71 results about "Hand bones" patented technology

The invention provides an X-ray film bone age prediction method and system based on deep learning. According to the invention, a bone age prediction result is finally formed through performing preprocessing on an X-ray image of a teenager, automatic segmentation of a hand bone area and bone age prediction. The method comprises a hand bone X-ray film preprocessing and sample data enhancement method, a hand bone X-ray film image block sampling method, a hand bone automatic segmentation algorithm and a transfer learning based hand bone X-ray film bone age assessment algorithm, and finally designsa hand bone X-ray film bone age prediction system taking Dicom data as input. Users only need to select a hand bone X-ray film with the bone age to be predicted, the segmentation and prediction process is completely automatic, and doctors are not required to perform region marking or selecting, and a powerful tool is provided for bone age assessment in scientific research and clinical practice.

The invention discloses a bone age evaluation method based on bone and joint quantized-information integration of a hand bone X-ray film. The method comprises the following steps: step 1, collecting picture samples of hand bone X-ray films, and classifying the samples according to genders and age stages to obtain grouping information; step 2, labeling and dividing bone and joint positions of the samples; step 3, inputting preprocessed sample images and real position information into the convolutional neural network to carry out iteration training to obtain position information and feature mapsof bones and joints; step 4, calculating morphological feature parameters of the bones and the joints in the samples; step 5, fusing the feature maps and morphological features of the bones and the joints into mixed feature information, and inputting the same and the grouping information together into a convolutional neural network model for iteration training; and step 6, completing model training, and carrying out bone age evaluation application. By utilizing the invention, a bone age can be more simply, conveniently and quickly evaluated on the premise of reducing human factor interference.

A pneumatically artificial muscle driven flexible manipulator simulating human hand is composed of the bones of index finger, middle finger, ring finger and little finger and consisting of three units, the thumb bone consisting two units, thumb linking palm, middle palm, little finger linking palm, and artificial tendons. The hand bone system has 21 joints and 17 freedoms.

The invention provides a hand bone X-ray film bone age assessment method and device, computer equipment and a storage medium. The method comprises the steps that a hand bone X-ray film with the bone age to be predicted is processed to be a hand bone photo with the specified pixel requirements; the hand bone photo is input into a preset convolutional-neural-network-based bone age assessment model for conducting calculation; a calculation result output by the bone age assessment model is obtained, wherein the result is the bone age of the hand bone. According to the hand bone X-ray film bone ageassessment method and device, the computer equipment and the storage medium, by means of the convolutional-neural-network-based bone age assessment model, bone age assessment can be conducted automatically, and the assessment accuracy rate is high.

The invention discloses a gesture identification control method used for virtual reality equipment. The virtual reality equipment comprises a plurality of 3D depth cameras and a controller. The method comprises the following steps that: establishing the bone and the three-dimensional model of a hand, tracking the hand through the depth cameras, optimizing a hand bone model so as to control the deformation of the three-dimensional model, quickly detecting an interaction function of the hand and environment in real time further according to the deformation information of the three-dimensional model, and realizing interaction between the user and the virtual environment. By use of the method, a calculated amount in the gesture control process of the virtual reality equipment is lowered, gesture comprehension accuracy is improved, and a quick and vivid interaction function between the user and the virtual environment is realized.

The invention provides a bone age evaluation method based on a two-stage neural network, which comprises the following steps: 1. Adjusting the original input hand bone image size to 512x512, namely scaling according to scale, and adding edge information; 2, extract an image mask; 3, generate a training image; 4, respectively calculating two-dimensional single-scale wavelet transform and Canny operator edge extraction for the image generated in the step 3, and composing three channels of input samples together with the image equalized by the histogram; 5, carrying out data enhancement on the three-channel image generated in the step 4 to expand the data set size; 6. Prediction of bone age; By combining the image segmentation and bone age prediction, the detection method can suppress the noise and segment the hand bone area accurately, so as to evaluate the bone age. For other image processing fields such as target segmentation, target retrieval, target regression prediction and so on, it has practical application value.

The invention discloses a deep neural network-based X-ray film hand bone region of interest automatic extraction method. The method comprises the steps of for an original hand bone X-ray film image, removing text embedded parts of black backgrounds on two sides of the image; performing brightening and denoising operations on the original hand bone X-ray film image in a unified way; sampling and training a model M1 to obtain a text-free hand bone X-ray film image Output2; for the Output2, normalizing the size to obtain Output3; sampling and training a model M2, and judging hand bones, backgrounds and intersection parts of the hand bones and the backgrounds in the Output3; based on the model M2, judging an image sliding window in the Output3, and according to a judgment value, obtaining a hand bone marker mapping graph Output4; based on the Output3 and the Output4, obtaining an image Output5 only with the hand bones; and optimizing the Output5 to obtain a final hand bone region of interest.

The invention provides a pneumatic joint-type rehabilitation manipulator. A pneumatic joint (2) is of a retractable pleated airbag structure; a wrist air inflation and deflation part (11) is communicated with the airbag structure of the pneumatic joint (2); a finger part (13) is matched with a connection structure of the hand bone, and a plurality of knuckle parts (131) on the finger part (13) aresequentially and rotatably connected and rotatably connected to a palm part (12) separately; the knuckle parts (131) are driven to rotate through the extension and retraction of the pneumatic joint (2) and provided with a wearing structure (3) for fixing the human hand. The pneumatic joint-type rehabilitation manipulator is suitable for training of patients with hand diseases in various occasionsespecially at home, helps the patients with the hand diseases to carry out correction rehabilitation training and is suitable for not only rehabilitation persons who cannot conduct active training with the hands and but also users who can carry out active training to a certain degree. The manipulator is simple in structure, convenient to manufacture and carry, easy to operate, economical and practical and has good market prospects.

The invention provides a human skeleton model establishing method and device. The human skeleton model establishing method comprises the steps of obtaining a human body image, recognizing face features in the human body image and determining hand features according to the face features; obtaining a human body depth image; determining trunk features according to a preset-area round region and the human body depth image and determining trunk bone points according to the trunk features; determining hand bone points according to the hand features; establishing a human body bone model according to the trunk bone points and the hand bone points. By means of the human skeleton model establishing method, the hands and the trunk of the human body model can be recognized and distinguished, and the human body bone model can be established.

The embodiment of the invention provides a bone age detection method. The bone age detection method comprises the following steps: acquiring basic information of a target user provided by a client; acquiring hand skeleton image information of a target user; inputting the hand bone image information into a first bone age evaluation model so as to output a first probability corresponding to each first bone age stage through the first bone age evaluation model; determining the first bone age stage with the highest first probability as preliminary bone age information of the target user; inputtingthe basic information of the target user and the preliminary bone age information into a second bone age evaluation model so as to output a second probability corresponding to each second bone age stage through the second bone age evaluation model; and determining the second bone age stage with the highest second probability as the final bone age information of the target user, generating an electronic diagnosis form according to the final bone age information, and sending the electronic diagnosis form to the client. According to the embodiment of the invention, bone age detection efficiencyand detection accuracy are effectively improved.

A method for producing a model of bone geometry of a volumetric region of a body is provided. The method comprises scanning the volumetric region using ultrasound and acquiring geometric data associated with bones; identifying points derived from a surface of the bones; organizing the points into separate bone entities and transforming the points so as to position the bone entities in accordance with a normalized template. The model may be used for identifying or verifying the identity of a person.

The invention provides X-ray imaging equipment. The X-ray imaging equipment comprises an array X-ray source, a collimator and an X-ray flat panel detector, wherein the array X-ray source is used for emitting array X-ray beams; the collimator is used for collimating the emitted array X-ray beams and irradiating the collimated array X-ray beams to a test object; the X-ray flat panel detector is used for receiving the array X-ray beams penetrating through the test object, and an X-ray photography image is formed by utilization of the received array X-ray beams. By the adoption of the combination of the array X-ray source and the collimator, the X-ray beams approximating parallel and an area source is formed, and it is avoided that as hand bone images are easily overlapped, judgment of a doctor on the bone age is affected; compared with an ordinary X-ray DR technology, as the distance between the hand and the X source is not increased, the size of the whole equipment is reduced, and portability is improved; unnecessary radiation is reduced, and therefore injury to human health is reduced.

The invention provides a hand bone fixer which comprises a wrist restraining device, a palm fixer and a bone surface fixing component, wherein the wrist restraining device comprises a wrist fixing ring and an arm wrapping plate; the arm wrapping plate is rotatably connected with the palm fixer by virtue of the wrist fixing ring; the bone surface fixing component is arranged between two supporting components of the palm fixer; the bone surface fixing component comprises fixing blocks arranged on a fixing rod; fixing cables are arranged among the fixing blocks; the bone surface fixing component is capable of realizing skeletal fixation by virtue of a skeletal fixation frame consisting of a plurality of fixing cables contacted with a bone surface.

The invention relates to a bone age assessment method and system. The method is applied to Raspberry Pi and comprises the following steps of: receiving a bone age assessment request; acquiring a hand bone image and a user gender corresponding to the hand bone image according to the bone age assessment request; and performing cutting and histogram matching on the hand bone image, performing numerical conversion on the user gender, transmitting the user gender to a nerve calculation rod, and performing bone age assessment according to the hand bone image and the user gender through a pre-trained bone age assessment model deployed in the nerve calculation rod. By adopting the method, the safety can be improved, and meanwhile, the processing speed is increased to improve the assessment efficiency.

The invention relates to a simulation human body model. The simulation human body model comprises a skeleton, a muscle layer covering the skeleton and a skin layer, wherein the skeleton consists of body bones, hand bones, foot bones, palm bones and sole bones; all the bones are moveably assembled through connecting pieces; the muscle layer is made of an elastic foaming material; the skin layer is attached to the surface of the muscle layer; the skeleton is made of galvanized iron wires; round through holes are formed in the skull, the body bones, the hand bones, the foot bones, the palm bones and the sole bones respectively; the connecting pieces are bolts; nuts are arranged at two ends of each bolt; the outer diameter of each bolt is less than the diameter of each round through hole; the muscle layer is made of a polyurethane foamed plastic; and the skin layer is made of a silicon rubber material. The simulation human body model has the advantage of human body texture such as elasticity, body torsibility, body bendability and the like, is simple in production process and easy to manufacture.

The invention discloses a hand epiphysis development grade determination method and related equipment. The method comprises the steps of obtaining a feature map of a first hand skeleton image; inputting the feature map into a preset hand epiphysis development grade determination model to obtain a position probability map of hand epiphysis points and a development grade probability map of the handepiphysis points output by the hand epiphysis development grade determination model; and determining the development level of the hand epiphysis point according to the position probability graph of the hand epiphysis point and the development level probability graph of the hand epiphysis point. According to the invention, the probability that each position in the hand bone image is an epiphysis point position and the probability that the development level of each position is determined are determined through the hand epiphysis development level determination model, and the development level ofeach hand epiphysis point in the hand skeleton image is determined; according to the technical means, the technical problem that an existing bone age prediction method is low in reliability is solved, and then the technical effect of scientifically determining the bone age is achieved.

The invention discloses a hand bone X-ray image texture feature extraction method for bone age evaluation. The invention can obtain texture features corresponding to the contribution degree of the shape features by processing the bones including the radius, the ulna and the short bones. The invention reasonably samples the image texture, obtains the texture features containing rich growth information, and combines the shape features to remarkably improve the accuracy of bone age evaluation.

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 relates to a key point position determining method and device and electronic equipment. The method comprises the following steps: determining the shape of a human hand and poses of a plurality of skeleton nodes in the human hand based on an image to be analyzed including the image of the human hand; and on the basis of the shape and the pose, determining the positions of the key points of the hand according to a preset geometric constraint condition of the skeleton of the hand. According to the method, the position of the shielded key point can be accurately calculated by utilizing the geometric constraint condition of the hand bone of the hand in combination with the hand parameters extracted from the to-be-analyzed image.

The invention relates to the technical field of capsules and preparation methods thereof, in particular to a Shenqi capsule and a preparation method thereof. The Shenqi capsule is prepared by bulk drug including, by weight, from 3 to 9 parts of ginseng, from 15 to 30 parts of astragalus, from 3 to 9 parts of turmeric, from 3 to 9 parts of safflower carthamus, from 0.5 to 1 part of scorpion powder, from 0.5 to 1 part of centipede powder and from 1 to 3.5 parts of microcrystalline cellulose. The preparation method includes steps of adding water in the ginseng, the astragalus, the turmeric and the safflower carthamus; mixing; decocting twice for 60 minutes every time; combining decoction liquid; filtering; concentrating into clear cream with the relative density ranging from 1.05 to 1.35 (atthe temperature of 50-65 DEG C); treating the clear cream in a vacuum drying manner to obtain clear cream powder; taking scorpion and centipede; respectively grinding the scorpion and the centipede into powder; blending the scorpion powder and the centipede powder with the clear cream powder and pharmaceutic adjuvant; and filling the mixture into capsules. The Shenqi capsule can nourish qi and promote blood circulation to remove meridian obstruction, can be widely used for treating arthralgia of joints such as knee joints, hand bone joints and the like, can obviously remove clinic symptoms ofpatients suffering from osteoarthritis, obviously takes effect, and is fine in treatment effect and free of toxic and side effects.