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Abstract #1090

A 3D electron microscopy segmentation pipeline for hyper-realistic diffusion simulations

Michiel Kleinnijenhuis1, Errin Johnson2, Jeroen Mollink1,3, Saad Jbabdi1, and Karla Miller1

1Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom, 2Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom, 3Department of Anatomy, Donders Institute for Brain, Cognition & Behaviour, Radboud University Medical Center, Nijmegen, Netherlands

Simulations of the diffusion signal can shed light on how the MR signal is generated from particular tissue microstructure. In our approach we use microscopy data to generate a realistic ground truth for investigating diffusion properties. We have developed a method to automatically segment large volumes of 3D electron microscopy data into individual axons for diffusion simulations. From these segmentations, we can also derive benchmark tissue microstructure characteristics such as axonal diameter, g-ratio and other compartment properties.

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