39 results about "Wrist bone" patented technology

A protective glove is disclosed having a flexible liner conforming to the shape of a hand and wrist and having a plurality of rigid guards secured thereto over the distal, middle, and proximal phalanx bones, the metacarpals, and wrist bones of the wearer. A distal guard is shaped as a cup placed over the posterior side of the distal phalanx bone. Middle and proximal guards protect the middle and proximal phalanx bones of the hand and may be embodied as rings positioned slightly distal of the finger joints and having extensions extending distally therefrom. A metacarpal guard secures to the posterior of the glove over the metacarpals and extends toward the anterior of the hand, providing a cutout to receive the thumb. A wrist guard encircles the liner over the wrist bones and is spaced apart from the metacarpal guard to permit wrist articulation.

Embodiments of the present application provides a method and apparatus for detecting bone age, and relates to the technical field of machine learning. The method comprises the following steps: acquiring a bone age slice of a user to be detected, adjusting each bone in the bone age slice to a reference position, determining a wrist bone region from the bone age slice, then determining the number ofossification centers in the wrist bone region by using a classification model, and finally determining the bone age of the user to be detected according to the number of ossification centers in the wrist bone region. Because the number of ossification centers in the carpal region represents different bone age stages, as such, embodiments of the present application employ classification models toautomatically determine the numb of ossification centers in the carpal region, then, the bone age of the user to be detected is determined according to the number of ossification centers in the wristbone region, without artificial subjective judgment of bone age according to bone age slices, so that on the one hand, the precision of detecting bone age is improved, and on the other hand, the efficiency of detecting bone age is improved.

The invention provides a wrist joint prosthesis. The wrist joint prosthesis comprises a carpal prosthesis and a radius prosthesis, wherein the carpal prosthesis is provided with a first curved surface, the radius prosthesis is provided with a second curved surface matched with the first curved surface in shape, and the carpal prosthesis and the radius prosthesis are connected in an abutting mode in the first direction through the first curved surface and the second curved surface. The carpal prosthesis is configured to be rotatable relative to the radius prosthesis around a second direction and a third direction which are perpendicular to the first direction, and one end used for being connected with carpal, of the carpal prosthesis is rotatable relative to one end used for being connectedwith the radius, of the radius prosthesis around the first direction. According to the configuration, one end used for being connected with carpal, of the wrist joint prosthesis is configured to rotate around the first direction relative to one end used for being connected with the carpal, of the radius prosthesis, so that the wrist joint prosthesis can achieve the circling motion function of a radial wrist joint, the wrist joint mobility of a patient is improved, and the satisfaction degree of the patient is increased.

The invention provides a bone age evaluation method and system based on a graph convolutional neural network, a terminal and a storage medium. The method comprises the steps: obtaining N target epiphysis of a wrist bone image; adopting a feature extraction network model to extract initial features X of N target epiphysis and nearby areas of the wrist bone image; adopting a context feature fusion network model based on a graph convolution network, adding the initial feature X and the context feature subjected to multilayer graph convolution to obtain a final fusion feature, inputting the fusionfeature into a prediction distribution network model, and predicting to obtain development level distribution of N target epiphysis, correspondingly calculating development grade expectation and variance, development score expectation and bone maturity total score; and performing calculating to obtain a final bone age prediction value according to a bone age standard by utilizing the predicted development grade and the calculated bone maturity total score. Context feature fusion is realized through the graph convolution network to promote information communication among different local bone regions, accumulated bone age errors are avoided through a bone maturity total score loss function, and bone age evaluation accuracy and robustness are realized.

The invention discloses a wrist bone interest region cutting method based on machine learning, which utilizes a machine learning method to segment a medical image, and achieves a better effect throughthe combination of central point cutting and cutting frame size self-adaption. According to the method, on the premise that it is guaranteed that the size of each individual is independent, more accurate cutting and feature extraction are conducted on each wrist bone picture. According to the method, the self-adaptive cutting frame can be generated for any height and age, and data support is provided for more accurate judgment of the wrist bone grade. The method can be applied to feature region cutting in the field of image recognition, and the recognition rate of the deep learning network isgreatly increased.

A hand bone X-ray film bone age evaluation method based on a heterogeneous data fusion network comprises: 1, preprocessing an X-ray film image, and extracting a wrist bone part in the image; step 2, constructing a convolutional neural network to extract image features; 3, constructing a text feature extraction model; 4, constructing a fusion layer, and combining the image features and the text features; step 5, model training: after sufficient convergence, storing and exporting a model structure and weight parameters; and performing bone age evaluation on the hand bone X-ray film by using thefusion network obtained by training. According to the invention, the accurate bone age can be obtained by analyzing the hand bone X-ray film by using the text information and the X-ray film image information.

The invention discloses a wrist part scaphoid bone replacement prosthesis, which is characterized by comprising a replacement part scaphoid bone, a residual healthy scaphoid bone, an anti-rotation forcing screw and a transplantation prosthesis, the replacement part navicular bone is a part of the carpal navicular bone, the transplantation prosthesis is fixedly connected with the residual healthy navicular bone, one end of the anti-rotation forcing screw is fixedly connected to the transplantation prosthesis, and the other end of the anti-rotation forcing screw is fixedly connected to the residual healthy navicular bone; according to the prosthesis, a three-dimensional scaphoid model of a patient is constructed through three-dimensional CT scanning of the scaphoid of the carpal bone at the intact position of the patient, and a three-dimensional model of a scaphoid replacement part is obtained by mirroring the three-dimensional model. Therefore, the scaphoid fracture healing process is directly simplified, the conditions of slow healing, non-healing and ischemic death of the two scaphoids after scaphoid fracture are avoided, the scaphoid fracture rehabilitation speed of the carpal bone is increased, the inconvenience of wrist movement caused by scaphoid fracture healing disorder in the later period is avoided, the later-period hidden danger is eliminated, and the postoperative rehabilitation quality of a patient is guaranteed.

The invention discloses a wrist bone mineral density detection instrument which comprises a hollow square frame body, wherein a first bone mineral density detection probe is arranged on the inner topwall of the hollow square frame body; a second bone mineral density detection probe is arranged on the inner left side wall of the hollow square frame body; a control display screen and a battery connected with the control display screen are arranged at the upper part of the hollow square frame body; and a camera is arranged at the upper part of the control display screen. The wrist bone mineral density detection instrument has the advantages that the structure is simple; the wrist can be well put; the bone mineral density of the wrist in two directions can be detected at the same time; the detection can be shot through the camera; the detection results of the detection probes are automatically stored into a storage module corresponding to a detected person all together; and the detectionresults can be acquired and checked at any time.

The invention provides a bone age evaluation method and device based on a deep convolutional neural network and feature fusion and a computer readable storage medium, and the method comprises the following steps: collecting wrist bone X-ray films, and classifying the wrist bone X-ray films to form a wrist bone X-ray image set; randomly selecting a training image and a test image, marking an ROI region based on a TW scoring method, constructing a target detection neural network applying a YOLO model, and inputting the training image and the test image into the target detection neural network to form a deep convolutional neural network; training images are randomly selected and input to the deep convolutional neural network, global feature information of the training images is extracted by the deep convolutional neural network, local feature information of the training images is extracted based on the target detection neural network, and the global feature information and the local feature information are fused to obtain a bone age evaluation result. After the technical scheme is adopted, full automation of bone age evaluation can be realized, the network performance is improved, and the accuracy of bone age evaluation is further improved.

The present invention discloses a combined semi-limiting multipolar artificial wrist joint, or “semi-limiting bipolar artificial wrist joint”, and be selected and assembled based on the specific pathological conditions of wrist bone destruction. For instance, the metacarpal bone articular surface is shown to be complete and the bone quality is good, and most of the far carpal bones (including small polyangular bones and head bones) can be preserved, while the proximal carpal bones (scaphoid and lunate) and the articular surface of the carpal radius are broken, and the proximal carpal bones are to be excised. The artificial wrist joint can also be assembled in another way, which is called “semi-limiting multipolar artificial wrist joint”, wherein the pathologically damaged double carpal bones are excised to form an inter-matching assembly of palm, wrist and radius joints.

The invention provides a bone age evaluation method and device based on a deep convolutional neural network and a computer readable storage medium, and the method comprises the steps: collecting a wrist bone X-ray film calibrated with bone age information, constructing a first deep convolutional neural network based on a UNet algorithm to carry out the image segmentation of the wrist bone X-ray film, so as to obtain a preprocessed image set, partial images are selected as training set images, and the rest images are selected as test set images; constructing a second deep convolutional neural network based on a DenseNet algorithm, and inputting the training set image to train parameters of the second deep convolutional neural network so as to obtain a trained second deep convolutional neural network, the trained second deep convolutional neural network having learned network weight parameters; and inputting the test set image into a trained second deep convolutional neural network, and outputting a bone age evaluation result after iteration of the trained second deep convolutional neural network. After the technical scheme is adopted, the bone age evaluation result can meet the requirements of clinical application.

The invention discloses a multi-classifier wrist bone grade recognition method based on height and age. According to the method, on the basis of a deep learning network regression model based on height and age information and a plurality of three-classification deep learning network classification models, an approximate range of grades is obtained through the regression model, and then corresponding classifiers are selected to accurately classify the grades of bones. According to the method, the bone age grade judgment accuracy can be effectively improved, and the final bone age judgment erroris reduced.

The invention relates to a fixing device for wrist bone fracture. The fixing device is used for fixing an arm, a wrist and finger bone fracture in the auxiliary rehabilitation process, , and is characterized in that three arc-shaped supporting plates are connected with one another in sequence on the side surfaces of the supporting plates through flexible connecting bands; an elbow is arranged at the same end part of each supporting plate; an arc-shaped groove is formed in the length direction of the plate surfaces in the plate surfaces of three supporting plates; the opening direction of the arc-shaped groove is reversed to the bending direction of the elbows; cracks are uniformly formed in the side surfaces of the supporting plates positioned on the outer side; a thumb plate can be selectively inserted in each crack; a transversal fixing band and a longitudinal fixing band are fixed on the supporting plate positioned at the middle part through rivets; one end part of a thumb plate connecting band and a thumb fixing band are both fixed on the thumb plate through rivets; the other end of the thumb plate connecting band is connected onto the longitudinal fixing band through rivets. The fixing device is free of limitation of a left hand and a right hand, that is the left hand and right hands can use the fixing device; meanwhile, the fixing device is suitable for patients in different physiques.

The invention discloses a wrist bone grade recognition method based on secondary classification. According to the invention, a deep learning method is used for judging the medical image, and the support vector machine and the deep learning network are combined for use to achieve a better effect. On the premise that judgment of other types of pictures is not affected, the more accurate judgment canbe made on a small number of types of pictures.

The invention provides a wrist joint prosthesis, which comprises a wrist bone component and a radius bone component, wherein the wrist bone component comprises a wrist bone body and locking screws, mounting holes are formed in the wrist bone body, the locking screws are arranged in the mounting holes in a penetrating manner, and a porous structure is arranged at one end of the wrist bone body close to the locking screws; and one end of the wrist bone body far away from the locking screws is abutted against the end part of the radius bone component, and a porous structure is arranged on the radius bone component. Through the technical scheme, the problem of easy loosening of the wrist joint prosthesis in the prior art can be solved.