Automatic Robust Neurite Detection and Morphological Analysis of Neuronal Cell Cultures in High-content Screening

Cell-based high content screening (HCS) is becoming an important and increasingly favored approach in therapeutic drug discovery and functional genomics. In HCS, changes in cellular morphology and biomarker distributions provide an information-rich profile of cellular responses to experimental treat...

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Bibliographic Details
Main Authors: Wu, Chaohong (Author), Schulte, Joost (Contributor), Sepp, Katharine J. (Contributor), Littleton, J. Troy (Contributor), Hong, Pengyu (Author)
Other Authors: Massachusetts Institute of Technology. Department of Biology (Contributor), Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences (Contributor), Picower Institute for Learning and Memory (Contributor)
Format: Article
Language:English
Published: Springer-Verlag, 2012-10-18T18:03:46Z.
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LEADER 02543 am a22002773u 4500
001 74092
042 |a dc 
100 1 0 |a Wu, Chaohong  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Biology  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences  |e contributor 
100 1 0 |a Picower Institute for Learning and Memory  |e contributor 
100 1 0 |a Schulte, Joost  |e contributor 
100 1 0 |a Sepp, Katharine J.  |e contributor 
100 1 0 |a Littleton, J. Troy  |e contributor 
700 1 0 |a Schulte, Joost  |e author 
700 1 0 |a Sepp, Katharine J.  |e author 
700 1 0 |a Littleton, J. Troy  |e author 
700 1 0 |a Hong, Pengyu  |e author 
245 0 0 |a Automatic Robust Neurite Detection and Morphological Analysis of Neuronal Cell Cultures in High-content Screening 
260 |b Springer-Verlag,   |c 2012-10-18T18:03:46Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/74092 
520 |a Cell-based high content screening (HCS) is becoming an important and increasingly favored approach in therapeutic drug discovery and functional genomics. In HCS, changes in cellular morphology and biomarker distributions provide an information-rich profile of cellular responses to experimental treatments such as small molecules or gene knockdown probes. One obstacle that currently exists with such cell-based assays is the availability of image processing algorithms that are capable of reliably and automatically analyzing large HCS image sets. HCS images of primary neuronal cell cultures are particularly challenging to analyze due to complex cellular morphology. Here we present a robust method for quantifying and statistically analyzing the morphology of neuronal cells in HCS images. The major advantages of our method over existing software lie in its capability to correct non-uniform illumination using the contrast-limited adaptive histogram equalization method; segment neuromeres using Gabor-wavelet texture analysis; and detect faint neurites by a novel phase-based neurite extraction algorithm that is invariant to changes in illumination and contrast and can accurately localize neurites. Our method was successfully applied to analyze a large HCS image set generated in a morphology screen for polyglutaminemediated neuronal toxicity using primary neuronal cell cultures derived from embryos of a Drosophila Huntington's Disease (HD) model. 
520 |a National Institutes of Health (U.S.) (Grant) 
546 |a en_US 
655 7 |a Article 
773 |t Neuroinformatics