Paulo Rodrigues1, Andrei Jalba2, Pierre Fillard3, Anna Vilanova1, Bart M. ter Haar Romeny1
1Biomedical Image Analysis, Eindhoven University of Technology, Eindhoven, Noord Brabant, Netherlands; 2Department of Computer Science, Eindhoven University of Technology, Eindhoven, Noord Brabant, Netherlands; 3CEA, Paris, France
The investigation of Diffusion Tensor Imaging (DTI) data is of complex and exploratory nature: tensors, fiber tracts, bundles. This quickly leads to clutter problems in visualization as well as in analysis. We propose a new framework for the multi-resolution analysis of DTI. Based on fast and greedy watersheds operating on a multi-scale representation of a DTI image, a hierarchical depiction of such image is determined conveying a global-to-local view of the fibrous structure of the analysed tissue. We present a simple and interactive segmentation tool, where different bundles can be segmented at different resolutions.