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Proceedings Paper

Model-based segmentation for multidimensional biomedical image analysis
Author(s): Raj S. Acharya
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Paper Abstract

One of the initial steps in the analysis of 3-D/4-D images is Segmentation, which entails partitioning the images into relevant subsets such as object and background. In this paper, we present a multidimensional segmentation algorithm to extract object surfaces from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans. The algorithm is formulated in the framework of blackboard model and uses Mathematical Morphology. We propose the Generalized Morphological operators( which are used as Knowledge Sources) for segmentation in multidimensions. Apriori knowledge of the approximate location of the object surface is communicated to the algorithm via the definition of the Search Space. The algorithm uses this definition of the Search Space to obtain the Surface Candidate elements. The search space specification reduces the computational cost and increases the reliability of the detected features.

Paper Details

Date Published: 1 May 1990
PDF: 15 pages
Proc. SPIE 1245, Biomedical Image Processing, (1 May 1990); doi: 10.1117/12.19550
Show Author Affiliations
Raj S. Acharya, SUNY/Buffalo (United States)

Published in SPIE Proceedings Vol. 1245:
Biomedical Image Processing
Alan Conrad Bovik; William E. Higgins, Editor(s)

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