A Markov random field approach to microarray image gridding

Giuliano Antoniol, Michele Ceccarelli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

Abstract

The paper reports a novel approach for the problem of automatic gridding in Microarray images. The solution is modeled as a Bayesian Random Field with a Gibbs prior possibly containing first order cliques (1-clique). On the contrary of previously published contributions, this paper does not assume second order cliques, instead it relies on a two step procedure to locate microarray spots. First a set of guide spots are used to interpolate a reference grid. The final grid is then produced by an a-posteriori maximization which takes into account the reference rectangular grid and local deformations. The algorithm is completely automatic and no human intervention is required, the only critical parameter being the range of the radius of the guide spots.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages550-553
Number of pages4
DOIs
Publication statusPublished - 20 Dec 2004
Externally publishedYes
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: 23 Aug 200426 Aug 2004

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume3
ISSN (Print)1051-4651

Other

OtherProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
CountryUnited Kingdom
CityCambridge
Period23/8/0426/8/04

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Antoniol, G., & Ceccarelli, M. (2004). A Markov random field approach to microarray image gridding. In J. Kittler, M. Petrou, & M. Nixon (Eds.), Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 (pp. 550-553). (Proceedings - International Conference on Pattern Recognition; Vol. 3). https://doi.org/10.1109/ICPR.2004.1334588