52 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 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 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 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.

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 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 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.

The utility model belongs to the technical field of medical instruments, and particularly relates to a digital X-ray bone age instrument for bone age detection, which comprises an outer protective box body, an X-ray generating component and a flat panel detector, an inner cavity of the outer protective box body is divided into a shooting space and an equipment mounting space, an extending opening for a hand to extend into is arranged on the outer protective box body, and the X-ray generating component is arranged on the outer protective box body. The outer side face of the outer protection box body is further provided with an extending opening, the extending opening is communicated with the shooting space in the inner cavity of the outer protection box body, the outer side face of the outer protection box body is further provided with an adjusting opening, the adjusting opening is communicated with the shooting space in the inner cavity of the outer protection box body, and the outer protection box body is further provided with an observation window. According to the utility model, the observation window and the adjusting port are arranged on the outer protective box body, so that a tested person can adjust the position and posture of a palm by himself / herself conveniently, other adults can stretch hands into a shooting space through the adjusting port conveniently, an infant whose palm is difficult to adjust to the correct position and posture by himself can be directly assisted to adjust, the use is more convenient, and the working efficiency is improved. And the use efficiency can be improved.

The invention provides a lifting type detection device based on bone age ultrasonic detection, and relates to the technical field of medical instruments. A group of moving frames are mounted on the base in a threaded manner, a group of moving arms are slidably mounted at the outer ends of the moving frames, a group of host machines are fixedly mounted at the tops of the outer ends of the moving frames, and limiting blocks at the outer ends of the bottoms of mounting seats are mounted on limiting grooves in the side ends of the ultrasonic detectors in an inserted manner; the device can realize height adjustment and angle fine adjustment, and an arc-shaped friction block is matched with a threaded rod to adjust the rotation tightness; the ultrasonic detector is quickly disassembled and assembled by utilizing a limiting block, a supporting rod and a second elastic piece; the movable arm is matched with the positioning groove through the guide block and the wedge-shaped block to realize position adjustment, so that the adjustability and the operation convenience of the device are integrally improved; the problems that the reliability of detection signals and results is influenced by inflexible adjustment, the accuracy comprehensiveness is reduced due to difficulty in adapting to various skeleton detection, the cost and time are increased due to tedious disassembly and maintenance of an ultrasonic detector, and the working continuity is influenced are solved.

The application discloses a coarse-to-fine bone age regression method based on multi-scale high-order self-attention, first extracts multi-scale features and multi-scale global self-attention response maps of the original hand bone image, fuses the latter and the down-sampling features of the original hand bone image to obtain fusion features, inputs the fusion features into a regression module, calculates an adaptive triad loss in the regression module to obtain a bone age regression value and an MSE loss for calculating the bone age, adjusts model parameters, trains the model on an original data set, then inputs the original data set into a backbone network, extracts high-dimensional representations of the image and inputs the high-dimensional representations into a K-means clustering algorithm, clusters the data set into multiple age stages, finally inputs the data in each age stage into multiple original backbone networks, trains multiple regression models, and obtains bone age prediction values in each age stage. The method can effectively perform left-hand bone regression detection of teenagers, and provides a general and efficient regression model and regression framework for a clinical computer bone age regression application scenario.

The invention relates to the technical field of medical imaging, in particular to an auxiliary positioning method and system for a dual-energy X-ray bone mineral density and bone age instrument. The method comprises the following steps: acquiring a real-time positioning image of a hand of a subject; dynamically adjusting the identification line template according to subject information to generate an individualized positioning identification line; image processing is conducted on the images collected in real time, whether the hand posture meets the preset standard or not is judged, the coincidence degree is judged, and if the coincidence degree is too low, an instruction is generated to conduct posture correction guiding; the positioning image and the individualized positioning identification line are displayed in a real-time overlapping mode; according to the generated prompt instruction, voice and character prompt is carried out, and the subject is guided to gradually adjust the hand position until the positioning requirement is met. According to the method, the individual hand structure difference is fully considered, the positioning mark line template is adaptively zoomed through the wrist width measurement result in the real-time image, and individualized matching of the template and the hand contour of the subject is achieved.

The invention discloses a children growth promoting preparation, which belongs to the technical field of traditional Chinese medicine preparations and comprises fructus alpiniae oxyphyllae, radix pseudostellariae, dried ginger, angelica sinensis, fructus amomi, radix inulae inula, pericarpium citri reticulatae, serissa serissoide, panax japonicus, rhizoma cibotii, radix scrophulariae and cattle bone powder. The preparation integrates the traditional Chinese medicine theory of tonifying spleen and kidney and regulating qi and blood, wherein the fructus alpiniae oxyphyllae, radix pseudostellariae, dried ginger and the like can tonify spleen and promote appetite, significantly improve the digestive function and improve the absorption rate of nutrient substances; the Tibet inula root and the fructus amomi regulate middle-jiao qi movement, relieve abdominal distension and qi stagnation and further optimize the absorption state; the panax japonicus, the rhizoma cibotii and the cattle bone powder directly act on a skeletal system to tonify kidney and strengthen bone, promote cartilage cell proliferation and bone longitudinal growth, and effectively improve height and growth speed. The formula gives consideration to intervention on growth disorder problems such as precocious puberty and the like, and through two-way regulation of nourishing yin and purging fire and tonifying kidney and replenishing essence, advanced bone age is delayed, and precious time is won for height increase.

1. Name of the Design Product: Digital X-ray Bone Age Analyzer. 2. Use of the Design Product: It is used for performing conventional X-ray photography on the hands and wrists of the human body to obtain X-ray images of the hands and wrists for clinical diagnosis, and for assisting in the detection of children's bone age and judging the development status of children's bones. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photo that Best Illustrates the Design Key Points: Perspective view.

The invention belongs to the field of bone age prediction, and particularly relates to an automatic bone age prediction method based on multi-modal feature matching. A hand bone X-ray image is obtained, and an enhanced hand region image is obtained through preprocessing; inputting the hand region into a segmentation network to obtain a plurality of local feature regions, and adding text tags according to the regions; corresponding image and text feature vectors are obtained through a feature matching network, and the weight of a feature extraction network is reserved; a targeted loss function is added in the training process; and finally performing fine tuning to obtain an automatic bone age prediction model. According to the method, the text labels are selected to carry out auxiliary feature matching, so that the feature positioning capability of the model on different local areas is improved. Through a cyclic feature matching mode, the generalization of the model on different data sets is improved, the effect of accurate prediction on different data sets through one model is achieved, the training overhead is saved, and the availability of the model is improved.

The application discloses a bone age prediction method, which comprises the following steps: pre-training a bone age prediction model through a preset training set, and using the bone age prediction model to predict the bone age. The technical scheme adds an attention mechanism according to the coupling degree of different convolution layer information in the bone age prediction model, improves the problem that the traditional attention mechanism is not easy to converge, and directly adds the gender information into the neural network model for end-to-end training, thereby optimizing the training process and further improving the accuracy of the bone age prediction. The bone age prediction model used in the bone age prediction method is verified through the attention mechanism, and the model pays more attention to the metacarpal part of the patient, thereby having a good prediction effect.