3 results about "Vertebral compression fracture" patented technology

The present application relates to the technical field of image analysis, in particular to an MRI image edema recognition method for osteoporotic vertebral compression fractures, which comprises: acquiring a target MRI image corresponding to an osteoporotic vertebral compression fracture of a target patient, and dividing the target MRI image; determining a characteristic performance index; determining a merging possibility index between each two fragment regions according to the characteristic performance index difference, the gray difference and the position difference between each two fragment regions; adaptively merging the fragment regions in the target MRI image; based on all the seed points screened out, performing region segmentation on the target MRI image through a watershed algorithm; and screening out an edema region. The present application adaptively performs region segmentation on the image, comprehensively considers the gray distribution, gradient distribution and shape rule condition when screening the edema region, realizes edema region recognition, and improves the accuracy of edema region recognition.

The present application relates to the technical field of early screening of osteoporotic vertebral compression fractures, and proposes an osteoporotic compression fracture screening method based on a multi-modal large language model, which takes patient posture images and action videos and other unstructured visual data as input, introduces a multi-modal large language model to quantitatively evaluate key functions such as patient posture alignment, motion coordination and pain-related responses from images and videos, and outputs in the form of standardized scores, automatically extracting structured features with clear clinical significance. Based on the above structured features, a machine learning model is constructed to assess the risk of OVCF, and combined with SHAP feature contribution analysis and decision tree visualization methods, the key discriminant factors and their action directions are clarified, realizing the interpretable expression of the prediction process. A safe, low-cost, interpretable and easy-to-promote technical solution is provided for the early screening of OVCF, which is suitable for various application scenarios such as community and home screening.

This invention relates to the field of fracture risk prediction technology, and more particularly to a risk prediction system for osteoporotic vertebral compression fractures based on DES-DXA-MRI fusion. The data acquisition module acquires the patient's DES image data, DXA detection data, MRI image data, and clinical risk factor data. The data fusion module generates a multimodal fusion feature set containing both image modality features and clinical modality features. The risk prediction module calls a pre-trained multimodal fracture risk prediction model to predict the fracture risk probability, risk contribution factors, and development trends of each vertebral segment, generating a risk assessment result set. The network construction module constructs a vertebral fracture risk assessment network based on the assessment results, including the vertebral segment topology, risk factor association weights, and time-series evolution paths. The risk warning module generates a fracture risk warning instruction set and sends it to a clinical decision support platform to achieve accurate prediction and personalized intervention.