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Microarray image segmentation using chan-vese active contour model and level set method

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3 Author(s)
Kaustubha A. Mendhurwar ; Faculty of Engineering and Computer Science, Concordia University, 1455 de Maisonneuve Blvd. West, Montreal, H3G1M8, Quebec, Canada ; Rajasekhar Kakumani ; Vijay Devabhaktuni

Microarray technology is considered to be one of the major breakthroughs in bioinformatics for profiling gene-expressions of thousands of genes, simultaneously. Analysis of a microarray image plays an important role in the accurate depiction of gene-expression. Segmentation, the process of separating the foreground from the background, of a microarray image, is one of the key issues in microarray image analysis. Level sets have tremendous potential in the segmentation of images. In this paper, a new approach for segmentation of the microarray images is proposed. In this work, Chan-Vese approximation of the Mumford-Shah model and the level set method are employed for image segmentation. Illustrative examples of the proposed method are presented highlighting its effectiveness.

Published in:

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Date of Conference:

3-6 Sept. 2009