Semi-automated atlas-based analysis of brain histological sections

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

URL: http://www.ncbi.nlm.nih.gov/pubmed/21194546
DOI: 10.1016/j.jneumeth.2010.12.007

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
Watson School > 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: http://repository.cshl.edu/id/eprint/27185

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