Meeting Banner
Abstract #0242

Deep Learning Assisted Full Knee 3D MRI-Based Lesion Severity Staging

Bruno Astuto Arouche Nunes1, Io Flament1, Nikan K. Namiri1, Rutwik Shah2,3, Matthew Bucknor1, Thomas Link2, Valentina Pedoia2,3, and Sharmila Majumdar2
11Department of Radiology and Biomedical Imaging, UCSF, San Francisco, CA, United States, 2Department of Radiology and Biomedical Imaging, UCSF, San Francisco, CA, United States, 3Center for Digital Health Innovation, UCSF, San Francisco, CA, United States

The goal of this study is to capitalizing on recent developments in Deep Learning (DL) applied to medical imaging. Specifically, we aim to (i) identify cartilage, meniscus, bone marrow edema (BEM) and ACL ligament lesions and assess severity providing full knee lesion severity assessment, and (ii) provide a condensed clinical history of patients in an automated manner.

This abstract and the presentation materials are available to 2020 meeting attendees and eLibrary customers only; a login is required.

Join Here