DTI Connectivity by Segmentation

Abstract. This paper proposes a new method to compute connectivity information from diffusion weighted images. It is inspired by graphbased 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.

• Type: Journal
• Year: 2010
• Where: MIAR
• Authors: Marc Niethammer, Alexis Boucharin, Christopher Zach, Yundi Shi, Eric Maltbie, Mar Sanchez, Martin Styner
• Keywords: Diffusion Weighted Images, Global Connectivity Measure, Maximum Diffusive flow, Medical Imaging, MIAR 2010