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Proceedings Paper

3D watershed-based segmentation of internal structures within MR brain images
Author(s): Gloria Bueno; Olivier Musse; Fabrice Heitz; Jean-Paul Armspach
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Paper Abstract

In this paper an image-based method founded on mathematical morphology is presented in order to facilitate the segmentation of cerebral structures on 3D magnetic resonance images (MRIs). The segmentation is described as an immersion simulation, applied to the modified gradient image, modeled by a generated 3D region adjacency graph (RAG). The segmentation relies on two main processes: homotopy modification and contour decision. The first one is achieved by a marker extraction stage where homogeneous 3D regions are identified in order to attribute an influence zone only to relevant minima of the image. This stage uses contrasted regions from morphological reconstruction and labeled flat regions constrained by the RAG. The goal of the decision stage is to precisely locate the contours of regions detected by the marker extraction. This decision is performed by a 3D extension of the watershed transform. Upon completion of the segmentation, the outcome of the preceding process is presented to the user for manual selection of the structures of interest (SOI). Results of this approach are described and illustrated with examples of segmented 3D MRIs of the human head.

Paper Details

Date Published: 6 June 2000
PDF: 10 pages
Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387690
Show Author Affiliations
Gloria Bueno, Univ. Louis Pasteur (France)
Olivier Musse, Univ. Louis Pasteur (France)
Fabrice Heitz, Univ. Louis Pasteur (France)
Jean-Paul Armspach, Univ. Louis Pasteur (France)


Published in SPIE Proceedings Vol. 3979:
Medical Imaging 2000: Image Processing
Kenneth M. Hanson, Editor(s)

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