Detection of osteochondritis dissecans in ultrasound images for computer-aided diagnosis of baseball elbow.

Baseball elbow is a pitching elbow disorder caused by repeated pitching movements. Osteochondritis dissecans (OCD) is one of baseball elbow disorders, and is an intractable osteochondral injury that tends to occur in elementary and junior high school students. If it can be found in the early stages, it will be completely cured by conservative treatment, which is to set a period to stop playing baseball. Since there is almost no pain in the early stage, the hurdles for consultation are high and there are many cases in which the condition becomes severe. Periodical medical check of baseball elbow is effective, however, the number of implementations is several times a year due to the shortage of specialists who can make a diagnosis. In this study, for the purpose of developing computer-aided diagnosis (CADx) of early-stage OCD, we propose an OCD detection method using ultrasound images of the elbow. The proposed method first segments the humerus capitellum using fully convolutional network (FCN). Secondly, the segmented region is classified into OCD +/- classes using fine-tuning VGG16 to detect OCD. The proposed method was applied to 125 child baseball players including 61 OCD children and 64 healthy children. 5-fold cross-validation was conducted. The average detection results were 76.8% for accuracy, 100% for precision, 52.3% for recall, F1-score was 0.673, and AUC was 0.851.