7 results about "Vertebral compression fracture" patented technology

The present invention relates to a system and a method for planning veterinary orthopedic surgery, for restoring volume and / or geometry of a bone, by expansion of at least one expandable bone implant (1) between a folded configuration and a deployed configuration, the implant comprising a body extending along a longitudinal axis (L) between a proximal end (11) connectable to an implantation instrument (A) for holding the implant and a distal end (12) intended to be inserted first into the bone, wherein the system comprises a plurality of expandable bone implants (1) and at least one implantation instrument (A) corresponding to each of the implants (1) and at least one planning support presenting the implants (1) and instrument (A), with reference to at least one standardized classification of the various types of fractures identified, in particular vertebral compression fractures, the planning support being capable of being implemented in the form of a human-machine interface.

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 invention relates to the technical field of early screening of osteoporotic compression fracture, and provides an osteoporotic compression fracture screening method based on a multi-modal large language model. A multi-modal large language model is introduced to carry out quantitative evaluation on key functions such as posture alignment, motion coordination and pain-related reactions of a patient from images and videos, and the key functions are output in a standardized scoring form, so that structural features with clear clinical significance are automatically extracted. And constructing a machine learning model based on the above structured features, evaluating the OVCF occurrence risk, and determining key discriminant factors and the action direction thereof in combination with an SHAP feature contribution analysis and decision tree visualization method, so as to realize interpretable expression of the prediction process. The technical scheme which is safe, low in cost, explainable and easy to popularize is provided for early screening of the OVCF, and the method is suitable for various application scenes such as community and home screening.

The present invention relates to a system and a method for planning veterinary orthopaedic surgery, for restoring the volume and / or geometry of a bone, by the expansion, between a folded configuration and a deployed configuration, of at least one expandable bone implant (1) comprising a body extending along a longitudinal axis (L) between a proximal end (11) that can be connected to an implantation instrument (A) for holding the implant, and a distal end (12) intended to be inserted first into the bone, wherein the system comprises a plurality of expandable bone implants (1) and at least one implantation instrument (A) corresponding to each of said implants (1), and at least one planning support having said implants (1) and instrument (A), with reference to at least one standardised classification of the various types of fractures identified, in particular vertebral compression fractures, it being possible for said planning support to be implemented in the form of a human-machine interface.

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.

A system and a method for planning human orthopaedic surgery for restoring the volume and / or the geometry of a bone, by expanding at least one expandable bone implant (1) between a folded configuration and a deployed configuration, the implant including a body extending along a longitudinal axis (L) between a proximal end (11) connectable with an implantation instrument (A) for holding the implant and a distal end (12) intended to be firstly inserted into the bone, wherein the system includes a plurality of expandable bone implants (1) and at least one planning support presenting the implants (1) and instrument (A), with reference to at least one standardized classification of the various types of fractures identified, in particular vertebral compression fractures, the planning aid being implementable in the form of a human-machine interface.