ImageJ plugin: Semi-automatic cell counting (with colocalization / categorization). Object based.
new ImageJ plugin: A versatile toolbox for semi-automatic cell-by-cell object-based colocalization analysis Link to paper: https://www.nature.com/articles/s4159... Video explanation (part 1): • ImageJ/FIJI plugin: Semi-automatic cell-by... Video explanation (part 2): • ImageJ plugin: Semi-automatic cell countin... FIJI update site: https://sites.imagej.net/ObjectColoca... Features: ImageJ plugin 1: Colocalization Image Creator: *Pre-process multichannel Z-stack (or 2D) microscopy images into a visual format for faster, simpler, and more accurate colocalization analysis. *Designed to help avoid common colocalization analysis artifacts and errors. *Can transform Z-stack 3D data into a specialized 2D Z-projection where Z-projection colocalization artifacts are removed/reduced. This simplifies the analysis of 3D colocalization data. ImageJ plugin 2: Colocalization Object Counter: *Quantity (count) cells/objects in a semi-automatic manner. *Assign, classify and keep track of multichannel signal presence/absence (colocalization analysis) for each cell/object. *Tools for subsequent 3D modeling/representation of data: draw tissue contours and indicate image-series global XY-origin. *Save data, load data, and export data to Excel. Custom Excel macro-file: *Import data from Colocalization Object Counter *Analyze and edit data from image series. *Export combined image series data to Matlab for 3D modeling Custom Matlab script: *3D visualize cells according to colocalization data *3D visualize tissue contours I hope the community will appreciate our work. The ImageJ plugin 1 might be somewhat hard to understand how to use effectively (though we hope not), but ImageJ plugin 2 should be very simple and useful to the broader community. I found a good cell counting tool for ImageJ lacking, so maybe this plugin (and the other) can be included as a standard part of FIJI. Sincerely, Anders Lunde, PhD University of Oslo, Norway

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