The analysis and visualisation of Diffusion Tensor Images (DTI) is still a challenge since it is multi-valued and exploratory in na- ture: tensors, fiber tracts, bundles. This quickly leads to clutter problems in visualisation but also in analysis. In this paper, a new framework for the multi-resolution analysis of DTI is proposed. Based on fast and greedy watersheds operating on a multi-scale representation of a DTI image, a hierarchical depiction of a DTI image is determined conveying a global-to-local view of the fibrous structure of the analysed tissue. The multi-resolution watershed transform provides a coarse to fine partitioning of the data based on the (in)homogeneity of the gradient field. With a transversal cross scale linking of the basins (regions), a hierarchical representation is established. This framework besides providing a novel hierarchical way to analyse DTI data, allows a simple and interactive segmentation tool where dif- ferent bundles can be segmented at different resolutions. We present preliminary experimental results supporting the validity of the proposed method.
|Title of host publication||MICCAI Workshop on Diffusion Modelling|
|Place of Publication||United Kingdom, Longon|
|Publication status||Published - 2009|
Rodrigues, P. R., Jalba, A. C., Fillard, P., Vilanova, A., & Haar Romenij, ter, B. M. (2009). A multi-resolution watershed-based approach for the segmentation of diffusion tensor images. In MICCAI Workshop on Diffusion Modelling (pp. 161-172). United Kingdom, Longon.