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Automatic Kellgren-Lawrence grade estimation driven deep learning algorithms

Publication ,  Conference
Li, N; Swiecicki, A; Said, N; O'Donnell, J; Jiranek, WA; Mazurowski, MA
Published in: Progress in Biomedical Optics and Imaging - Proceedings of SPIE
January 1, 2020

Knee osteoarthritis (OA) is a prevalent and disabling degenerative joint disease. Objectively identifying knee OA severity is challenging given significant inter-reader variability due to human interpretation factors. The Kellgren-Lawrence (KL) grading system is a commonly used scale to quantitatively characterize the severity of knee OA in knee radiographs. It is important to reliably identify severe knee OA since total knee arthroplasty (TKA) can provide significant improvement in patient quality of life for patients with severe knee OA. In this study, we demonstrate a deep learning approach to automatically assessing KL grades. Our approach uses faster R-CNN object detection network to identify the knee region and deep convolutional neural network for classification. We used a dataset of 7962 knee radiographs for each posteroanterior (PA) and lateral (LAT) views, to develop and evaluate our approach. Images with their corresponding KL grades were obtained from the Multicenter Osteoarthritis Study (MOST) dataset. Our network showed multi-class classification accuracy of 69.15 % when the assessment was made based on PA views and accuracy of 56.68 % when LAT views were used. The developed network may play a significant role in surgical decision-making regarding knee replacement surgery.

Duke Scholars

Published In

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

DOI

ISSN

1605-7422

ISBN

9781510633957

Publication Date

January 1, 2020

Volume

11314
 

Citation

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Li, N., Swiecicki, A., Said, N., O’Donnell, J., Jiranek, W. A., & Mazurowski, M. A. (2020). Automatic Kellgren-Lawrence grade estimation driven deep learning algorithms. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 11314). https://doi.org/10.1117/12.2551392
Li, N., A. Swiecicki, N. Said, J. O’Donnell, W. A. Jiranek, and M. A. Mazurowski. “Automatic Kellgren-Lawrence grade estimation driven deep learning algorithms.” In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 11314, 2020. https://doi.org/10.1117/12.2551392.
Li N, Swiecicki A, Said N, O’Donnell J, Jiranek WA, Mazurowski MA. Automatic Kellgren-Lawrence grade estimation driven deep learning algorithms. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2020.
Li, N., et al. “Automatic Kellgren-Lawrence grade estimation driven deep learning algorithms.” Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 11314, 2020. Scopus, doi:10.1117/12.2551392.
Li N, Swiecicki A, Said N, O’Donnell J, Jiranek WA, Mazurowski MA. Automatic Kellgren-Lawrence grade estimation driven deep learning algorithms. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2020.

Published In

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

DOI

ISSN

1605-7422

ISBN

9781510633957

Publication Date

January 1, 2020

Volume

11314