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Abstract #0645

Accelerated knee imaging using a deep learning based reconstruction

Florian Knoll1,2, Kerstin Hammernik3, Elisabeth Garwood1,2, Anna Hirschmann4, Leon Rybak1,2, Mary Bruno1,2, Tobias Block1,2, James Babb1,2, Thomas Pock3,5, Daniel K Sodickson1,2, and Michael P Recht1,2

1Radiology, NYU, New York, NY, United States, 2CAI2R, NYU, New York, NY, United States, 3Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria, 4Radiology, University Hospital Basel, Basel, Switzerland, 5Austria Safety & Security Department, AIT Austrian Institute of Technology GmbH, Vienna, Austria

The goal of this study is to determine the diagnostic accuracy and image quality of a recently proposed deep learning based image reconstruction for accelerated MR examination of the knee. 25 prospectively accelerated cases were evaluated by three readers and show excellent concordance to the current clinical gold standard in identification of internal derangement.

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