Probability and statistics for the engineering, computing, and physical sciences
Probability and statistics for the engineering, computing, and physical sciences
On Optimal Pairwise Linear Classifiers for Normal Distributions: The Two-Dimensional Case
IEEE Transactions on Pattern Analysis and Machine Intelligence
Microarray image processing based on clustering and morphological analysis
APBC '03 Proceedings of the First Asia-Pacific bioinformatics conference on Bioinformatics 2003 - Volume 19
A Pattern Classification Approach to DNA Microarray Image Segmentation
PRIB '09 Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics
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One of the key issues in microarray analysis is to extract quantitative information from the spots, which represents gene expression levels in the experiments. The process of identifying the spots and separating the foreground from the background is known as microarray image segmentation. In this paper, we propose a new approach to microarray image segmentation, which we called the adaptive ellipse method, and shows various advantages when compared to the adaptive circle method. Our experiments on real-life microarray images show that adaptive ellipse is capable of extracting information from the images, which is ignored by the traditional adaptive circle method, and hence showing more flexibility.