/ImaCytE

ImaCytE is an interactive tool for data-driven exploration of Imaging Mass Cytometry data as presented in the paper "ImaCytE: Visual Exploration of Cellular Micro-environments for Imaging Mass Cytometry Data".

Primary LanguageMATLABApache License 2.0Apache-2.0

ImaCytE

DOI

ImaCytE is a tool developed for the interactive and data-driven exploration of Imaging Mass Cytometry data as presented in the paper "ImaCytE: Visual Exploration of Cellular Micro-environments for Imaging Mass Cytometry Data". It is focused on the identification of the cell phenotypes that exist in the samples and the interactive exploration of their microenvironment.

Cite

If you use ImaCytE within the scope of a scientific article you must cite the original publication:

Somarakis A., van Unen V., Koning F., Lelieveldt B., and Höllt T., ImaCytE: Visual Exploration of Cellular Microenvironments for Imaging Mass Cytometry Data, IEEE Transactions on Visualization and Computer Graphics, pp. 1-1, 2019. DOI: 10.1109/TVCG.2019.2931299

Getting started

In case you have a Matlab 2016b or newer you can run ImaCytE from source code.

If you have an older version or you don't have a Matlab installed in your PC you can download and install the executable from the release page .

Using ImaCytE from source code

  • Please download the full repisotory and add it to your current direcotry.

  • Run ImaCytE.m to start histoCAT from source

Loading data for analysis

  • Select the Option menu

  • Click on Load Data

  • Here, provide a folder. In this folder should be one subfolder for each sample you want to load. In each subfolder you must contain a mutli-".tiff" file with all markers as exported from MCD viewer and a "*_mask.tiff" file which is used as the cell mask.

Detailed Tutorial

ImaCytE tutorial, kindly written by ImaCytE user,
Juan Manuel Ojeda García, Flow Cytometry Core Facility, Newcastle University

Video

video

Video describing main functionalities of ImaCytE through the case study described in the paper.

Video presenting our paper in PacificVis 2020.

Contact

Antonios Somarakis a.somarakis@lumc.nl