ACAQ3

Version 1

This is the image analysis algorithm used in Cseresnyes, Kraibooj and Figge, Hessian-based quantitative image analysis of host-pathogen confrontation assays Cytometry A. 2018 Mar;93(3):346-356. doi: 10.1002/cyto.a.23201. Code is being maintained at https://github.com/applied-systems-biology/ACAQ3.

Read.me

This package contains code that implements the Hessian-based macrophage segmentation algorithm. In addition, the macro provides segmentation tools for fungal conidia and spores, based on their fluorescence labelling. Full details of the algorithm and the rest of the macro can be found in the paper by Cseresnyes et al. (2017), Hessian-based quantitative image analysis of host-pathogen confrontation assays, Cytometry A, currently under revision . The paper can be found by contacting the corresponding author using the email address thilo.figge@leibniz-hki.de.

With all questions, please contact: thilo.figge@leibniz-hki.de.

If any part of this code is used for academic purposes please cite the paper above.

Contents

ACAQ-v3: The Fiji macro implements a Hessian-based segmentation algorithm to detect macrophages in transmitted light images, as well as the corresponding fungal spores based on their fluorescence labelling. The details are described in Cseresnyes et al., 2017 read.me: What you currently have open. license: Licencing details of this software (BSD License 2.0). Data/: Folder containing some example images and their segmented end-results that is appropriate to test ACAQ-v3 on.

Requirements:

ImageJ: Code is developed and tested using ImageJ 1.51n