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Abstract #0679

Microstructure Tracking (MicroTrack): An Algorithm for Estimating a Multiscale Hierarchical White Matter Model from Diffusion-Weighted MRI

Anthony Jacob Sherbondy1, Tim B. Dyrby2, Matthew C. Rowe3, Maurice Ptito2,4, Brian A. Wandell1, Daniel C. Alexander3

1Psychology Department, Stanford University, Stanford, CA, USA; 2Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; 3Centre for Medical Image Computing, University College London, London, United Kingdom; 4School of Optometry, University of Montreal, Montreal, Canada

MicroTrack combines whole-brain global tractography and local tissue microstructure estimation. The algorithm simultaneously estimates macrostructure (tract cross-section and connectivity) and microstructure (average axon radii and axon volume fraction) parameters for a white matter connectome using a mutliscale forward model. To date, tractography algorithms and microstructure parameter estimation operate entirely independently. However, connectivity and microstructure estimates have great potential to inform one another. We use MicroTrack to demonstrate this hypothesis for the first time on synthetic data and post-mortem monkey-brain data.