Paper Info
Title
RESOLVING CLUSTERED WORMS VIA PROBABILISTIC SHAPE MODELS.
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.
Year
DOI
Venue
2010
10.1109/ISBI.2010.5490286
Rotterdam, Netherlands
Keywords
Field
DocType
automated microscopy,robotic sample preparation,biological process,individual animal,image analysis,high-throughput screening experiment,c. elegans,probabilistic shape model,effective model system,high-throughput microscopy image,individual c. elegans,high throughput screening,microscopy,image segmentation,feature extraction,active shape model,biological processes,shape,immune system,bioinformatics,biomedical research,high throughput,probability measure,sample preparation,probability,microorganisms,biochemistry
Computer vision,Active shape model,Pattern recognition,Computer science,Segmentation,Model system,Caenorhabditis elegans,Image segmentation,Feature extraction,Artificial intelligence,Probabilistic logic
Conference
Volume
Issue
ISSN
2010
14-17 April 2010
1945-7928
ISBN
Citations 
PageRank 
978-1-4244-4126-6
9
1.10
References 
Authors
6
7
Name
Order
Citations
PageRank
Carolina Wählby1416.76
Tammy Riklin-Raviv251030.51
Vebjorn Ljosa320812.43
Annie L. Conery491.43
Polina Golland51690114.38
Frederick M. Ausubel691.77
Anne E. Carpenter713712.90