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Abstract #0352

Energy dependent z-scores improve parallel imaging motion correction using trimmed autocalibrating k-space estimation (TAKE)

Jeremy Beaumont1, Thomas Troalen2, Swetali Nimje1,3, Stanislas Rapacchi1, and Ludovic de Rochefort1
1Aix Marseille Univ, CNRS, CRMBM, Marseille, France, 2Siemens Healthcare SAS, Saint-Denis, France, 3Aix Marseille Univ, CNRS, LIS, Marseille, France


MRI motion corruption prevents clinical interpretation and image analysis for research purposes. The trimmed autocalibrating k-space estimation based on parallel imaging and structured matrix completion (TAKE) algorithm was previously proposed to retrospectively correct motion corrupted raw k-space data. This study proposes specific modifications of the TAKE algorithm to decrease its computation time and improve the detection of motion-corrupted k-space data. The proposed changes significantly improve the TAKE motion detection sensitivity and specificity along with its motion correction performance, while sufficiently decreasing its computation time to allow for its use in a standard clinical routine workflow.

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