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 Thiran^1,5, Yves Wiaux⁶, and Alessandro Daducci^1,5

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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