Trustworthy Deep Learning for the Automated Quantification of the Fatty Infiltration of the Rotator Cuff Muscles Using MRI

Background

The current method of classifying fatty infiltration is highly subjective and has low reliability, which may impact the decision-making for the management of rotator cuff tears. The purpose of this study was to present and evaluate a new deep-learning (DL) approach to automatically and objectively classify fatty infiltration of rotator cuff muscles on magnetic resonance imaging (MRI).