced.