Convolutional Neural Network Based Diagnosis of Bone Pathologies of Proximal Humerus

In this study automatically segmented PD weighted shoulder images were evaluated by the proposed convolutional neural network (CNN) to extract features and classify humeral head in three groups as normal, edematous and Hill -Sachs lesion with a success rate of %98.43. Compared to the state of art methods, our proposed CNN based diagnosis system is very promising to assist radiologists and orthopedists in decision making.
Source: Neurocomputing - Category: Neuroscience Source Type: research