Automatic mining of fruit fly embryo images

Authors:
Jia-Yu Pan;André G. R. Balan;Eric P. Xing;Agma Juci Machado Traina;Christos Faloutsos
Affiliations:
Carnegie Mellon University, Pittsburgh, PA;Universidade de Sao Paulo, Sao Paulo, Brazil;Carnegie Mellon University, Pittsburgh, PA;Universidade de Sao Paulo, Sao Paulo, Brazil;Carnegie Mellon University, Pittsburgh, PA
Venue:
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Year:
2006

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Abstract

We present FEMine, an automatic system for image-based gene expression analysis. We perform experiments on the largest publicly available collection of Drosophila ISH (in situ hybridization) images, showing that our FEMine system achieves excellent performance in classification, clustering, and content-based image retrieval. The major innovation of FEMine is the use of automatically discovered latent spatial "themes" of gene expressions, LGEs, in the whole-embryo context, as opposed to patterns in nearly disjoint portions of an embryo proposed in previous methods.