Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet.

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet.

<h4>Background</h4>Magnetic resonance imaging (MRI) of the knee is the preferred method for diagnosing knee injuries. However, interpretation of knee MRI is time-intensive and subject to diagnostic error and variability. An automated system for interpreting knee MRI could prioritize high...

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Bibliographic Details
Main Authors: Nicholas Bien, Pranav Rajpurkar, Robyn L Ball, Jeremy Irvin, Allison Park, Erik Jones, Michael Bereket, Bhavik N Patel, Kristen W Yeom, Katie Shpanskaya, Safwan Halabi, Evan Zucker, Gary Fanton, Derek F Amanatullah, Christopher F Beaulieu, Geoffrey M Riley, Russell J Stewart, Francis G Blankenberg, David B Larson, Ricky H Jones, Curtis P Langlotz, Andrew Y Ng, Matthew P Lungren
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-11-01
Series:PLoS Medicine
Online Access:https://doi.org/10.1371/journal.pmed.1002699

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https://doi.org/10.1371/journal.pmed.1002699

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