638 results about "Vertebra" patented technology

A clinical vertebra image segmentation method for assisting pedicle screw placement surgery, said method comprising: constructing a VerseDiff-UNet end-to-end framework, the framework being integrated with a denoising diffusion probabilistic model (DDPM); combining a noise-added image with a marked mask by using the VerseDiff-UNet framework, and guiding a diffusion direction toward a target region; and introducing a shape priors module on the basis of the DDPM, and extracting structural semantic information from an input spine image. In order to capture specific anatomical prior information in a medical image, the shape priors module is combined and the module effectively extracts the structural semantic information from the input spine image, thereby enabling more accurate anatomical structure segmentation, and facilitating accurate diagnosis and treatment of spinal disorders.

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.

An implant assembly for stabilizing a joint between a superior vertebra and an inferior vertebra may include a bone plate and an interbody spacer. The bone plate may include an anterior member having at least one superior fastener aperture and at least one inferior fastener aperture formed therethrough. The bone plate may also include a first arm extending from a first end of the anterior member, and a second arm extending from a second end of the anterior member, opposite the first arm, forming a cavity therebetween. The interbody spacer may be configured for placement within the cavity of the bone plate. At least a portion of the bone plate may be formed via at least one subtractive manufacturing process, and at least a portion of the interbody spacer may be formed via at least one additive manufacturing process.

An implant assembly for stabilizing a joint between a superior vertebra and an inferior vertebra may include a bone plate and an interbody spacer. The bone plate may include an anterior member having at least one superior fastener aperture and at least one inferior fastener aperture formed therethrough. The bone plate may also include a first arm extending from a first end of the anterior member, and a second arm extending from a second end of the anterior member, opposite the first arm, forming a cavity therebetween. The interbody spacer may be configured for placement within the cavity of the bone plate. At least a portion of the bone plate may be formed via at least one subtractive manufacturing process, and at least a portion of the interbody spacer may be formed via at least one additive manufacturing process.

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 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.

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.

A continuum manipulator that comprises an assembly of ‘vertebra’-like modules fabricated using two curved links and twelve strings and actuated using Motor-Tendon Actuators. The modules being modeled as tensegrity structures having a polyhedron shape. The vertices and edges of the tensegrity structure polyhedron correspond to the holes and strings or links of the structure. Furthermore, a mobile continuum manipulator that includes a control unit and wheels or mobile legs.

A system for correcting a lateral curvature of a spine that can include a plurality of screws configured to be implanted in a plurality of vertebrae, and a plurality of extensions configured to be removably coupled with the plurality of screws. Some embodiments of the plurality of extensions can be curved, bent, angled, and / or offset along at least a portion thereof and can be removably coupled with a screw head of each of the plurality of screws. The system can include a connecting element or rod that is configured to be coupled with the plurality of screw heads. Some embodiments of the system can be configured such that the rod can be guided along the plurality of extensions from the proximal toward the distal end portions of the extensions and into engagement with the plurality of screws to cause the plurality of vertebrae to move laterally.

Systems and methods for providing an interbody implant are disclosed. According to some implementations, the implant includes an implant body having a cranial face and a caudal face disposed opposite the cranial face. In some implementations, the implant includes one or more primary fixation mechanisms, which in turn can include one or more anchor cavities defined by the implant body. In some cases, one or more anchors are configured to be housed at least partially within the anchor cavities in an undeployed position, and the anchors are configured to be translationally deployed to a deployed position in order to couple the implant to a bony endplate of a spinal vertebra. In some implementations, the implant includes one or more actuators configured to effectuate selective deployment of the anchors.

The invention provides a human body posture abnormity assessment method based on a body measurement all-in-one machine, and the method comprises the steps: obtaining the video data, collected by multiple cameras, of the bending and foot touching actions of a subject, carrying out the preliminary positioning of a spine, a lumbar vertebra and thoracic vertebra transition region, and key points of legs, and extracting the coordinates of the key points; leg joint angle change is calculated according to the leg key point coordinates, if the angle change amplitude is lower than a preset threshold value, it is judged that leg flexibility is insufficient, a key point tracking strategy is adjusted, and the tracking density of a leg area is increased; according to the posture abnormity score, generating a posture abnormity report of the bending and foot touching actions of the subject, and marking specific positions of spine curvature abnormity, stiffness increase of a transition area between the lumbar vertebra and the thoracic vertebra and insufficient leg flexibility; and dynamically updating a key point tracking strategy and an attitude anomaly judgment threshold according to the action normativity score, and optimizing the accuracy and real-time performance of subsequent action evaluation.

The invention relates to a lumbar vertebra protection method and system and a medium, and relates to the technical field of intelligent wearing. According to the scheme, personal basic information and past medical history of a patient are collected, the personal basic information comprises the age, the gender, the height, the weight and the BMI value of the patient, and the past medical history comprises past disease types and current disease courses; on the basis of the personal basic information and the past medical history, a lumbar vertebra supporting strength dynamic adjusting strategy is obtained, and the lumbar vertebra supporting strength dynamic adjusting strategy comprises a control strategy for supporting strength of the patient in all activity states, a control strategy for a supporting mode and recognized bad postures on the basis of the collected electromyographic signals of the patient; and controlling the waist support protection device based on the obtained dynamic adjustment strategy of the lumbar support strength, wherein the control comprises the control of the support strength, the control of the support mode and the early warning control of bad postures. Compared with the prior art, more targeted support strength and support mode control strategies for the patient can be obtained.

The present invention discloses a two-stage AIS spine CT image multi-label segmentation method based on deep learning. The method first obtains an AIS spine image dataset, preprocesses the images in the dataset, and creates new labels for vertebrae positioning. Secondly, the preprocessed images and new labels are processed to train a convolutional neural network for vertebrae positioning. The preprocessed images are then tested using the trained convolutional neural network, and the test results are post-processed to obtain the predicted results of the vertebral center of mass in the spine image. The preprocessed original images and labels are then reprocessed to train the constructed segmentation network. Finally, a region of interest is created based on the vertebral center of mass position predicted during the vertebrae positioning process, and the trained segmentation network is used to segment the target vertebrae in the region of interest, and then the multi-label segmentation results are obtained by integration. The present invention can effectively segment vertebrae.

The invention discloses a pillow regulation and control method self-adaptive to cervical vertebra flexion and shoulder width and application of the pillow regulation and control method to a pillow, and relates to the technical field of sleeping posture regulation. The method comprises the steps of registering a three-dimensional contour point cloud through an ICP algorithm, calculating a neck curvature value, establishing a multiple linear regression model in combination with a pressure gradient change curve and a pressure peak offset, and realizing quantitative correlation between pressure data and a cervical vertebra inclination angle; based on the curvature change amplitude and shoulder breadth classification, a personalized model is constructed; and through attitude monitoring and pressure feedback, a real-time optimization instruction is generated. A target displacement error is set, and correction is stopped after the bending degree reaches the standard continuously for three times; pre-storing a medical-level support parameter library; multi-user switching is achieved through pressure feature and head contour double verification, and physical compression emergency stop is set. According to the method, through multi-source data fusion, scientific model construction and dynamic closed-loop control, the personalization and safety of pillow supporting are improved, and the method is suitable for people with sub-health cervical vertebrae and multi-user scenes.

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.

The invention provides an orthodontic skull lateral film cervical vertebra image segmentation method and system. According to the method, an orthodontic skull side position film image to be processed is obtained, a target image area containing a second cervical vertebra, a third cervical vertebra and a fourth cervical vertebra is determined, then image preprocessing is carried out on the target image area to obtain a standardized input image, then the standardized input image is input into a CNN-Transformer fusion segmentation network for segmentation reasoning, and the image is obtained. According to the method, the centrum segmentation masks of the second cervical vertebra, the third cervical vertebra and the fourth cervical vertebra are output, and finally, the segmentation result is output based on the centrum segmentation masks, so that the segmentation result is output based on the centrum segmentation masks, and a repeatable and traceable objective basis can be provided for subsequent morphological parameter extraction and bone age / maturity quantitative evaluation; the subjective deviation and time cost of manual sketching are practically reduced, and the segmentation consistency and availability under the cross-individual and cross-equipment condition are improved.

In one implementation, we describe the semantics of skeleton joints of the avatar to be animated as a mapping to a highly-detailed skeleton model containing most or all of the joints and bones of human anatomy (the "reference skeleton"). Such a reference skeleton (e.g., the "LOA-4" version of the Web3D humanoid skeleton model) features detailed models of the hand and foot phalanges and joints for every vertebra of the spine. Owing to the level of detail of the reference skeleton, each joint of a user-defined animation skeleton can be mapped to one of the joints of the reference skeleton. The identification and location of each joint in the user-defined skeleton on the human body is thereby accurately and unambiguously described. Such semantics can be used in implementing some features of a virtual world platform, for example, in automated action or gesture recognition.

The invention relates to the technical field of medical equipment, in particular to an angle-adaptive anterior cervical dilator. An auxiliary plier body is connected with a main plier body. The plurality of supporting rods are mounted at respective working ends; the self-adaptive opening assembly is used for automatically adjusting and fixing according to the intervertebral space of a patient, and comprises a sliding adjusting part which is fixed on the main forceps body and is used for opening the main forceps body and the auxiliary forceps body in a semicircular rotating direction; the hydraulic triggering part is installed in the main clamp body and acts on the sliding adjusting part so that the main clamp body and the auxiliary clamp body can be locked after the cervical vertebra of the patient is opened. The clamping blocks are driven through the hydraulic action to lock the piston block located in the inner cavity of the clamp body, and then the main clamp body and the auxiliary clamp body fix the intervertebral space at the current opening distance; the clamping distance adjusting assembly is designed, the auxiliary supporting rod and the ratchet bar are combined with the locking block with the rack structure to fix the auxiliary supporting rod, and the fixing device has the advantages of being good in fixing effect, high in flexibility and convenient to use.

Systems and methods for providing an interbody implant are disclosed. According to some implementations, the implant includes an implant body having a cranial face and a caudal face disposed opposite the cranial face. In some implementations, the implant includes one or more primary fixation mechanisms, which in turn can include one or more anchor cavities defined by the implant body. In some cases, one or more anchors are configured to be housed at least partially within the anchor cavities in an undeployed position, and the anchors are configured to be translationally deployed to a deployed position in order to couple the implant to a bony endplate of a spinal vertebra. In some implementations, the implant includes one or more actuators configured to effectuate selective deployment of the anchors.

A magnetic compression anastomosis device comprises a plurality of interconnected vertebrae including a first vertebra and a second vertebra, wherein each of the first vertebra and the second vertebra is a multipiece vertebra comprising a magnet at least partially encapsulated by a vertebra skin, and wherein the first vertebra and the second vertebra are interconnected by a cylindrical roller and at least one flex element, the roller and the at least one flex element at least partially encapsulated by the first vertebra skin and the second vertebra skin, the roller configured to allow the first and second vertebra to pivot through a predetermined range of rotation in a device plane between at least a delivery configuration and an assembled configuration while constraining movement in other degrees of freedom, the at least one flex element biasing the first and second vertebra toward the assembled configuration.

1. Name of the Design Product: Travel Neck Pillow (Foam Particles). 2. Use of the Design Product: A neck pillow for protecting the cervical vertebra during travel breaks. 3. Design Feature of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Illustrates the Design Feature: Perspective View.

The invention discloses a manufacturing method of a 3D printing guide plate for a cervical vertebra single-door operation, and relates to the technical field of crossing of medical auxiliary instruments and additive manufacturing. Firstly, a cervical vertebra CT data three-dimensional reconstruction skeleton model is obtained, an operation scheme is virtually planned, then a navigation template digital prototype is generated through parameterization, finite element simulation optimization is carried out, and a three-dimensional 3D printing guide plate for the cervical vertebra single-door operation is obtained. Printing with the biocompatible resin by using light curing equipment, and finally treating to obtain a final product. According to the method, a high-precision cervical vertebra skeleton model is generated through CT thin-layer scanning and three-dimensional reconstruction, parameters of a hinge area, a door opening groove line and a nail path are determined through virtual planning, and the problem that damage or positioning deviation is easily caused due to the fact that a traditional operation depends on experience is solved; constructing a navigation template attaching curved surface by a specific algorithm, reserving a soft tissue compensation gap, matching with a hollow window bulge to limit the depth of an abrasion drill, controlling the deformation of a guide plate through finite element simulation and topological optimization, selecting specific resin to ensure the stability, ensuring the suitability by virtue of virtual registration and standardized manufacturing, and improving the accuracy, safety and efficiency of an operation.

Systems and methods for providing an interbody implant are disclosed. According to some implementations, the implant includes an implant body having a cranial face and a caudal face disposed opposite the cranial face. In some implementations, the implant includes one or more primary fixation mechanisms, which in turn can include one or more anchor cavities defined by the implant body. In some cases, one or more anchors are configured to be housed at least partially within the anchor cavities in an undeployed position, and the anchors are configured to be translationally deployed to a deployed position in order to couple the implant to a bony endplate of a spinal vertebra. In some implementations, the implant includes one or more actuators configured to effectuate selective deployment of the anchors.

The invention relates to the technical field of cervical vertebra rehabilitation systems, and discloses an intelligent self-adaptive cervical vertebra rehabilitation system. The system comprises a multi-mode sensing unit which synchronously collects form data and soft tissue data of the cervical vertebra of a user through an optical mark point array and an ultrasonic probe array to generate a multi-source sensing data set; the intelligent analysis unit constructs a cervical vertebra dynamic mechanical model by using a graph convolutional neural network based on the multi-source sensing data set, analyzes a cervical vertebra joint coupling relation and stress distribution, and generates an analysis parameter set; the strategy generation unit generates a personalized rehabilitation strategy according to the analysis parameter set, the personalized rehabilitation strategy comprises an action sequence and an impedance adjustment parameter, and a strategy instruction set is formed; the dynamic control unit responds to the strategy instruction set and combines muscle activity data fed back by the electromyographic signal sensor in real time to adjust an execution strategy and generate a control command set; and the flexible driving unit drives the soft robot outer skeleton to perform multi-axis linkage rehabilitation training based on the control command set.

A neck traction fixing device comprises an elastic supporting part, an adjusting assembly is arranged in the elastic supporting part and comprises an outer shell, an upper supporting frame, a lower supporting frame, a transmission assembly and a rotary adjusting part, the upper supporting frame and the lower supporting frame are arranged in the outer shell in an up-down staggered mode, and the transmission assembly is connected between the upper supporting frame and the lower supporting frame in an engaged mode; the rotary adjusting part comprises an adjusting plate and a rotary cover body, a mounting groove is formed in the front face of the outer shell, a rigid tooth-shaped surface is arranged on the inner edge of the mounting groove, and a concave notch is formed in the outer wall of the adjusting plate. The elastic supporting part is arranged for protecting the cervical vertebra; by arranging the adjusting assemblies capable of moving independently, the elastic supporting part can conduct independent traction and fixation on the left side, the right side and the rear side of the neck, especially for a patient with the torticollis, neck muscle groups at different positions of the neck can be stretched, neck muscle tension can be relieved, and the torticollis orthopedic effect is more remarkable.

The invention discloses a spine structure detection method for vertebrae in an X-ray image, and belongs to the field of computer vision and medical image processing. At present, a spinous structure of a model is generally not designed in a targeted manner, and local fine features of the spinous structure are very easy to ignore. And on the other hand, the target is influenced by surrounding tissues and artifacts, and the model needs to have enough capability to distinguish the target from the background. The invention provides a convolution operator used for capturing thorn-shaped structure features and a more effective channel attention mechanism, the convolution operator and the channel attention mechanism are embedded into a popular target detection framework, and the spine-shaped structure detection method for the vertebrae in the X-ray image is constructed. The method provided by the invention can accurately detect the vertebrae in the X-ray image and the spinous structure generated by the vertebrae, and provides powerful technical support for downstream tasks.

Systems and methods for automatically determining pedicle screw trajectories for surgery may be provided. A scan of a spine may be received, and positions of one or more vertebra and one or more components of the one or more vertebra in the scan may be identified. Next, a screw trajectory planning algorithm may determine an initial screw trajectory plan using the positions of the one or more vertebra and the one or more components. The screw trajectory planning algorithm may then determine a revised screw trajectory plan by revising the initial screw trajectory plan according to weighted factors.