DTI connectivity by segmentation

Authors:
Marc Niethammer;Alexis Boucharin;Christopher Zach;Yundi Shi;Eric Maltbie;Mar Sanchez;Martin Styner
Affiliations:
University of North Carolina at Chapel Hill;University of North Carolina at Chapel Hill;Swiss Federal Institute of Technology, Zurich;University of North Carolina at Chapel Hill;University of North Carolina at Chapel Hill;Emory University;University of North Carolina at Chapel Hill
Venue:
MIAR'10 Proceedings of the 5th international conference on Medical imaging and augmented reality
Year:
2010

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Abstract

This paper proposes a new method to compute connectivity information from diffusion weighted images. It is inspired by graph-based approaches to connectivity definition, but formulates the estimation problem in the continuum. In particular, it defines the connectivity through the minimum cut in tensor-weighted space. It is therefore closely related to prior work on segmentation using continuous versions of graph cuts. A numerical solution based on a staggered grid is proposed which allows for the computation of flux directly through diffusion tensors. The resulting global connectivity measure is the maximum diffusive flow supported between two regions of interest.