UCL Centre for Medical Image Computing


Colin Reveley, Sussex University

29 November 2017, 1:00 pm–2:00 pm

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UCL Bloomsbury - ROberts 106 Roberts building

I'm giving two short talks. The talks are both about my work with diffusion MRI scans of ex-vivo primate brains in a high field scanner. In this work we explore the relationship of neuroanatomy to diffusion imaging. Ex-vivo brains offer the capability to scan for extended periods, yielding very high SNR and spatial resolution as high as 100um isotropic. This allows us to look at what dMRI can do in principle rather than limited by clinical constraints. Ex-vivo brains also afford the opportunity to look at the scanned brain under a microscope. Using both methods together can elucidate the relationship of dMRI methods to the structure of the brain, and this has wide ramifications for in-vivo imaging studies in neuroscience, psychology and medicine.

Can We Use Diffusion MRI to Infer Cortical Connectivity?   

In this talk we examine the scope and limits of diffusion tractography for estimating point to point connectivity between brain regions. We look at the factors which determine the behavior of tractography. We find that one of the most important factors is the existence of fiber systems lying underneath the gray matter that have been previously overlooked. This is a potted version of my paper in PNAS in 2015 (http://www.pnas.org/content/112/21/E2820.abstract)

dMRI Correlates of Gray Matter Structure : Pilot Work

Historically, it has been thought that diffusion in gray matter is isotropic. More recently, evidence of changes in anisotropy in the cortex from the white matter boundary to the pial surface has accumulated. This talk shows pilot work in which we demonstrate that diffusion tensors in gray matter show rich variety that can be linked to subtle anatomical features. It seems likely that diffusion imaging is capable of identifying anatomical regions (like motor or sensory) in the cortex, or detecting markers for changes in tissue structure caused by diseases.

Short bio

I've studied a range of topics in Computer Science and Neuroscience. I would presently describe myself as a computational neuroanatomist, but my focus is on anatomy rather than the development of novel computational methods. I am associate faculty in the department of informatics at Sussex University and guest researcher at the Neurophysiology Imaging core facility at the National Institutes of Health in Bethesda, Maryland USA.