1236 results about "Bone quality" patented technology

The invention relates to the technical field of biological medicines, and provides application of an ADRM1 inhibitor in preparation of a medicine for treating osteoporosis. Through the scheme of the invention, the ADRM1 affects bone metabolism, bone tissue morphological structure and osteoporosis progress, and can provide a new drug target for clinical prevention and treatment of osteoporosis. The ADRM1 inhibitor is applied to preparation of the osteoporosis medicine, and bone mass loss can be obviously reduced by down-regulating ADRM1 expression or inhibiting ADRM1 activity and inhibiting differentiation and functions of osteoclasts, so that the effect of treating osteoporosis is achieved.

The invention relates to the technical field of osteoporosis diagnosis, and discloses an osteoporosis diagnosis method based on image recognition. The method comprises the following steps: acquiring bone density image data of a target object and bone structure image data of a target area based on medical imaging equipment, and determining a bone trabecula distribution condition of the target area according to the bone structure image data; constructing a three-dimensional bone mineral density model of the target object according to the bone mineral density image data, and determining an image analysis strategy by combining the three-dimensional bone mineral density model and the bone trabecula distribution condition; and an image analysis module acquires bone structure feature data of the target area according to the strategy, and identifies the bone density grade and the osteoporosis degree of the target area according to the feature data to obtain diagnosis data. According to the method, related data of the bone mineral density and the bone structure are integrated, comprehensive analysis is carried out in combination with the image recognition technology, an efficient and reliable new mode is provided for clinical diagnosis, the accuracy and objectivity of osteoporosis diagnosis are improved, and misdiagnosis and missed diagnosis are reduced.

The invention discloses an intelligent identification system for an osteoporosis area, belongs to the field of image processing calculation, and aims to solve the problems of limited technical coverage and lack of a dynamic optimization mechanism. In a feature extraction stage, a system combines traditional image processing and deep learning technologies in parallel, extracts bone trabecula multidirectional texture features by using a Gabor filter and a local binary pattern algorithm, analyzes bone contour curvature by combining Sobel edge detection and morphological operation, constructs geometric morphological parameters, and performs feature extraction on the bone trabecula. The local branch focuses on the porosity and arrangement rule of the bone trabecula by adopting a 3D convolutional network, the global branch is embedded into a compression excitation module based on an improved MobileNetV3 network to strengthen the overall morphological expression of the bone, the response intensity of a local microstructure is enhanced by space attention, the weight of global bone topological characteristics is calibrated by channel attention, and a multi-scale splicing strategy is combined, so that the overall morphological expression of the bone trabecula is optimized. And finally, outputting a fusion feature matrix after noise suppression, and remarkably improving the expression ability of pathological features.

The invention provides an osteoporosis prediction method and system based on a centrum CT image, and the method comprises the steps: obtaining a patient centrum CT image, and carrying out the preprocessing of the image, and obtaining standardized three-dimensional voxel data; performing spatial resampling on the original data to a uniform resolution; constructing a hierarchical feature extraction network for centrum bone structure perception, and designing a non-uniform sampling mechanism for centrum density distribution; constructing an intervertebral biomechanical conduction diagram network; designing an osteoporosis specific loss function; and outputting a grading prediction result containing confidence, generating probability distribution of each grade through a softmax function, and generating a visual thermodynamic diagram of the lesion area. Through time sequence consistency constraint, the system can analyze image changes of the same patient at different time points and evaluate the treatment effect and the disease progress. The dynamic monitoring ability provides a powerful tool for long-term management of chronic osteoporosis, and is helpful for timely adjustment of treatment schemes and improvement of prognosis of patients.

The invention relates to the technical field of medical data processing, in particular to a postmenopausal osteoporosis patient medical data analysis method and system, and the method comprises the following steps: extracting a bone mineral density measurement value and a bone metabolism index concentration based on patient bone mineral density data, bone metabolism index data and fracture event records; according to the method, through combination of covariance matrix calculation, feature value and feature vector extraction and revealing of deep relevance between data, fine description of bone mineral density and metabolism index changes is achieved, state probability values, fracture records and drug use data are subjected to normalization weighting processing, and an optimized posterior state distribution matrix is generated; the accuracy and comprehensiveness of data fusion are improved, a key dynamic feature set is extracted through screening and accumulation operation, the pertinence and efficiency of analysis and normalization and time interval prediction of a trend curve are optimized, a quantitative result of the bone mineral density change trend and the fracture risk is formed, and high-precision support is provided for illness state assessment and personalized analysis.

The invention provides a nutritional composition and application of the nutritional composition. The nutritional composition comprises medium-chain and long-chain fatty acid triglyceride and a milk fat globule membrane in a mass ratio of (2: 1)-(97: 1), and the medium-chain and long-chain fatty acid triglyceride and the milk fat globule membrane have a synergistic effect in the aspects of promoting skeletal development, especially increasing bone mineral density and / or preventing or treating osteogenesis insufficiency and / or osteoporosis.

The invention provides a compound with a structure as shown in a formula (I). The compound can be used as a polyphenol organic ligand to be self-assembled with metal ions to form metal polyphenol nanoparticles. The nano-particles have a bone targeting effect, are safe, effective, stable and uniform, can realize whole-body transfer, can be degraded in a bone pathology microenvironment, have regulation and control effects on bone resorption and bone formation, can cooperatively regulate and control bone balance, and have a great application prospect in the field of bone diseases such as osteoporosis. # imgabs0 #

The invention provides a multi-modal data and interaction quantification-based senile osteoporosis dynamic risk assessment method. The method comprises the steps of screening effective variables in candidate risk factors; collecting structured data and unstructured data, and cleaning and standardizing the data to obtain multi-mode data of a patient; calculating a statistical weight and a clinical weight to obtain a multi-dimensional weight, calculating a dynamic total risk integral of an effective variable, and quantifying a variable interaction effect; and carrying out risk level layering and clinical intervention suggestion to obtain a dynamic risk assessment result, and then carrying out internal cross validation and external data set validation. According to the method, data full coverage, weight self-adaption and risk dynamic interaction analysis can be achieved, scientificity, sensitivity and clinical friendliness of osteoporosis screening are greatly improved, the method is low in cost and high in prediction precision, risk grading is associated with specific prevention and treatment measures, and a prevention and treatment integrated information closed loop is achieved.

The invention provides an osteoporosis automatic diagnosis method and system based on position specific attention, and the method comprises the steps: carrying out the dual-channel enhancement preprocessing of a lumbar CT image, and generating an enhanced image taking the bone mineral density and the bone trabecula structure characteristics into consideration; inputting the enhanced image into a deep convolutional neural network for multi-scale feature extraction to obtain a feature map containing spatial semantic information; on the basis of the anatomical position index information, generating attention weighted features which highlight the key diagnosis area of the vertebral body; global pooling is carried out on the attention weighted features, and then comprehensive diagnosis features containing anatomical priori knowledge are constructed; and inputting the comprehensive diagnosis features into a classifier to realize centrum-level accurate diagnosis. According to the invention, the workload of radiologists can be effectively relieved, and the efficiency and coverage of osteoporosis screening can be improved. Especially under the condition that primary medical institutions are lack of experienced radiologists, the primary medical service level can be improved.

The invention relates to a metabolic marker for diagnosing diabetic secondary osteoporosis and application of the metabolic marker, and belongs to the technical field of biological medicine. The method comprises the following steps: firstly, screening out obviously different metabolites between osteoporosis (DOP) and osteoporosis-free groups (DM) in diabetic patients; and secondly, screening out significant difference metabolites between the primary osteoporosis patient and the healthy control group, and excluding the intersection of the two groups of difference metabolites to obtain metabolites which exclude the influence of the primary osteoporosis. Metabolic markers, namely cytosine nucleotide, ketoglutaric acid and triethylamine, are obtained through further screening, and when the three metabolic markers are independently used, AUCgt; the AUC during combined use is 0.99, so that the limitation that the sensitivity of the traditional bone mineral density detection on the osteoporosis recognition in the diabetic population is insufficient is effectively made up.

The invention belongs to the technical field of biological medicine, and discloses a probiotic agent capable of improving the physiological activity function of vitamin D and maintaining bone health and application of the probiotic agent. The invention provides a probiotic agent composed of bifidobacterium adolescentis and bifidobacterium longum, the probiotic agent can significantly improve the bone mineral density, the bone trabecula thickness, the bone trabecula number, the bone trabecula connectivity and the bone volume fraction of an osteoporosis mouse, and meanwhile, the bone trabecula separation degree of the osteoporosis-removed mouse is significantly reduced; the level of vitamin D metabolites such as 25-hydroxy vitamin D and 1, 25-dihydroxy vitamin D in mouse serum is improved; the content of serum calcium and alkaline phosphatase in serum of mice is reduced, and the level of osteocalcin and type I procollagen amino terminal peptide in the serum is improved. The probiotic agent can relieve bone calcium loss, maintain bone health, repair bone injury, increase osteoblasts and reduce the osteoporosis degree, and can be used for preparing drugs for preventing and / or treating osteoporosis or preparing health care products or food beneficial to improving bone mineral density.

The invention relates to the technical field of medical informatics, in particular to a construction method of an osteoporotic fracture risk prediction model. The method comprises the following steps: acquiring an included angle between a foot and the ground, a step speed and a CT image of a target person in a monitoring process; dividing pixel points in the CT image into a plurality of bone tissue areas; according to the shape distribution characteristics of the edge lines in the bone tissue area, bone characteristic values of the bone structure are obtained; obtaining a posture control factor of each gait according to the included angles between the left and right feet of the target person in each gait and the ground; determining an abnormal posture index of each gait in combination with the posture control factor and the corresponding step speed; obtaining a control disorder coefficient of each time period according to the numerical distribution characteristics and the change characteristics of all the posture control factors in each time period; and determining an osteoporosis evaluation value by integrating the bone characteristic value and the disorder control coefficient of the skeleton structure. The accuracy of the bone comprehensive evaluation result of the target person is improved.

The invention discloses an edentulous jaw dental implant positioning method combined with depth variation reasoning. The method comprises the following steps: S1, generating optimized medical image data; s2, generating a jaw bone three-dimensional reconstruction model of the edentulous jaw patient; s3, generating anatomical feature data; s4, generating a preliminary implant positioning scheme; s5, generating a local bone reconstruction simulation result; s6, performing dynamic interaction on a local bone reconstruction simulation result and the preliminary implant positioning scheme, optimizing the preliminary implant positioning scheme through a depth variation inference model, and generating an implant optimized positioning scheme including mechanical stability and biomechanical performance evaluation; and S7, based on the implant optimization positioning scheme, generating implant guide plate design data and surgical navigation data in combination with the jaw bone three-dimensional reconstruction model of the patient. According to the method, the final implant positioning point obtains a globally optimal solution in the aspects of long-term stability and biological adaptability.

The invention provides an osteoporosis auxiliary diagnosis method fusing CT image features and a semantic knowledge graph, and the method is characterized in that the method comprises the steps: multi-source heterogeneous data collection and standardization processing; constructing a modal exclusive depth coding network; mapping and aligning a unified semantic space; carrying out multi-level cross-modal attention fusion; self-adaptive segmentation and feature enhancement of anatomical perception are carried out; semantic reasoning guided by the knowledge graph; performing multi-task collaborative diagnosis output; and training optimization and interference elimination. Through automatic multi-modal analysis and intelligent diagnosis, the workload of doctors in the imaging department is remarkably relieved, and the diagnosis time of a single example is shortened to be within 3 minutes from the average 15-20 minutes. The standardized diagnosis process of the system improves the diagnosis consistency among different doctors, reduces the diagnosis deviation caused by experience difference, and helps primary hospitals to improve the osteoporosis diagnosis and treatment level.

The present disclosure includes methods and devices used to diagnose or treat or manage bone conditions such as osteoporosis. The present disclosure includes bone and soft tissue imaging methods, some of which involve specific patient positioning and alignment of bodily regions and ensuring consistent imaging at multiple time points. Several artificial intelligence-based techniques are also disclosed that process imaging data and other clinical inputs using machine learning models and other methods to obtain desired clinical information. The disclosed artificial intelligence-based techniques are designed to use imaging data and other clinical inputs generated by the imaging methods and devices of the disclosure or existing imaging data and other clinical inputs.

The invention relates to the technical field of biomedical materials, in particular to a titanium implant multifunctional composite coating with anti-active oxygen and anti-inflammatory dual performance and a preparation method of the titanium implant multifunctional composite coating. The coating is composed of a lanthanum oxide (La2O3) nano-particle layer growing on the surface of the titanium implant in situ and queen lily glycoside A (RA) loaded on the lanthanum oxide (La2O3) nano-particle layer and can continuously release La < 3 + > and RA. The preparation method comprises the following steps: performing alkali heat treatment on the titanium substrate; a La (OH) 3 coating is synthesized on the surface in situ through a hydrothermal reaction; the La2O3 nano-particles are calcined and converted into a La2O3 nano-particle layer with a porous structure; and finally loading RA through an impregnation method. The coating can effectively remove ROS, regulate immune inflammatory response, promote osteogenic differentiation and inhibit osteoclast activity, thereby remarkably promoting osseointegration. The problem of osseointegration under the osteoporosis pathological microenvironment is effectively solved, the preparation process is simple and controllable, and the composition is suitable for bone defect repair of osteoporosis patients and has important clinical application value.

The invention discloses an impacted wisdom tooth extraction resistance analysis simulation method and system based on CBCT and AI segmentation, is suitable for scenes of extraction resistance intelligent analysis and preoperative path simulation of impacted wisdom teeth, and assesses risks by automatically measuring the minimum spatial distance between the tooth root tip of a wisdom tooth to be extracted and a dental nerve tube. A resistance removal strategy is selected by performing three-dimensional mechanical analysis on adjacent tooth resistance, bone resistance and tooth root resistance of a wisdom tooth to be extracted, and a wisdom tooth extraction simulation path is planned based on a risk assessment result and the resistance removal strategy. According to the method, complex impacted wisdom teeth are analyzed for the first time, risk assessment and three-dimensional mechanical analysis related to an operation are achieved, and special modeling, risk assessment and tooth extraction resistance analysis can be conducted on the impacted wisdom teeth, especially the impacted mandibular wisdom teeth which are high-risk conditions that the shapes of adjacent neural tubes and tooth roots are complex and resistance sources are diversified; the pull-out difficulty, the resistance source and the intraoperative risk point are reflected, and the clinical use requirements are met.

The invention belongs to the field of medicines, foods and health-care products, and particularly relates to an accelerant with a bone growth effect and application of the accelerant in the fields of medicines, health-care foods and functional foods. According to the application disclosed by the invention, the inhibiting effect of the morurin on osteogenesis promoting and osteoporosis resisting marker post target osteosclerosis protein is found through high-throughput virtual screening for the first time and is verified through experiments; meanwhile, in-vitro and animal experiments prove the osteogenic differentiation promoting effect of the morusin for the first time. According to the present invention, the morusin and the pharmaceutically acceptable salt thereof can be adopted as the bone growth promoter, can be singly or jointly used, can be used for promoting bone growth and resisting osteoporosis, and can be used in the forms of drugs, health-care foods, functional foods, food additives and the like.

The invention provides a plant lactobacillus TH13, and the preservation number of the plant lactobacillus TH13 is CGMCC (China General Microbiological Culture Collection Center) NO.32112. The plant lactobacillus TH13 provided by the invention can be used for fermenting folium cortex eucommiae and enzymatically hydrolyzed bone meal, and the fermentation product of the plant lactobacillus TH13 has high content of chlorogenic acid, proline, glycine and lysine. The fermentation product can significantly improve the content of alkaline phosphatase (ALP) and osteocalcin (OCN) in mouse serum and reduce the content of tartrate-resistant acid phosphatase (TRACP). Therefore, the fermentation product can significantly improve the bone mineral density of the femur, increase the number of bone trabecula and significantly reduce the separation degree of the bone trabecula, thereby promoting bone formation of a mouse with senile osteoporosis, inhibiting bone resorption and improving senile bone loss and bone microstructure deterioration. The preparation method of the probiotic preparation containing the plant lactobacillus and the probiotic fermentation product is simple, and large-scale production can be realized.

The invention relates to the technical field of medical image processing, in particular to a method and system for identifying odontogenic jaw cyst and tumor based on deep learning, and the method comprises the steps: obtaining original jaw CBCT image data, carrying out the preprocessing, and generating a combined annotation data set containing lesion types, tooth root absorption form annotations and CT value annotations; constructing a multi-branch neural network model, and training the multi-branch neural network model by using the joint labeling data set to obtain an odontogenic jaw lesion recognition model; and obtaining jaw CBCT image data of a target patient, inputting the jaw CBCT image data into the odontogenic jaw lesion recognition model, and outputting lesion type classification results, tooth root absorption forms and bone destruction volumes. The diagnosis capability of minimal lesions can be improved, missed diagnosis is reduced, whole-process auxiliary diagnosis from qualitative diagnosis to quantitative analysis is realized, and the diagnosis speed is increased.

The invention relates to the technical field of oral implantation guidance, and provides a digital false tooth mounting and positioning device based on three-dimensional scanning and a method thereof. The method comprises the following steps: scanning the oral cavity of a patient through an oral cavity scanner to generate a three-dimensional oral cavity digital model; generating a virtual implant of the patient and corresponding initial implantation parameters based on the three-dimensional oral cavity digital model through a SegFormer segmentation network; based on historical operation data, initial implantation parameters, bone density, patient attributes and occlusal force parameters, a long sequence prediction network is adopted to predict the position offset and bone resorption degree of the virtual implant after osseointegration through a segmented attention mechanism and a network memory cache mechanism, and optimal implantation parameters are obtained; and pushing a visual dynamic model containing the candidate positioning strategy to the user based on the optimal implantation parameter, driving an oral cavity model printer to obtain an implantation guide plate model and an oral cavity environment model, assisting the user in verifying the installation effect of the candidate positioning strategy, and improving the accuracy of false tooth installation and positioning.

The invention relates to the technical field of biology, in particular to sporosarcina pasteurii with high urease activity and application of the sporosarcina pasteurii. The invention provides sporosarcina pasteurii sp., and the preservation number of the sporosarcina pasteurii sp. Is CCTCC (China Center For Type Culture Collection) M 2025059. The invention further provides application of the sporosarcina pasteurii Sporosarcina sp in induction of calcium carbonate deposition and solidification, and / or bone cultural relic reinforcement and / or bone cultural relic repair, and a method for reinforcing or repairing bone cultural relics. The screened strain has high urease activity, and the bone cultural relics can obtain high compressive strength by adopting the strain to reinforce and repair the bone cultural relics.

The invention discloses an osteoporosis prevention strategy analysis method and system, and belongs to the technical field of health data analys.The osteoporosis prevention strategy analysis method specifically comprises the steps that the bone mineral density of a user is measured and preprocessed, a T value is calculated and compared with a preset osteoporosis threshold value, and the osteoporosis condition is judged; for the osteoporosis user, risk self-evaluation is carried out, risk grades are divided, a personalized treatment scheme is formulated, and the effect is monitored; for non-osteoporosis users, a risk prediction model is established through an osteoporosis prediction algorithm, and risk scores are calculated and graded; formulating a prevention strategy according to the risk level, evaluating an effect and adjusting an algorithm and the strategy; according to the invention, accurate prevention and treatment of osteoporosis are realized.

The invention discloses a bone health tablet candy rich in marine peptide calcium chelate and a preparation method thereof, and belongs to the technical field of polypeptide biologication.The calcium chelating peptide provided by the invention has an amino acid sequence as shown in SEQ ID No.1, the specific sequence is GETGPA (F21-1), and the calcium binding capacity is 4.72 + / -1.06 mu g / mg. The bone health tablet candy provided by the invention has relatively good calcium absorption promoting activity. A mouse experiment result shows that no adverse effect is caused to mouse growth, high bone transition caused by osteoporosis can be reversed, the bone biomechanical property of the osteoporosis mouse is improved, and then the effect of enhancing the bone mineral density is achieved.

The invention discloses a yolk protein source tripeptide with a function of improving osteoporosis and application of the yolk protein source tripeptide, and belongs to the technical field of biological medicines. The tripeptide is a tripeptide APW of which the amino acid sequence is Ala-Pro-Trp. The peptide fragment can be obtained through artificial synthesis or directional enzymolysis of defatted yolk powder. Functional verification shows that the tripeptide APW and the egg yolk protein hydrolysate containing the peptide fragment have the function of improving the bone mineral density, and in a zebra fish osteoporosis model, when the egg yolk protein hydrolysate is 20 mu g / mL, the bone mineral density is improved by 58%; when the tripeptide APW is 0.5 mu g / mL, the bone mineral density is increased by 23.4%; in a rat osteoporosis model, the bone mineral density of thighbone is increased by 3.39% after 10 mg / kg. D of egg yolk protein enzymatic hydrolysate is eaten. Moreover, the food-borne bioactive peptide is high in biological safety, so that the tripeptide APW and a yolk protein enzymolysis product containing the peptide fragment can be applied to preparation of medicines for treating osteoporosis or health-care foods for improving bone mineral density, and the tripeptide APW has a good market prospect and application potential.

To provide an apparatus for the treatment or prevention of osteopenia and osteoporosis, stimulating bone growth, preserving or improving bone density, and inhibiting adipogenesis.SOLUTION: A vibration apparatus for treating a subject comprises an actuator configured to generate vibrational energy, a securing mechanism for positioning the actuator upon the body of the subject while maintaining portability of the actuator such that the vibrational energy is directed into an area of the body to be treated, an accelerometer disposed along the securing mechanism, and a controller in communication with the actuator and the accelerometer. The controller is programmed to measure an exposure level of the vibrational energy to the area of the body using acceleration acquired from the accelerometer, and to compare the exposure level with a maximum exposure level such that the exposure level is limited by the maximum exposure level within a predetermined period of time.SELECTED DRAWING: Figure 1

The invention discloses an image recognition system for constructing osteoporotic vertebral fracture healing based on artificial intelligence, and particularly relates to the technical field of orthopedic treatment, which comprises a data preprocessing module for extracting and optimizing data from an original medical image. According to the method, the advantage of discipline crossing is developed, a recognition system on medical imaging is developed based on deep learning, the advantage that the recognition system can discover detail features and hidden rules which cannot be found by human beings is utilized, and then a large amount of structured data is utilized to automatically learn and train visual feature expression of abstract data, so that the clinical missed diagnosis rate is reduced, and the clinical diagnosis efficiency is improved. The artificial intelligence architecture is trained by a rigorous and scientific means, so that the artificial intelligence architecture has clinical experience and knowledge of high-age dominant doctors and is popularized in local hospitals to achieve an auxiliary diagnosis effect, the difference of medical differentiation is reduced, the technical and experience defects of local medical personnel are made up, and the technical and experience defects of the local medical personnel are overcome. The aim of improving the definite diagnosis rate of diseases and reducing the missed diagnosis rate is one of the purposes of the invention.

The invention provides a chlorella pyrenoidosa calcium chelating peptide and a chlorella pyrenoidosa peptide calcium chelate prepared by using the chlorella pyrenoidosa calcium chelating peptide. The prepared chlorella pyrenoidosa peptide calcium chelate can enhance the maximum load and structural strength of the tibia of a mouse with osteoporosis. The chlorella pyrenoidosa calcium chelating peptide provided by the invention is combined with calcium ions to form a peptide-calcium chelate, and animal experiments prove that the peptide-calcium chelate can significantly improve the maximum load and structural strength of the tibia of a mouse with osteoporosis, and has a good effect of improving the bone biomechanical properties of the mouse with osteoporosis.

The invention relates to the technical field of data processing, and discloses a postmenopausal osteoporosis risk assessment system based on big data, a data preprocessing module is used for collecting multidimensional data of postmenopausal women and processing the collected data to obtain preprocessed data; the feature extraction module is used for extracting features related to the postmenopausal osteoporosis risk from the preprocessed data to obtain target feature data; the risk assessment module is used for constructing a risk assessment model based on the target feature data, inputting the original data of the to-be-assessed postmenopausal female into the risk assessment model after data preprocessing and feature extraction, and outputting a risk assessment result of osteoporosis of the to-be-assessed female; the result visualization module is used for visualizing the risk assessment result and providing corresponding intervention suggestions according to different risk levels; according to the invention, early prevention and intervention of postmenopausal osteoporosis can be realized.

The invention discloses a CT-based osteoporosis intelligent diagnosis method and system, and relates to the technical field of medical image diagnosis, and the method comprises the steps: carrying out the positioning of a lumbar region in an abdomen or thoracic and abdominal CT image through a deep learning model; digitally modeling the shape and the internal structure of the vertebral body; and automatic diagnosis of osteoporosis is completed. According to the method, full-automatic positioning, accurate segmentation and intelligent diagnosis of osteoporosis of the lumbar region in a conventional abdomen or thoracic and abdominal CT image are realized, the accuracy and efficiency of diagnosis are remarkably improved, and the problems of strong subjectivity and poor repeatability caused by dependence on manual sketching or simple threshold segmentation in a traditional method are solved; the method can be directly operated based on clinical conventional CT data, is beneficial to large-scale osteoporosis screening and early intervention, and has remarkable clinical popularization significance and technical progress value.