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ImageJ macro scripts for analyzing fluorescent microscopy images: segmenting cells, divide into quadrants, and quantify innervation

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rsenft1/auto-basket-detector-2D

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auto-basket-detector-2D

ImageJ macro scripts for analyzing fluorescent microscopy images: segmenting cells, divide into quadrants, and quantify innervation

What is this repo for?

  • This repo contains a number of scripts used in my paper for quantifying the pericellular basket-type innervation of fluorescently-labeled target cell soma
  • These scripts work on 2D multichannel fluorescent images. They require a cell soma/cell marker channel (you could also use DAPI) and a fluorescent marker of innervation
    • Theoretically it could be brightfield, but it was made with fluorescence in mind.

Macros/Code in this repo

All are .ijm files written in the ImageJ macro programming language. They can be dragged and dropped into Fiji or installed using the Plugins > Macros > Install... menu.

Manual_cell_segmentation.ijm

  • Performs user-assisted segmentation of cells using a magic wand tool

Automatic_cell_segmentation.ijm

  • Performs automatic segmentation of cells, specifically made with tiled images with uneven illumination in mind

ROI_manual_remover.ijm

  • Opens images and their associated ROIs from automatic or manual methods and allows the user to remove (or add, technically) ROIs
  • Useful with the automatic method to correct for any inaccurate segmentation

Quad_basket_quant.ijm

  • Divides cell ROIs generated from previous two macros into quadrants
  • Removes the center (to prevent a single bouton from being counted in all quadrants)
  • Segments the innervation/fiber channel
  • Quantifies the fiber area in each quadrant per cell

Region_labeler.ijm

  • Creates user-defined region ROIs for subregions within an image (e.g. cortical layer, hippocampal subfields)

Region_analyzer.ijm

  • Will sort cell ROIs from a previous manual or automatic segmentation method into the region ROIs made with Region_labeler.ijm

How to cite this repo:

If you want to use these scripts in your own research, please do! If you publish, please cite the original publication: Senft et al., 2020 (in press, more details added soon)

If you experience any issues... Please feel free to raise it to me using the Issues section

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