Interactive Segmentation and Visualization of DTI Data Using a Hierarchical Watershed Representation

Magnetic resonance diffusion tensor imaging (DTI) measures diffusion of water molecules and is used to characterize orientation of white matter fibers and connectivity of neurological structures. Segmentation and visualization of DT images is challenging, because of low data quality and complexity o...

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Bibliographic Details
Published in:IEEE transactions on image processing 2015-03, Vol.24 (3), p.1025-1035
Main Authors: Jalba, Andrei C., Westenberg, Michel A., Roerdink, Jos B. T. M.
Format: Article
Language:English
Subjects:
Data visualization
Diffusion tensor imaging
DTI
Image segmentation
Merging
multiple views
Partitioning algorithms
segmentation
Tensile stress
Vectors
waterfall algorithm
watershed
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Summary:Magnetic resonance diffusion tensor imaging (DTI) measures diffusion of water molecules and is used to characterize orientation of white matter fibers and connectivity of neurological structures. Segmentation and visualization of DT images is challenging, because of low data quality and complexity of anatomical structures. In this paper, we propose an interactive segmentation approach, based on a hierarchical representation of the input DT image through a tree structure. The tree is obtained by successively merging watershed regions, based on the morphological waterfall approach, hence the name watershed tree. Region merging is done according to a combined similarity and homogeneity criterion. We introduce filters that work on the proposed tree representation, and that enable region-based attribute filtering of DTI data. Linked views between the visualizations of the simplified DT image and the tree enable a user to visually explore both data and tree at interactive rates. The coupling of filtering, semiautomatic segmentation by labeling nodes in the tree, and various interaction mechanisms support the segmentation task. Our method is robust against noise, which we demonstrate on synthetic and real DTI data.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2015.2390139