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Proceedings Paper

GICEB: automatic segmentation algorithm for biomedical images
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Paper Abstract

Automatic segmentation is an essential problem in biomedical imaging. It is still an open problem to automatically segment biomedical images with complex structures and compositions. This paper proposes a novel algorithm called Gradient-Intensity Clusters and Expanding Boundaries (GICEB). The algorithm attempts to solve the problem with considerations of the image properties in intensity, gradient, and spatial coherence in the image space. The solution is achieved through a combination of using a two-dimensional histogram, domain connectivity in the image space, and segment region growing. The algorithm has been tested on some real images and the results have been evaluated.

Paper Details

Date Published: 28 February 2007
PDF: 9 pages
Proc. SPIE 6498, Computational Imaging V, 64981I (28 February 2007); doi: 10.1117/12.716208
Show Author Affiliations
Qiqi Wang, Purdue Univ. (United States)
Navaneetha Vaidhyanathan, Purdue Univ. (United States)
Fijoy Vadakkumpadan, Purdue Univ. (United States)
Yinlong Sun, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 6498:
Computational Imaging V
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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