Deep Learning for Automated Segmentation of the Hip Joint in X-ray Images

Abstract

Hip osteoarthritis is a widespread disease, with medical experts facing difficulties in this illness, due to a lack of standard grading score. Nevertheless, the minimum joint space width remains the most important score for osteoarthritis severity. Manual estimation of this metric is a tedious task, which can greatly benefit from employing an automated tool. While some research has been done in developing such a tool using deep learning methods, a novel and promising approach, most lack annotated data to use for training, which can be hard to obtain. Thus, thus research aims at developing a deep learning approach towards estimating the minimum joint space, while using automatically labels produced with an existing algorithm.