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Proceedings Paper

Segmentation using a region-growing thresholding
Author(s): Matei Mancas; Bernard Gosselin; Benoit Macq
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Paper Abstract

Our research deals with a semi-automatic region-growing segmentation technique. This method only needs one seed inside the region of interest (ROI). We applied it for spinal cord segmentation but it also shows results for parotid glands or even tumors. Moreover, it seems to be a general segmentation method as it could be applied in other computer vision domains then medical imaging. We use both the thresholding simplicity and the spatial information. The gray-scale and spatial distances from the seed to all the other pixels are computed. By normalizing and subtracting to 1 we obtain the probability for a pixel to belong to the same region as the seed. We will explain the algorithm and show some preliminary results which are encouraging. Our method has low computational cost and very encouraging results in 2D. Future work will consist in a C implementation and a 3D generalisation.

Paper Details

Date Published: 1 March 2005
PDF: 11 pages
Proc. SPIE 5672, Image Processing: Algorithms and Systems IV, (1 March 2005); doi: 10.1117/12.587995
Show Author Affiliations
Matei Mancas, Faculte Polytechnique de Mons (Belgium)
Bernard Gosselin, Faculte Polytechnique de Mons (Belgium)
Benoit Macq, Univ. Catholique de Louvain (Belgium)

Published in SPIE Proceedings Vol. 5672:
Image Processing: Algorithms and Systems IV
Edward R. Dougherty; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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