Kopec, C. D., Bowers, A. C., Pai, S. , Brody, C. D. (March 2011) Semi-automated atlas-based analysis of brain histological sections. Journal of Neuroscience Methods, 196 (1). ISSN 0165-0270
Abstract
Quantifying the location and/or number of features in a histological section of the brain currently requires one to first, manually register a corresponding section from a tissue atlas onto the experimental section and second, count the features. No automated method exists for the first process (registering), and most automated methods for the second process (feature counting) operate reliably only in a high signal-to-noise regime. To reduce experimenter bias and inconsistencies and increase the speed of these analyses, we developed Atlas Fitter, a semi-automated, open-source MatLab-based software package that assists in rapidly registering atlas panels onto histological sections. We also developed CellCounter, a novel fully automated cell counting algorithm that is designed to operate on images with non-uniform background intensities and low signal-to-noise ratios. © 2010 Elsevier B.V. All rights reserved.
| Item Type: | Paper |
|---|---|
| Uncontrolled Keywords: | Analysis Arc Atlas Cell counting Histology IEG Mapping Software |
| Subjects: | organs, tissues, organelles, cell types and functions > organs types and functions > brain educational material manuals and technical reports neurobiology organs, tissues, organelles, cell types and functions > organs types and functions organs, tissues, organelles, cell types and functions |
| CSHL Authors: | |
| Communities: | CSHL labs > Zador lab School of Biological Sciences > Publications |
| Depositing User: | Matt Covey |
| Date: | 15 March 2011 |
| Date Deposited: | 05 Feb 2013 21:27 |
| Last Modified: | 22 Sep 2014 20:07 |
| PMCID: | PMC3075115 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/27185 |
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