64 results about "Bone age" patented technology

The invention discloses a teenager physical exercise real-time monitoring system, and relates to the technical field of intelligent monitoring. An individualized health assessment model is constructed through space-time alignment processing of joint three-dimensional movement, electromyographic signals and plantar pressure and a bone age dynamic matching technology. Time sequence deviation is eliminated through unified clock marking and interpolation compensation, parameters such as bone stress deviation degree, muscle synergy asymmetry degree and plantar pressure unbalance degree are extracted, and comprehensive health indexes are generated through weighting. And in combination with a preset training path model, analyzing a health index trend in real time and triggering a grading adjustment instruction, dynamically optimizing training intensity, interval and action schemes, and correcting path model parameters through a closed-loop feedback mechanism to realize adaptive updating. The defects that traditional teenager physique monitoring data fusion is large in deviation and static evaluation hysteresis is high are overcome, real-time accurate monitoring and personalized training optimization of teenager physique exercise are achieved, and the sport injury risk is effectively reduced.

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.

The invention relates to a cervical vertebra bone age staging identification method. The method comprises the following steps: S1, acquiring a skull side film of a cervical vertebra bone age staging object; s2, inputting the skull side position film into a cervical vertebra region target detection model to remove irrelevant backgrounds, and only retaining target regions containing C2, C3 and C4 joints; s3, inputting the area detected in the S2 into an instance segmentation model to segment C2, C3 and C4 joints, and labeling category labels; s4, inputting the area detected in the S2 into a mark point detection model to extract mark points with detail information at the edges of the bone joints C2, C3 and C4; and S5, inputting the features extracted in S3 and S4 into a cervical vertebra staging estimation module to obtain a final staging result. Compared with the prior art, the method has the advantages that the traditional manual skull side position film evaluation is converted into automatic detection, segmentation and staging tasks by using deep learning, so that the diagnosis efficiency is greatly improved, the staging accuracy is improved, and a doctor is effectively assisted in making an orthodontic plan.

The invention relates to the field of food materials, and particularly discloses a gamma-aminobutyric acid and hydrolyzed egg yolk powder composite beverage capable of promoting sleep and inhibiting bone age and a preparation method of the gamma-aminobutyric acid and hydrolyzed egg yolk powder composite beverage. A gamma-aminobutyric acid and hydrolyzed egg yolk powder composite beverage capable of promoting sleep and inhibiting bone age comprises the following raw materials in percentage: 3-5% of xylitol, 3-5% of fructo-oligosaccharide, 2-4% of gamma-aminobutyric acid, 3-9% of antioxidant composite concentrated juice, 0.16-1% of purple carrot juice beverage thick slurry, 0.1-0.19% of calcium aspartate, 0.02-0.05% of casein hydrolyzed peptide, 0.02-0.05% of hydrolyzed egg yolk powder, 0.02-0.05% of casein phosphopeptide and the balance of water. The formula comprises the following components in percentage by weight: 0.006 to 0.01 percent of zinc gluconate, 0.0005 to 0.00085 percent of zinc-rich edible yeast powder, 0.0005 to 0.00085 percent of tea theanine, 0.0005 to 0.00085 percent of N-acetylneuraminic acid, 0.0018 to 0.09 percent of a traditional Chinese medicine composition, 0.005 to 0.01 percent of L-calcium lactate, 0.0005 to 0.01 percent of collagen peptide, 0.1 to 0.3 percent of xanthan gum, 0.0005 to 0.00085 percent of melissa officinalis, 0.2 to 0.98 percent of a compound flavoring agent and the balance of purified water. Through the synergistic effect of all the components, the sleep quality is effectively improved, overactivity of bone cells is inhibited, and the bone age development is delayed.

The present application provides a bone age prediction method, device, electronic device and storage medium, which belongs to the field of artificial intelligence technology. The method includes: obtaining a target bone image; performing key point detection on the target bone image through a first key point detection model to obtain a first target bone key point; performing a first posture correction process on the target bone image according to the first target bone key point to obtain a standard bone image; performing a segmentation process on the standard bone image through an image segmentation model to obtain a preliminary bone foreground map; performing key point detection on the standard bone image through a second key point detection model to obtain a second target bone key point; performing a second posture correction process on the preliminary bone foreground map according to the second target bone key point to obtain a standard bone foreground map; inputting the standard bone foreground map into the bone age prediction model to perform bone age prediction, and obtaining bone age prediction data. The present application can improve the accuracy of bone age prediction.

The utility model discloses an accurate bone age ruler, which comprises a film viewer panel, the outer wall of the film viewer panel is slidably sleeved with a U-shaped slide fastener, the outer wall of the U-shaped slide fastener is provided with a circular groove, the inner wall of the circular groove is fixedly connected with a threaded column, and the outer wall of the threaded column is rotatably connected with a circular block. According to the utility model, the U-shaped slide fastener, the threaded column, the round block, the rubber pad, the rectangular block, the first ruler, the T-shaped long groove, the first scale line, the T-shaped column, the second ruler, the second scale line, the locking cap, the fastening cap and the limiting block are arranged, so that the first ruler and the second ruler are placed on the film viewer panel, and the first ruler and the second ruler cannot rotate when not subjected to external force through friction force; the first ruler is used for measuring the lengths of the phalanx, the radialis and the ulna, the second ruler is used for measuring the widths of the phalanx, the radialis and the ulna, multiple times of taking and calibration are not needed under the condition that the measuring precision is not affected, and standard reference and recording are facilitated.

The invention relates to the technical field of image processing, in particular to a metacarpal and phalanx image processing method and device. The method comprises the following steps: acquiring an initial metacarpal and phalanx image, and performing brightness processing on the initial metacarpal and phalanx image to obtain a first metacarpal and phalanx image; performing contrast processing on the first metacarpal and phalanx image to obtain a second metacarpal and phalanx image; constructing a preset convolution kernel, and performing definition processing on the second metacarpal and phalanx image based on the preset convolution kernel to obtain a metacarpal and phalanx target image; and inputting the metacarpal and phalanx target image into the bone age recognition model, and outputting a bone age recognition result. According to the method, dynamic image enhancement optimization can be carried out on metacarpal and phalanx X-ray images of different devices and different qualities through brightness, contrast and definition processing, so that the processed metacarpal and phalanx target images can highlight morphological characteristics of epiphysis, the bone age recognition accuracy is improved, and the bone age recognition efficiency is improved. The problem of low bone age recognition accuracy caused by different image qualities in the prior art is solved.

The invention discloses a method for constructing a bone age detection model, which comprises the following steps of: inputting an X-ray film image in a training set into a bone age detection model to obtain a corresponding predicted bone age, and training the bone age detection model by minimizing the difference loss between the predicted bone age and a corresponding bone age label, wherein the bone age detection model comprises a global model, local models in one-to-one correspondence with k bone age segments and a fusion module, and when an X-ray film image is input into the bone age detection model, an X-ray film obtains first probability distribution and second probability distribution of the bone age through the global model and the corresponding local models, the first probability distribution and the second probability distribution are input into a fusion module, third probability distribution is obtained, the corresponding predicted bone age is obtained according to the third probability distribution, the X-ray image in the training set is an image containing bone age information, and the corresponding label is the bone age. According to the method, the bone age prediction precision is improved by considering the global features of the bone age and the specific features of the bone age.

The utility model relates to the technical field of medical instruments and the like, and provides a portable bone age instrument which is provided with a machine body which comprises an X-ray detection box module, a machine body shell and a machine body upper cover. The machine body upper cover is assembled at the upper end of the machine body shell, and the X-ray detection box module is assembled in the machine body shell; a shell inlet is formed in the side wall of the upper end of the machine body shell, a detection opening and a detection channel are formed in the upper end of the X-ray detection box module, and the shell inlet, the detection opening and the detection channel are communicated; a main control module is arranged to control the X-ray detection box module to detect the bone age of the hand in the detection channel and obtain detection data for analysis and processing; and a main support frame is arranged to support the X-ray detection box module and the machine body shell, so that measurement by a user is facilitated, the size of the bone age instrument is reduced, the structure of the bone age instrument is simplified, the assembly difficulty of the bone age instrument is reduced, and the carrying convenience of the bone age instrument is improved.

The embodiment of the present invention provides a bone age assessment method, comprising: obtaining a skeletal map and a voiceprint sequence of a target person; extracting features from the skeletal map through a preset image feature extraction network to obtain skeletal features of the skeletal map; extracting features from the voiceprint sequence through a preset voiceprint feature extraction network to obtain voiceprint features of the voiceprint sequence; fusing skeletal features with voiceprint features through a preset first feature fusion network to obtain fusion features of skeletal features and voiceprint features; classifying the fused features for bone age through a preset classification network, and assessing the target person's bone age based on the classification results of the bone age classification to obtain a bone age assessment result for the target person. The method can detect the age corresponding to the bones in the skeletal map, and because voiceprints are added as auxiliary detection, the accuracy of bone age assessment is improved, and there is no need for doctors to manually observe the skeletal map and interpret the skeletal image, thereby improving the efficiency of bone age assessment.

The present invention relates to a method for predicting bone age of children, comprising the following steps: randomly selecting a part of hand X-rays from a public data set of hand X-rays with bone age labels to form a data set, and adjusting all pictures to a specified size; establishing a TENet model and constructing a training set at the same time; using the training set as the input of the TENet model, using the Adam optimizer to train the TENet model, and obtaining a trained TENet model when the maximum number of iterations is reached. The model of the present invention can accurately predict the bone age of children.

The present invention discloses a real-time monitoring system for teenagers' physical exercise, which relates to the field of intelligent monitoring technology. Through the spatiotemporal alignment processing of joint three-dimensional motion, electromyographic signals, and plantar pressure and the dynamic matching technology of bone age, an individualized health assessment model is constructed. Timing deviation is eliminated through unified clock marking and interpolation compensation, and parameters such as bone stress deviation, muscle synergy asymmetry, and plantar pressure imbalance are extracted, and weighted comprehensive health indicators are generated. Combined with a preset training path model, the health indicator trend is analyzed in real time and hierarchical adjustment instructions are triggered, the training intensity, interval and action plan are dynamically optimized, and the path model parameters are corrected through a closed-loop feedback mechanism to achieve adaptive updates. It solves the defects of large fusion deviation and strong lag of static evaluation of traditional teenagers' physical fitness monitoring data, realizes real-time and accurate monitoring of teenagers' physical exercise and personalized training optimization, and effectively reduces the risk of sports injuries.

The invention belongs to the technical field of medicines, and particularly relates to application of lycium barbarum glycopeptide in preparation of a medicine for preventing or treating senile ossification. The experimental results show that the wolfberry glycopeptide can improve the posterior limb movement ability and the bone trabecula condition of old mice by increasing the femoral hardness, relieving the bone tissue calcium loss condition, improving the bone formation rate, promoting osteoblasts and inhibiting osteoclasts, so that the effect of treating bone aging is achieved. As a traditional Chinese medicinal material extraction product, the lycium barbarum glycopeptide can be effectively used for preventing and treating senile ossification, has the prospect of being developed into the medicine for preventing and treating senile ossification, provides more treatment choices for clinically preventing or treating senile ossification, and has important social benefits and economic values.

The present invention discloses a positioning device and a detection method for collecting bone age images of children, belonging to the technical field of bone age detection, specifically including: setting a standard inspection period, collecting bone age images of children every period and obtaining inspection records written by medical staff; these records are then input into a preset BERT model to extract bone age feature keywords; an auxiliary detection model is constructed using a convolutional neural network and a recurrent neural network and trained through a labeled historical data set; the child's age and keywords are converted into vectors and input into the trained auxiliary inspection model, and the bone age difference between the child's actual age and bone age is output; every n inspection periods, the system will statistically analyze the bone age difference sequence of the child, calculate the inspection period adjustment coefficient according to the index and through a specific formula, and then adjust the number of days of the next n inspection periods; the present invention improves the popularization rate and effectiveness of bone age detection.

This invention discloses a bone age-assisted diagnostic system and method based on multimodal clinical data fusion and retrieval enhancement. The system includes acquiring X-ray images of the subject's hand and multimodal clinical data containing endocrine indicators; extracting visual feature vectors from the images using a deep learning model and encoding the clinical data into clinical semantic feature vectors; deeply fusing visual and clinical features through a multimodal cross-attention mechanism to generate diagnostic fusion features; predicting bone age values ​​based on the fusion features; retrieving standard atlas descriptions from a medical knowledge base using visual features and retrieving disease risk warnings using the fusion features; and finally inputting the predicted values, atlas descriptions, and risk warnings into a generative large language model to generate a natural language diagnostic report containing imaging evidence and clinical recommendations. This invention solves the problem of existing technologies relying solely on images and being unable to interpret the basis for judgment.

The utility model provides a bone age instrument detection structure, which comprises a support frame used for providing fixed support; the supporting plate is arranged at the upper end of the supporting frame; the bottom plate is arranged at the lower end of the supporting frame; the ray generator is arranged on the upper surface of the supporting plate and emits detection rays towards the bottom plate; the detector is arranged on the upper surface of the bottom plate, and the detector and the ray generator are oppositely arranged; and the channel assembly is arranged above the detector, the channel assembly is provided with a channel window for an object to be detected to enter and exit, and a positioning assembly for assisting in positioning the detection position is arranged in the channel assembly. The bone age instrument detection structure has the advantages of being convenient to position and detect and good in shielding protection.

The invention provides a forensic medicine pelvic adult bone age estimation method based on enhanced OfficientNetV2. The forensic medicine pelvic adult bone age estimation method comprises the following steps: firstly, acquiring MSCT image data of a pelvis; performing 3D reconstruction on the MSCT image data to obtain 3D image data; and finally, determining a bone age estimation result of the forensic pelvic adult according to the preprocessed and data enhanced MSCT image data, the 3D image data and the enhanced OfficientNetV2 model. According to the enhanced OfficientNetV2 model, a linear layer and a nonlinear activation function are added on the basis of an OfficientNetV2 model, so that an output value of the model is mapped into a predicted value, and the predicted value is controlled within a specified range. According to the pelvic adult bone age estimation method based on the deep learning, an original OfficientNetV2 model is improved, a linear layer and a nonlinear activation function are added to map an output value of the model into a predicted value and control the predicted value in a specified range, exploratory application of deep learning in the aspect of forensic pelvic adult bone age estimation is achieved, the influence of subjective factors is effectively avoided, and the accuracy of an automatic recognition result is improved.

A method for calculating a predicted adult height according to one embodiment of the present application includes generating a growth prediction model; and calculating a predicted adult height using the generated growth prediction model, wherein the generating the growth prediction model further includes acquiring input data and growth statistical data, including height information at the time of measurement, chronological age information at the time of measurement, bone age information at the time of measurement, and gender information; calculating an adult height based on the input data and the growth statistical data; and generating the growth prediction model based on the input data and the calculated adult height.

1. The name of the design product: micro-aging bone age instrument detection device. 2. The use of the design product: for human bone age determination. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view. 5. The bottom of the design product is not easy to see or not visible during use, omit the top view.

The invention discloses a bone age detection device and method, and relates to the technical field of bone age detection.The device comprises a solid sound conducting pad bracelet, an ultrasonic function module and a forearm fixing and position adjusting module; the ultrasonic function module comprises an ultrasonic image processing system and two ultrasonic probes; the ultrasonic image processing system is used for obtaining the maximum value of the transverse diameter of the ossification center and the maximum value of the transverse diameter of the epiphysis according to the ultrasonic data; according to the maximum value of the transverse diameter of the ossification center and the maximum value of the transverse diameter of the epiphysis, the ultrasonic epiphysis ossification rate is calculated; and comparing the ultrasonic epiphyseal ossification rate with the standard characteristic data to obtain the age corresponding to the ultrasonic epiphyseal ossification rate. According to the method, the bone age is detected in an ultrasonic mode, so that radioactive X-rays are prevented from being used, meanwhile, the calculated ultrasonic epiphyseal ossification rate is compared with the standard characteristic data, the corresponding age is obtained, and the objectivity and accuracy of bone age detection are guaranteed.

The invention provides a bone age AI prediction system based on MRI, and belongs to the technical field of medical image processing. The system comprises a data acquisition unit used for acquiring joint MRI image data; the data preprocessing unit is used for preprocessing the joint MRI image data; and the bone age prediction unit is used for performing bone age prediction according to the preprocessed joint MRI image data by utilizing the trained bone age prediction model and outputting a bone age differential diagnosis result. According to the system, MRI images are used for bone age prediction, radiation damage in the radiography process is avoided, meanwhile, MRI has the advantages that cartilage around epiphysis is accurately visualized, the contrast ratio is high, data are easy to store, the system is suitable for bone age prediction research, meanwhile, pure automatic prediction is adopted, human factor interference can be reduced, and accuracy is high.

The application provides a palate midline suture maturity prediction method based on deep learning, obtains a plurality of head lateral film image samples, respectively labels palate midline suture maturity information, and obtains a head lateral film image dataset; a palate midline suture maturity prediction model is constructed, the palate midline suture maturity prediction model comprises an image preprocessing module, a feature extraction module, a hybrid multi-scale attention convolutional neural network and a feature fusion module; the head lateral film image dataset is used to train the palate midline suture maturity prediction model, and a trained palate midline suture maturity prediction model is obtained; after a head lateral film image to be predicted is input into the trained palate midline suture maturity prediction model, a palate midline suture maturity prediction result is obtained; the application can reduce subjective differences of artificial interpretation, can improve the accuracy, consistency and reliability of bone age prediction, can realize non-invasive, objective and efficient palate midline suture maturity prediction, and provides a scientific basis for clinical expansion arch treatment decision-making.

The embodiment of the present application provides a key point labeling method based on bone age detection and a related device. Among them, a key point labeling method based on bone age detection includes: obtaining a target DR image; labeling each bone of the m bones in the target DR image, and obtaining the epiphyseal point corresponding to each bone in the m bones; connecting the center point of the line between the epiphyseal point corresponding to the ulna bone and the epiphyseal point corresponding to the radius bone with the epiphyseal points corresponding to the n bones respectively, and determining the vertical line perpendicular to the line between the center points corresponding to each epiphyseal point in the n epiphyseal points; in the finger area corresponding to the i-th bone, according to the vertical line corresponding to the i-th bone, calculate the center of mass corresponding to the i-th bone; if the center of mass coincides with the epiphyseal point corresponding to the i-th bone, then update the epiphyseal point corresponding to the i-th bone to the key point of the i-th bone. The embodiment of the present application can improve the accuracy of key point labeling when detecting bone age.

The invention provides a training method of a bone age prediction model and a bone age prediction method and device. The invention relates to the technical field of computers, in particular to a bone age prediction model training method which comprises the steps that a plurality of first samples and a plurality of second samples are obtained, the first samples comprise hand bone image samples of human bodies in a first group, and the second samples comprise hand bone image samples of human bodies in a second group; the group scale of the first group is larger than that of the second group; and using the sequence knowledge of the relative ages contained in the plurality of first samples to assist the plurality of second samples to train the bone age prediction model to obtain a target bone age prediction model for the second group.

The invention relates to a remote artificial intelligence detection method and system for a bone age digital X-ray image, and the method comprises the following steps: remotely obtaining X-ray image data which are obtained through the transmission of a 5G private network in a desensitization encryption mode; carrying out normalization processing on the received X-ray image data; according to the X-ray image data after normalization processing, needed GPU computing power resources are judged, and at least one needed AI computing server is called based on the load balancing principle; acquiring a bone age detection result of the AI computing server, and generating a detection report; wherein the X-ray image data and the detection report are stored in an AI storage device, and the storage of the X-ray image data and the detection report follows an IHE integration specification. Compared with the prior art, the problems that bone age detection resources are deficient, the cost is high, privacy is prone to being leaked and the like in basic and remote areas are effectively solved, and the detection efficiency and the service coverage are improved.

The utility model relates to the technical field of X-ray sources, and discloses an X-ray source for a medical bone age machine and a bone mineral density instrument, which comprises a main control assembly and a machine head assembly which are connected with each other through a cable, the machine head assembly comprises an X-ray tube, an anode flow limiting plate, a cathode flow limiting plate, a voltage-multiplying rectifying plate and a sealing interface plate, the two ends of the X-ray tube are connected with the anode flow limiting plate and the cathode flow limiting plate respectively, the anode flow limiting plate is connected with an E7 pin of the voltage-multiplying rectifying plate, the cathode flow limiting plate is connected with an E6 port of the voltage-multiplying rectifying plate, an MJ1 port and an MJ2 port of the voltage-multiplying rectifying plate are connected with the sealing interface plate, and the sealing interface plate is connected with the X-ray tube. The main control board is provided with an interface circuit, a tube current control circuit and a main controller; only a simple interface circuit is needed for control, and the difficulty of system integration is reduced; a framework is adopted in the machine head assembly for insulation, and a transformer and a circuit board are highly integrated, so that the whole machine is small in size, small in occupied space and high in flexibility.

The invention relates to a method for three-dimensionally printing bone organs and application, belongs to the technical field of three-dimensional printing, and provides a material composition for three-dimensionally printing the bone organs, the material composition comprises bio-ink, osteoblasts and osteoclasts, and the number ratio of the osteoblasts to the osteoclasts is 1: (2-3.5). Meanwhile, the invention provides a method for carrying out three-dimensional printing on a bone organoid by utilizing the material composition and a method for preparing a bone aging organoid. The bone organoid provided by the invention provides an ideal experimental platform for pathogenesis research of degenerative bone diseases, can be used for bone tissue engineering research, can also provide an important experimental basis for drug screening, treatment strategy optimization and the like of degenerative diseases such as osteoarthritis and the like, and has remarkable scientific value and application potential.

This invention discloses a self-activated NO nanopump, its construction method, and its application. The self-activated NO nanopump comprises a chemiluminescent substrate CPPO and a NO donor BNN6 encapsulated in DSPE-PEG-Mal. The DSPE-PEG-Mal surface is conjugated with a LepR antibody. The self-activated NO nanopump of this invention can specifically target LepR... + It accumulates in cells and releases intracellular NO, thereby effectively reversing cellular aging and differentiation fate. It rescues bone aging by upregulating the glycolysis pathway. It possesses strong H2O2 scavenging capacity, NO production capacity, and anti-aging ability. In vivo administration significantly reverses osteoporosis in OVX mice. The self-activated NO nanopump provided by this invention offers a novel strategy for the treatment of bone aging.

The invention discloses a self-service detection type campus bone age instrument, and relates to the technical field of bone age detection equipment, the self-service detection type campus bone age instrument comprises a mounting seat, a detection assembly, a positioning assembly and a fixing glove, the detection assembly comprises a detection chamber and an X light source, the detection chamber is provided with a detection port in the outer wall of the mounting seat, and the X light source is arranged in the detection chamber; the positioning assembly comprises a driving roller, a driven roller and a plurality of imaging chain plates, the driving roller is rotationally arranged in the detection chamber, the driven roller and the driving roller are arranged in parallel and rotationally arranged in the detection chamber, the imaging chain plates are rotationally connected in sequence, the imaging chain plates are wound around the driving roller and the driven roller, first hook-and-loop fasteners are fixedly connected to the outer walls of the imaging chain plates, and second hook-and-loop fasteners are fixedly connected to the outer walls of the imaging chain plates. When the driving roller rotates, the driving roller is matched with the driven roller so as to drive the imaging chain plates to move around the driving roller and the driven roller at the same time. And a second magic tape is fixedly connected to one side of the back of the fixed glove. The method has the effect of improving the bone age detection efficiency of children.

The invention discloses a bone age prediction method, device and equipment based on a deep learning model, and belongs to the technical field of medical image analysis, and the bone age prediction method comprises the steps: carrying out the preprocessing of an original hand bone image of a current user, and obtaining a target hand bone image; inputting the target hand bone image into a trained region cutting network to obtain a target segmentation region; inputting the target hand bone image marking the target segmentation region into a trained deep learning model, so as to enable the deep learning model to extract hand bone features of the current user from the target segmentation region; and predicting the bone features of the hand bones by using a regression model to obtain bone age prediction data of the current user. According to the method, accurate skeleton region segmentation is performed by using the segmentation network, and the bone age prediction is performed in combination with the deep learning model, so that the interference of background noise can be avoided while effective skeleton features are extracted, and the prediction accuracy and reliability are remarkably improved.