Anterior cruciate ligament classification in knee MRI using automated pseudo-masking

Saba Dadsetan; Marcio Albers; Allison Weinstock; Volker Musahl; Gene Kitamura; Dooman Arefan; Shandong Wu

doi:10.1117/12.2655278

7 April 2023 Anterior cruciate ligament classification in knee MRI using automated pseudo-masking

Saba Dadsetan, Marcio Albers, Allison Weinstock, Volker Musahl, Gene Kitamura, Dooman Arefan, Shandong Wu

Proceedings Volume 12465, Medical Imaging 2023: Computer-Aided Diagnosis; 124650B (2023) https://doi.org/10.1117/12.2655278
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

Anterior cruciate ligament (ACL) is one of the most common injuries associated with sports. Knee osseous morphology can play a role in increased knee instability. Our hypothesis is that the morphological features of the knee, as seen in knee osseous morphology, can contribute to increased knee instability and, thus, increase the likelihood of ACL tear. To test this relationship, it is necessary to segment the femur and tibia bones and extract relevant imaging features. However, manual annotation of 3D medical images, such as on magnetic resonance imaging (MRI) scans, can be a time-consuming and challenging task. In this work, we propose an automated pipeline for creating pseudo-masks of the femur and tibia bones in knee MRI. Our approach involves unsupervised segmentation and deep learning models to classify ACL integrity (intact or torn). Our results demonstrate a high agreement between the automated pseudo-masks and a radiologist’s manual segmentation, which also leads to comparable AUC values for the ACL integrity classification.

Conference Presentation

Citation Download Citation

Saba Dadsetan, Marcio Albers, Allison Weinstock, Volker Musahl, Gene Kitamura, Dooman Arefan, and Shandong Wu "Anterior cruciate ligament classification in knee MRI using automated pseudo-masking", Proc. SPIE 12465, Medical Imaging 2023: Computer-Aided Diagnosis, 124650B (7 April 2023); https://doi.org/10.1117/12.2655278

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