Abstract #2037

Validation of MRI-based axon radius index estimation using large-scale light microscopy and deep learning

Mohammad Ashtarayeh¹, Laurin Mordhorst¹, Maria Morozova^2,3, Tobias Streubel^1,2, Jan Malte Oeschger¹, Joao Periquito⁴, Andreas Pohlmann⁴, Henriette Rusch³, Carsten Jäger², Thoralf Niendorf⁴, Nikolaus Weiskopf^2,5, Markus Morawski^2,3, and Siawoosh Mohammadi^1,2

¹Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, ²Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ³Paul Flechsig Institute of Brain Research, University of Leipzig, Leipzig, Germany, ⁴Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany, ⁵Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany

We used a new method for validation of MRI-based axon radius index (ARI) mapping using large-scale light microscopy (lsLM) that provides a good representation of the fraction of large axons - the main contributors to the MRI-based ARI. The proposed method captures 100-1000 times more axons than current standard small field of view microscopy. We showed that the one-to-one correspondence between MRI-based ARI and lsLM-based effective axon radius is superior to the current standard method.

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