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Abstract #0664

Motion artifact quantification and localization for whole-body MRI

Thomas Kuestner1,2, Marvin Jandt2, Annika Liebgott2,3, Lukas Mauch2, Petros Martirosian1, Fabian Bamberg3, Konstantin Nikolaou3, Sergios Gatidis3, Bin Yang2, and Fritz Schick1

1Section on Experimental Radiology, University Hospital of Tuebingen, Tuebingen, Germany, 2Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany, 3Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany

Motion is still one of the major extrinsic factors degrading image quality. Automated detection of these artifacts is of interest, (i) if suitable prospective or retrospective correction techniques are not available/applicable, (ii) if human experts who judge the achieved quality are not present, or (iii) if a manual quality analysis of large databases from epidemiological cohort studies is impracticable. A convolutional neural network assesses and localizes the motion artifacts. This work extends the previously published method by proposing a general architecture for a whole-body scenario with varying contrast weightings. High accuracies of >90% were achieved in a volunteer study.

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