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Adaptive techniques for microarray image analysis with related quality assessment

[+] Author Affiliations
Sebastiano Battiato

University of Catania, Image Processing Laboratory, Catania, Italy

Gianpiero Di Blasi

University of Catania, Image Processing Laboratory, Catania, Italy

Giovanni Maria Farinella

University of Catania, Image Processing Laboratory, Catania, Italy

Giovanni Gallo

University of Catania, Image Processing Laboratory, Catania, Italy

Giuseppe Claudio Guarnera

University of Catania, Image Processing Laboratory, Catania, Italy

J. Electron. Imaging. 16(4), 043013 (December 17, 2007). doi:10.1117/1.2816445
History: Received April 05, 2006; Revised June 07, 2007; Accepted June 23, 2007; Published December 17, 2007
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We propose novel techniques for microarray image analysis. In particular, we describe an overall pipeline able to solve the most common problems of microarray image analysis. We propose the microarray image rotation algorithm (MIRA) and the statistical gridding pipeline (SGRIP) as two advanced modules devoted to restoring the original microarray grid orientation and to detecting, the correct geometrical information about each spot of input microarray, respectively. Both solutions work by making use of statistical observations, obtaining adaptive and reliable information about each spot property. They improve the performance of the microarray image segmentation pipeline (MISP) we recently developed. MIRA, MISP, and SGRIP modules have been developed as plug-ins for an advanced framework for microarray image analysis. A new quality measure able to effectively evaluate the adaptive segmentation with respect to the fixed (e.g., nonadaptive) circle segmentation of each spot is proposed. Experiments confirm the effectiveness of the proposed techniques in terms of visual and numerical data.

© 2007 SPIE and IS&T

Citation

Sebastiano Battiato ; Gianpiero Di Blasi ; Giovanni Maria Farinella ; Giovanni Gallo and Giuseppe Claudio Guarnera
"Adaptive techniques for microarray image analysis with related quality assessment", J. Electron. Imaging. 16(4), 043013 (December 17, 2007). ; http://dx.doi.org/10.1117/1.2816445


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