Pallast, Niklas, Wieters, Frederique, Fink, Gereon R. ORCID: 0000-0002-8230-1856 and Aswendt, Markus ORCID: 0000-0003-1423-0934 (2019). Atlas-based imaging data analysis tool for quantitative mouse brain histology (AIDAhisto). J. Neurosci. Methods, 326. AMSTERDAM: ELSEVIER. ISSN 1872-678X

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Cell counting in neuroscience is a routine method of utmost importance to support descriptive in vivo findings with quantitative data on the cellular level. Although known to be error- and bias-prone, manual cell counting of histological stained brain slices remains the gold standard in the field. While the manual approach is limited to small regions-of-interest in the brain, automated tools are needed to up-scale translational approaches and generate whole mouse brain counts in an atlas framework. Our goal was to develop an algorithm which requires no pre-training such as machine learning algorithms, only minimal user input, and adjustable variables to obtain reliable cell counting results for stitched mouse brain slices registered to a common atlas such as the Allen Mouse Brain atlas. We adapted filter banks to extract the maxima from round-shaped cell nuclei and various cell structures. In a qualitative as well as quantitative comparison to other tools and two expert raters, AIDAhisto provides accurate and fast results for cell nuclei as well as immunohistochemical stainings of various types of cells in the mouse brain.

Item Type: Journal Article
CreatorsEmailORCIDORCID Put Code
Fink, Gereon
URN: urn:nbn:de:hbz:38-133261
DOI: 10.1016/j.jneumeth.2019.108394
Journal or Publication Title: J. Neurosci. Methods
Volume: 326
Date: 2019
Publisher: ELSEVIER
Place of Publication: AMSTERDAM
ISSN: 1872-678X
Language: English
Faculty: Unspecified
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
CELL DETECTIONMultiple languages
Biochemical Research Methods; NeurosciencesMultiple languages
Refereed: Yes


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