By Topic

A Markov random field approach to microarray image gridding

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
G. Antoniol ; Res. Center on Software Technol., Sannio Univ., Benevento, Italy ; M. Ceccarelli

This 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 is 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.

Published in:

Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on  (Volume:3 )

Date of Conference:

23-26 Aug. 2004