Abstract #0645

Accelerated knee imaging using a deep learning based reconstruction

Florian Knoll^1,2, Kerstin Hammernik³, Elisabeth Garwood^1,2, Anna Hirschmann⁴, Leon Rybak^1,2, Mary Bruno^1,2, Tobias Block^1,2, James Babb^1,2, Thomas Pock^3,5, Daniel K Sodickson^1,2, and Michael P Recht^1,2

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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