Segmentation using a region-growing thresholding

Matei Mancas; Bernard Gosselin; Benoit Macq

doi:10.1117/12.587995

1 March 2005 Segmentation using a region-growing thresholding

Matei Mancas, Bernard Gosselin, Benoit Macq

Proceedings Volume 5672, Image Processing: Algorithms and Systems IV; (2005) https://doi.org/10.1117/12.587995
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

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.

Citation Download Citation

Matei Mancas, Bernard Gosselin, and Benoit Macq "Segmentation using a region-growing thresholding", Proc. SPIE 5672, Image Processing: Algorithms and Systems IV, (1 March 2005); https://doi.org/10.1117/12.587995

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