In this paper we present the results of a system for processing microarray images which includes the gridding and spot detection steps. The main goal of this work is to develop automatic methods to process microarray images including confidence measures on the results. The gridding step is based on the method proposed in [1] and improves it by the automatic determination of the grid parameters, and a more precise orientation detection. For spot detection the algorithm uses the Number of False Alarms methodology [2] which can be used to finely adjust the spot position and provides a confidence measure on the detection. We test the results obtained by our method with simulated images against existing microarray software. © 2009 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Mastandrea, F., & Pardo, Á. (2009). Processing of microarray images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5856 LNCS, pp. 962–969). https://doi.org/10.1007/978-3-642-10268-4_112
Mendeley helps you to discover research relevant for your work.