AIDAhisto
Posted on 18 October 2019
Atlas-based imaging data analysis tool for quantitative mouse brain histology (AIDAhisto)
AIDAhisto features a simple protocol for landmark-correspondence registration using ImageJ/Fiji for whole-brain slice microscopy with the Allen Mouse Bran Atlas, ARA, (Lein et al., 2006, Oh et al., 2014) and a two-step cell detection algorithm using the cell nuclei segmentation as a seed for cell counting. For the cell detection, we advanced previous implementations of kernel-based cell nuclei detection adding the Schmid Filter Bank and the Leung–Malik Filter Bank. Both filter banks are rotationally invariant and enable the identification of more complex non-circular geometries. AIDAhisto was developed as an open-source script for Python and Matlab and tested against other tools for the detection of cell nuclei and immunostainings of astrocytes and immune cells.
Pallast et al. Journal of Neuroscience Methods 2019: https://doi.org/10.1016/j.jneumeth.2019.108394
Type of tool: Image analysis software
Contact email: markus.aswendt@uk-koeln.de
Resource Created By: Niklas Pallast and Markus Aswendt
You may also be interested in
SynapseNet: Deep Learning for Automatic Synapse Reconstruction
automatic synapse reconstruction and analysis in EM
Sarah Muth, Frederieke Moschref, Luca Freckmann, Sophia Mutschall, Ines Hojas-Garcia-Plaza, Julius N. Bahr, Arsen Petrovic, Thanh Thao Do, Valentin Schwarze, Anwai Archit, Kirsten Weyand, Susann Michanski, Lydia Maus, Cordelia Imig, Nils Brose, Carolin Wichmann, Ruben Fernandez-Busnadiego, Tobias Moser, Silvio O. Rizzoli, Benjamin H. Cooper, Constantin Pape
Icy
Platform for bioimage informatics
Quantitative Image Analysis Unit, Institut Pasteur
LEMOLish
A lego approach to SPIM/LSFM
Colombelli, Tosi & Andilla