Classifying Dual-Energy X-ray Absorptiometry Images Using Machine Learning

Abstract

In this paper we study the ability of machine learning or convolutional neural networks in particular to be trained to classify dual-energy x-ray absorptiometry images of the spine and hip. For this purpose we create models which could differentiate images with healthy bone from images with pathology.