Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge
Year: 2021
Type: conference-paper
Authors: Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin De Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. Van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan Caan, Max Welling, Matthew J. Muckley, Florian Knoll
Institutions: NYU Langone Health, Philips (Germany), Yonsei University, Imperial College London, TUM Klinikum, Hyperfine, Inc. (United States), Technical University of Munich, Philips (Netherlands), University of Edinburgh, Leiden University Medical Center, University of Birmingham, University of Amsterdam, Johns Hopkins University, Amsterdam University Medical Centers, The Netherlands Cancer Institute, Meta (United States)
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W3204290769