A multi-resolution watershed-based approach for the segmentation of diffusion tensor images

P.R. Rodrigues, A.C. Jalba, P. Fillard, A. Vilanova, B.M. Haar Romenij, ter

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Abstract

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.
Original languageEnglish
Title of host publicationMICCAI Workshop on Diffusion Modelling
Place of PublicationUnited Kingdom, Longon
Pages161-172
Publication statusPublished - 2009

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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.