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Abstract #5133

An Algorithm for Detecting Short-Lived Motion-Induced Corruption in k-Space

Tim Höpfner1, Frank Werner1, Tobias Wech2, and Herbert Köstler2
1Institute for Mathematics, University of Würzburg, Würzburg, Germany, 2Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany

Synopsis

Keywords: Artifacts, Artifacts

Motivation: Motion-caused short-lived data inconsistencies present challenges for artifact reduction in magnetic resonance imaging.

Goal(s): Development of a method for automatically detecting motion-corrupted k-space lines in MRI data.

Approach: The proposed approach utilizes multiple statistical multiscale testing to identify motion-corrupted data.

Results: The method successfully detected corruptions in both simulated and in-vivo MRI data, enhancing the potential for artifact reduction in motion-sensitive MRI applications.

Impact: We propose a method to automatically detect k-space lines, corrupted by patient motion, using a multiscale scanning statistic, allowing to replace these data in optimized reconstructions.

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Keywords