Code Monkey home page Code Monkey logo

auto-basket-detector-2d's Introduction

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

auto-basket-detector-2d's People

Contributors

rsenft1 avatar

Watchers

 avatar

auto-basket-detector-2d's Issues

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.