Trabecular Bone Microarchitecture Assessment and Fracture Risk Prediction Using Machine Learning Techniques: A Short Review

摘要

Today, the technological explosion has led to the digitalization of many already proven applications thanks to the promising results it has provided. In fact, Computer-Aided Diagnosis (CAD) is one of the applications where digitization has played an effective role, especially with the advancement of medical imaging technology. Osteoporosis is one of the diseases diagnosed by computer today. It is a major skeletal disorder that predominantly affects women and has become a major impact on public health. this is a condition characterized by gradually decreased bone mass and deteriorated bone structure, causing bone fragility and fracture risk, especially of the wrist, hip, and spine. Considering the importance of machine learning in CAD systems design. This article provides an overview of various machine learning models for predicting osteoporosis risk. We will review the latest research in the AI application to predict osteoporosis and in particular that related to deep learning used to model the risk of fragility fracture and to help identify and segment images.