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Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging DOI:10.1109/ISBI.2010.5490286

RESOLVING CLUSTERED WORMS VIA PROBABILISTIC SHAPE MODELS.

Publication TypeJournal Article
Year of Publication2010
AuthorsWählby, C, Riklin-Raviv, T, Ljosa, V, Conery, AL, Golland, P, Ausubel, FM, Carpenter, AE
JournalProceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging
Volume2010
Issue14-17 April 2010
Pages552-555
Date Published2010/06/21
ISSN1945-7928
Abstract

The roundworm Caenorhabditis elegans is an effective model system for biological processes such as immunity, behavior, and metabolism. Robotic sample preparation together with automated microscopy and image analysis has recently enabled high-throughput screening experiments using C. elegans. So far, such experiments have been limited to per-image measurements due to the tendency of the worms to cluster, which prevents extracting features from individual animals.We present a novel approach for the extraction of individual C. elegans from clusters of worms in high-throughput microscopy images. The key ideas are the construction of a low-dimensional shape-descriptor space and the definition of a probability measure on it. Promising segmentation results are shown.

DOI10.1109/ISBI.2010.5490286
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/21383863?dopt=Abstract