Detection of osteochondritis dissecans using convolutional neural networks for computer-aided diagnosis of baseball elbow

Baseball elbow is a kinetic disorder of the elbow caused by repetitive pitching in baseball. Osteochondritis dissecans (OCD), one of the most common forms of baseball elbow, is a disorder of the humeral capitellum of the elbow, and early detection of OCD is important. This study aims to create a mod...

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Bibliographic Details
Published inProceedings / International Symposium on Multiple-Valued Logic pp. 59 - 63
Main Authors Sasaki, Kenta, Fujita, Daisuke, Takatsuji, Kenta, Kotoura, Yoshihiro, Sukenari, Tsuyoshi, Minami, Masataka, Kobayashi, Yusuke, Kida, Yoshikazu, Takahashi, Kenji, Kobashi, Syoji
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 01.05.2023
Subjects
baseball elbow
deep learning
osteochondritis dissecans
Online AccessGet full text
ISSN2378-2226
DOI10.1109/ISMVL57333.2023.00022

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Summary:Baseball elbow is a kinetic disorder of the elbow caused by repetitive pitching in baseball. Osteochondritis dissecans (OCD), one of the most common forms of baseball elbow, is a disorder of the humeral capitellum of the elbow, and early detection of OCD is important. This study aims to create a model to detect OCD from ultrasound images of the elbow. The model is based on VGG16. The proposed method was validated by using 67 OCD subjects and 91 normal subjects. The results showed that the model achieved an accuracy of 88.5%, a precision of 87.9%, a recall of 97.0%, an F1 score of 0.910, and an AUC of 0.971.
ISSN:2378-2226
DOI:10.1109/ISMVL57333.2023.00022