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
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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
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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:
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ImageJ:
Code is developed and tested using ImageJ 1.51n

SEEK ID: https://funginet.hki-jena.de/models/23?version=1

1 item is associated with this Model:
  • ACAQ3.zip (Zip file - 16.6 KB)

Organism: Aspergillus fumigatus

Model type: Not specified

Model format: Not specified

Execution or visualisation environment: Not specified

Model image: No image specified

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Created: 16th Feb 2021 at 15:44

Last updated: 16th Feb 2021 at 15:44

Last used: 27th Sep 2021 at 02:26

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