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Abstract #1991

Reducing acquisition time for axon diameter mapping using global optimization in the spatial-angular-microstructure space

Anna Auria1, David Romascano1, Erick J. Canales-Rodriguez2, Tim B. Dyrby3, Daniel C. Alexander4, Jean-Philippe Thiran1,5, Yves Wiaux6, and Alessandro Daducci1,5

1LTS5, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland, 2Centro de Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Barcelona, Spain, 3Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 4Department of Computer Science and Centre for Medical Image Computing, University College London, London, United Kingdom, 5University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 6Institute of Sensors, Signals, and Systems, Heriot-Watt University, Edimburgh, United Kingdom

State-of-the-art microstructure imaging methods usually fit biophysical models to the diffusion MRI data on a voxel-by-voxel basis using non-linear procedures that require both long acquisitions and processing time. We recently introduced AMICO, a framework to reformulate these techniques as efficient linear problems and enable faster reconstructions. Here, we propose an extension that enables robust reconstructions from a reduced number of diffusion measurements, thus leading to faster acquisitions, too. Our novel formulation estimates simultaneously the microstructure configuration in all voxels as a global optimization problem, exploiting information from neighboring voxels that cannot be taken into account with existing techniques.

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