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Abstract #2351

Preclinical Evaluation of Two Compressed Sensing Methods for DTI

Diego Alves Rodrigues de Souza1, Hervé Mathieu1,2, Jean-Christophe Deloulme1, and Emmanuel L. Barbier1,2
1Univ. Grenoble Alpes - Inserm U1216 - Grenoble Institut des Neurosciences (GIN), Grenoble, France, 2Univ. Grenoble Alpes - Inserm US17 - CNRS UMS3552 - CHUGA - IRMaGe, Grenoble, France


Compressed Sensing (CS) is not routinely implemented at the preclinical level, especially in case of multiple receivers. In this study, we evaluate preclinical Kernel Low-Rank and Conventional CS reconstruction schemes at 9.4T using a 4-channel receive coil and spin-echo data. By analyzing diffusion parametric maps and white-matter tracts, we evaluate the median absolute error, the structural similarity index measure and the mean fiber length as a function of the acceleration factor and of the CS reconstruction pipeline.

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