Semi-automated atlas-based analysis of brain histological sections

Charles D. Kopec, Amanda C. Bowers, Shraddha Pai, Carlos D. Brody

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)12-19
Number of pages8
JournalJournal of Neuroscience Methods
Issue number1
StatePublished - Mar 15 2011

All Science Journal Classification (ASJC) codes

  • General Neuroscience


  • Analysis
  • Arc
  • Atlas
  • Cell counting
  • Histology
  • IEG
  • Mapping
  • Software


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