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Abstract #0642

Towards Fast and Motion-Robust Foot and Knee MRI: Application of SAMER Retrospective Motion Correction with Deep Learning for 2D TSE and 3D SPACE

Daniel Polak1, Esther Raithel1, Rodrigo Andujar Lugo2, Andre Fischer1, Daniel Nicolas Splitthoff1, Bryan Clifford3, Elisabeth Gabler2, Wei-Ching Lo3, Lawrence L. Wald4, and Stephen Cauley3
1Siemens Healthineers AG, Forchheim, Germany, 2Friedrich-Alexander University, Erlangen, Germany, 3Siemens Medical Solutions USA, Boston, MA, United States, 4Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States

Synopsis

Keywords: Motion Correction, Motion Correction

Motivation: High-resolution imaging is required for detecting subtle pathologies in musculoskeletal MRI, but even slight involuntary patient motion during the lengthy exams can introduce artifacts that may degrade image quality.

Goal(s): Evaluate the effectiveness of SAMER retrospective motion detection and correction applied to knee and foot MRI.

Approach: SAMER was implemented into PDw and T2w 2D TSE and 3D SPACE sequences, utilizing scout and guidance lines for rapid motion estimation and a deep learning-based reconstruction framework to enhance image quality for highly accelerated acquisitions.

Results: Findings indicate significant reductions in motion artifacts and improved accuracy in automated cartilage segmentation in the knee.

Impact: SAMER retrospective motion correction was applied to knee and foot imaging and integrated with a deep learning reconstruction to facilitate fast and motion-robust 2D and 3D MSK imaging. This could enhance clinical diagnostics and improve patient outcomes in musculoskeletal MRI.

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Keywords