5614 results about "Spinal column" patented technology

The invention relates to the technical field of image processing, and discloses a scoliosis angle intelligent measurement method and system based on spine CT three-dimensional reconstruction. The method comprises the following steps: carrying out adaptive threshold segmentation and gray optimization processing on a spine CT sequence image to obtain a standardized preprocessed image, and carrying out adaptive bone tissue region identification and boundary enhancement processing to obtain spine skeleton segmentation data; performing three-dimensional grid construction and curved surface smoothing processing on the spine skeleton segmentation data to obtain spine three-dimensional model data; carrying out centrum gap identification and key point positioning processing on the spine three-dimensional model data to obtain a centrum feature data set, and carrying out spine midline curve construction and end centrum marking processing to obtain Cobb angle data; and performing three-dimensional space reconstruction and multi-plane projection processing on the Cobb angle data to obtain a measurement result report. According to the method and the device, full-automatic processing from acquisition of the CT image to generation of the final measurement result report is realized on the premise of ensuring the measurement accuracy.

A catheter adapted or high density mapping and / or ablation of tissue surface has a distal electrode array with offset spine loops, each spine loop having at least a pair of linear portions and a distal portion connecting the pair of linear portions, and one or more electrodes on each linear portion. The linear portions of the plurality of offset spine loops are arranged in-plane a single common plane, and the distal portions of the plurality of offset spine loops are arranged off-plane from the single common plane.

A catheter comprising an elongated catheter body, an electrode array distal of the catheter body, the array having a mounting member and at least first and second spine supports. Each spine support includes a base having a planar configuration, and a plurality of spines extending from the base, wherein the first base extends in a first plane and the second base extends in a second plane different from the first plane in the mounting member.

A catheter comprising an elongated catheter body, and an electrode assembly distal of the catheter body, the assembly comprising a plurality of spines, wherein each spine has a distal end that is connected to the distal end of at least one other spine, wherein each spine has an electrode-carrying portion, the electrode-carrying portions of all spines of the assembly being in a single common plane, and wherein all spines of the assembly have a uniform exposed total length.

The invention discloses a covariance self-adaptive control method for a quadruped robot for spine joint adjustment. The method comprises the following steps that 1, a spine quadruped robot kinematics model with spine joints, a robot trunk dynamics model with the spine joints and a robot leg multi-rigid-body dynamics model are established; 2, based on the energy stability margin theorem and the spine joint coupling effect, a posture control method of the spine joint quadruped robot is provided by combining a covariance self-adaptive evolutionary strategy, and the angle, rigidity and damping coefficient of spine joints are estimated and adjusted according to the terrain gradient; 3, extracting the spatial relationship between the trunk mass center and the foot ends of the robot as an expected reference, updating the expected mass center position in real time, and constructing a model prediction control method to control the posture of the spinal joint quadruped robot; 4, the position of the foot falling point of the swing leg is designed in advance in combination with the additional freedom degree provided by the spine joint and MPC prediction state information. The motion stability of the robot in the complex terrain is improved.

The invention provides a seat comfort optimization calculation method based on a sensor and AI modeling, and the method comprises the steps: collecting the pressure distribution data of the sitting posture of a passenger and a spine contact area in real time through an attitude sensor and a pressure sensor which are disposed on a seat; a seat supporting area is divided into a cervical vertebra area, a thoracic vertebra area, a lumbar vertebra area and a sacrococcygeal area, and a pressure distribution prediction model of each area is established; constructing an input vector based on the average pressure, the maximum pressure, the pressure gravity center, the body type parameter and the pathological weight factor, and outputting a target support pressure value, a pressure avoiding curve and a neighbor cell migration proportion of each partition by using an artificial intelligence model; dynamic adjustment is achieved through the partitioned air bag and the driving unit, and secondary fine adjustment and protection are achieved in combination with feedback monitoring. The system comprises a posture sensing module, a pressure sensing module, a data processing module, a model building module, a regulation and control execution module and a feedback monitoring module, and self-adaptive regulation and control of different areas of the spine of a passenger can be achieved.

A system for non-invasively adjusting the curvature of a spine includes a housing having a first end and a second end, a first rod having a first end telescopically disposed within a cavity of the housing along a first longitudinal axis at the first end of the housing and having a first threaded portion extending thereon, and a second end configured to be coupled to a first portion of a spinal system of a subject, a second rod having a first end telescopically disposed within the cavity along a second longitudinal axis at the second end of the housing and having a second threaded portion extending thereon, and a second end configured to be coupled to a second portion of the spinal system of the subject, a driving member rotatably disposed within the cavity and configured to be activated from a location external to the body of the subject.

The invention discloses a scoliosis evaluation system and device based on multi-modal information fusion, and belongs to the field of spine health. A back pressure electromyographic signal acquisition module acquires stress electromyographic information of a back muscle group; the thermal imaging module obtains a thermal imaging information graph of a human body; the plantar pressure acquisition module acquires plantar pressure information; the multi-mode data fusion module inputs the stress myoelectricity information, the thermal imaging information graph and the plantar pressure information into the encoder layer, a cross attention mechanism is adopted in the feature matching layer to fuse features from different modules, a classifier model is used for scoliosis evaluation, and classification is conducted according to the scoliosis degree. According to the application, the collaborative mechanism of the stress myoelectricity information, the thermal imaging information graph and the plantar pressure information of the back during scoliosis is utilized, multi-modal data fusion is performed on the stress myoelectricity information, the thermal imaging information graph and the plantar pressure information of the back, full-automatic evaluation is realized through a multi-modal data fusion model, the evaluation accuracy is high, and no radiation is generated.

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.

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 invention discloses a spine three-dimensional evaluation method and system based on RGB images and anatomical constraints, and belongs to the field of medical image analysis. The method comprises the following steps: carrying out preprocessing and anatomical symmetry correction on an upright position back RGB image shot by the intelligent mobile equipment for a single time; extracting regions of interest of shoulder blade and iliac crest mark points by using a lightweight segmentation network; generating an initial depth map through a depth estimation model fusing a vertebra attention mechanism and a multi-constraint loss function; carrying out physiological scale calibration on the initial depth map based on height and weight parameters; a cascade GAN is adopted to eliminate clothes interference and reconstruct a back three-dimensional surface; based on biomechanical characteristics, NURBS parameters are adjusted in a self-adaptive mode to fit a spine three-dimensional curve; and outputting a coronal plane Cobb angle, a trunk rotation angle and a sagittal plane curvature parameter. Through monocular depth estimation and dynamic evaluation of anatomical constraint, the problems of radiation risk, subjective error and clothes interference of a traditional method are solved.

The invention discloses a scoliosis orthosis registration method based on deep learning and biomechanical constraint, and relates to the technical field of scoliosis orthosis design, and the method comprises the steps: respectively obtaining first feature information of a three-dimensional spine model and second feature information of a three-dimensional body surface model, the second feature information comprises a geometric feature, a pressure feature and a motion feature; the first feature information and the second feature information are simultaneously input to a pre-constructed hybrid configuration network for rigid registration and non-rigid registration, the rigid registration outputs an initial alignment model, and the non-rigid registration outputs high-precision local adaptation data with reasonable dissection; and performing joint optimization on the initial alignment model and the high-precision local adaptation data with reasonable dissection to obtain a final registration result. Geometric and motion features of a spine and a body surface are extracted through double-flow features, so that a registration network of coarse rigidity and then fine non-rigidity is carried out, and transition from geometric registration to function optimization is realized.

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 present disclosure provides for spinal implants configured for lateral insertion techniques deployable between a contracted position and an expanded position. The spinal implant may include a first endplate and a second endplate, each having a plurality of guide walls and inclined ramps. The spinal implant may further include a moving mechanism having first and second trolleys configured to act against the first and second plurality of ramps. The moving mechanism may further include a first set screw and a second set screw opposite the first set screw. The moving mechanism may be configured to operably adjust a spacing between the first and second endplates upon simultaneous rotation of the first and second set screws along a rotation axis, and may also operably adjust an angle of inclination between the first and second endplates upon rotating the first set screw or second set screw along the rotation axis.

The method of making a spinal implant fusion device has the steps of: fabricating an implant body structure using 3D printing to create the implant body structure; additively building the body structure having a superior load bearing surface and an inferior load bearing surface and a wall structure; and wherein the body structure has at least a portion of the body structure having a lattice of interconnected struts forming porous walls with openings or passages extending inwardly from an exterior surface forming a porous or open portion with a void volume to solid mass volume greater than 10 percent, preferably greater than 25 percent. Alternatively, the 3D printed structure may be completely or substantially solid with a surface structure comprised of the interconnected arcs that are raised, or created like troughs that appear to be cut into the surface but were created through 3D printing.

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.

An apparatus can include a wheel chock. The wheel chock can include a body portion. The body portion can include: a bottom face; a first side face and a second side face extending upward relative to the bottom face; at least one chocking face positioned above at least one of the first side face or the second side face, wherein the at least one chocking face includes an angled surface; and a spine forming a top surface parallel to the bottom face, the spine adjoined to the at least one chocking face, and the spine defining apertures. The wheel chock can also include an elongated handle attachable to the body portion via the apertures, the elongated handle configured to maintain an upright, self-standing position.

The invention relates to the technical field of spine deformation recognition, in particular to a spine deformation recognition method and system based on image recognition, and the method comprises the following steps: S1, data collection and preprocessing: obtaining multi-view and multi-time-point spine image data of the spine of a patient; s2, soft tissue shielding correction: automatically identifying and correcting interference of the soft tissue on the spine image data; s3, dynamic change prediction of the spine: performing dynamic change prediction on the spine image data subjected to soft tissue shielding correction; and S4, deformation judgment and result output: judging the deformation condition, the deformation type and the severity of the spine, and generating a visual report containing the spine deformation condition and future change prediction. According to the method, the noise in the image is effectively removed, the definition of the spine structure is enhanced, and meanwhile, the interference problem of soft tissue on the spine image is solved.

A spinal implant assembly, a kit for forming same and a method for forming same. The spinal implant assembly comprises: a first endplate having a first non-planar inner surface; a second endplate having a second non-planar inner surface facing toward the first non-planar inner surface; at least one fastener attaching the first endplate and the second endplate to one another; and a layer including a piezoelectric material (piezoelectric layer), the piezoelectric layer between the first non-planar inner surface and the second non-planar inner surface and having a non-planar upper surface facing toward the first non-planar inner surface and a non-planar lower surface facing toward the second non-planar inner surface, wherein, at a front region of the spinal implant assembly, the first non-planar inner surface and the second non-planar inner surface define a vertically biased interface.

The invention discloses a dynamic three-dimensional ultrasonic spine detection method and imaging system, and belongs to the field of medicine.The method adopts a mature three-dimensional spine ultrasonic imaging system to be matched with a wearable wireless ultrasonic probe to collect real-time ultrasonic images, a depth camera records space coordinate changes of spine feature points in real time when the spine of a patient is bent, and the dynamic three-dimensional spine ultrasonic imaging system is obtained. A three-dimensional ultrasonic image, a real-time ultrasonic image and a dynamic three-dimensional image of a back form are fused to obtain a dynamic three-dimensional ultrasonic spine image, and a deep learning algorithm is combined according to the dynamic three-dimensional ultrasonic spine image to carry out Lenke typing parameter measurement and calculation and carry out dynamic comprehensive evaluation on the spine. Scoliosis typing is improved from a traditional X-ray plane evaluation mode based on radiation hazards to non-radiation dynamic three-dimensional ultrasonic analysis, and the problems that in the prior art, the error rate of data collected under the static condition is high, and collection parameters are insufficient are solved.

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.

An apparatus can include a wheel chock. The wheel chock can include a body portion. The body portion can include: a bottom face; a first side face and a second side face extending upward relative to the bottom face; at least one chocking face positioned above at least one of the first side face or the second side face, wherein the at least one chocking face includes an angled surface; and a spine forming a top surface parallel to the bottom face, the spine adjoined to the at least one chocking face, and the spine defining apertures. The wheel chock can also include a handle having a rigid portion, the handle being attachable to the body portion via the apertures. In some examples, the wheel chock further includes a high visibility material integrally formed with at least one of the body portion or the handle.

The present invention relates to the fields of child health monitoring and artificial intelligence technology, and provides a child scoliosis monitoring and early warning system. Existing methods rely on static inspections, and it is difficult to capture abnormal dynamic changes of the spine in real time. The present invention acquires multimodal data through posture sensors, acceleration sensors, and image acquisition devices, combines convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) to perform deep feature extraction, and uses hidden Markov models (HMMs) to identify children's behavioral contexts and dynamically adjust the early warning threshold. The system uses a Q-learning algorithm to generate personalized health intervention strategies, and uses differential privacy and homomorphic encryption technologies to ensure data security. Finally, the system generates a three-level health warning signal to immediately remind children to adjust their postures and notify guardians. The present invention realizes real-time monitoring and personalized intervention of spinal health, provides an efficient and safe health management solution, and promotes the early detection and correction of scoliosis.

An intervertebral implant for implantation in an intervertebral space between vertebrae. The implant includes a body having a front end, a rear end and a pair of spaced apart first and second side walls extending between the front and rear ends. The front and rear ends extend in a transverse direction and a central axis of the body extends from the rear end to the front end. The rear end defines a first fastener hole having a first central axis and a second fastener hole having a second central axis. The first and second central axes extend parallel to one another at an acute angle relative to the body central axis in the transverse direction.

The invention relates to the technical field of spine rehabilitation training, and discloses a computer vision recognition and guidance system for spine rehabilitation training actions. The system comprises a data acquisition module for acquiring user spine motion three-dimensional dynamic image data by using a multi-camera array; the action recognition module tracks bone joint points based on an improved algorithm to generate a real-time action sequence; the posture evaluation module is used for extracting spine curvature and joint angle features through a multi-scale convolutional neural network; the guidance instruction generation module inputs the features into a reinforcement learning model to generate a personalized instruction; and the feedback execution module constructs a fuzzy self-adaptive control model to correct the motion trail of the spine. According to the system, training actions can be accurately recognized, personalized guidance is provided, real-time correction is achieved, the spine rehabilitation training effect is effectively improved, subjectivity and errors of manual evaluation are reduced, and rehabilitation requirements of different patients are met.

The embodiment of the invention discloses a spinal metastatic tumor treatment scheme generation system. According to one specific embodiment, the system comprises a data processing server, an information fusion server and a scheme generation server which are in communication connection with one another, and the data processing server is used for preprocessing multi-source patient data to obtain standard multi-source patient data; the information fusion server is used for executing the following steps: performing feature code fusion on standard multi-source patient data to obtain a multi-source patient feature vector; performing feature enhancement on the multi-source patient feature vector to obtain a joint patient characterization vector; generating an initial therapeutic schedule result based on the joint patient characterization vector; and the scheme generation server is used for performing feature decision processing on the initial treatment scheme result to obtain a final treatment report. According to the embodiment, waste of computing resources can be reduced, and system response time can be shortened.

Described herein are wearable sensory stimulation and monitoring devices that can be worn around the back of the neck along and in contact with the spine. Apparatuses described herein stimulate one or more senses including auditory, tactile or olfactory. Apparatuses are also described that allow for sensing and monitoring of physiologic parameters such as heart rate, blood pressure and movement. The device also has features that allow for easy attachment or integration to articles worn on the head such as augmented reality and virtual reality accessories to provide visual stimulation and entertainment.

An access device for accessing an intervertebral disc having an outer shield comprising an access shield with a larger diameter (˜16-30 mm) that reaches from the skin down to the facet line, with an inner shield having a second smaller diameter (˜5-12 mm) extending past the access shield and reaches down to the disc level. This combines the benefits of the direct visual microsurgical / mini open approaches and the percutaneous, “ultra-MIS” techniques.

Embodiments include example systems, methods, and computer-accessible mediums for analysis of anatomical images for assessment of stenosis and disc degeneration. In some embodiments, systems, devices, and methods described herein include selecting a region of interest (ROI) in a three-dimensional (3D) volume of image data of a plurality of vertebra of a spine, identifying one or more anatomical parts in the ROI, determining one or more parameters of the one or more anatomical parts, and assessing a severity of a spinal deformity based on the one or more parameters.

The invention discloses a spine rehabilitation training device, comprising: a rehabilitation training assembly comprising a head and neck supporting mechanism, a thoracolumbar supporting mechanism and a caudal vertebra supporting mechanism which are arranged at intervals from top to bottom and are connected with each other through a flexible connecting piece I, the head and neck supporting mechanism, the thoracolumbar supporting mechanism and the caudal vertebra supporting mechanism each comprise a plurality of air bag supporting pieces arranged at intervals. The plurality of air pumps are respectively used for supplying air to the plurality of air bag supporting pieces so as to adjust the pressure on each part of the body; and the control unit is connected with the plurality of air pumps and can independently control the start and stop of each air pump so as to control the pressure of each air bag supporting piece. Bed-in-bed, physical or exercise rehabilitation treatment methods can be selected according to different periods, and the application range is wide.