{"id":28740127,"url":"https://github.com/rsenft1/auto-basket-detector-2d","last_synced_at":"2026-01-31T22:04:04.238Z","repository":{"id":121657743,"uuid":"325715482","full_name":"rsenft1/auto-basket-detector-2D","owner":"rsenft1","description":"ImageJ macro scripts for analyzing fluorescent microscopy images: segmenting cells, divide into quadrants, and quantify innervation","archived":false,"fork":false,"pushed_at":"2020-12-31T05:22:48.000Z","size":19,"stargazers_count":0,"open_issues_count":1,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2023-12-16T16:11:06.322Z","etag":null,"topics":["ijm","image-classification","image-processing","imagej-macro-scripts","microscopy","microscopy-images","publication-code","region-rois","rois","science-research","segmenting-cells"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rsenft1.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2020-12-31T04:43:25.000Z","updated_at":"2021-02-23T16:30:32.000Z","dependencies_parsed_at":null,"dependency_job_id":"d110cc48-1443-44a8-9210-ff43dcd3099c","html_url":"https://github.com/rsenft1/auto-basket-detector-2D","commit_stats":{"total_commits":5,"total_committers":1,"mean_commits":5.0,"dds":0.0,"last_synced_commit":"5916a987d44821d9c7037bb03c789f3ac85fcd55"},"previous_names":[],"tags_count":0,"template":null,"template_full_name":null,"purl":"pkg:github/rsenft1/auto-basket-detector-2D","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rsenft1%2Fauto-basket-detector-2D","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rsenft1%2Fauto-basket-detector-2D/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rsenft1%2Fauto-basket-detector-2D/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rsenft1%2Fauto-basket-detector-2D/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rsenft1","download_url":"https://codeload.github.com/rsenft1/auto-basket-detector-2D/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rsenft1%2Fauto-basket-detector-2D/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260115295,"owners_count":22961027,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ijm","image-classification","image-processing","imagej-macro-scripts","microscopy","microscopy-images","publication-code","region-rois","rois","science-research","segmenting-cells"],"created_at":"2025-06-16T06:41:29.215Z","updated_at":"2026-01-31T22:04:04.229Z","avatar_url":"https://github.com/rsenft1.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# auto-basket-detector-2D\nImageJ macro scripts for analyzing fluorescent microscopy images: segmenting cells, divide into quadrants, and quantify innervation\n\n# What is this repo for?\n* This repo contains a number of scripts used in my paper for quantifying the pericellular basket-type innervation of fluorescently-labeled target cell soma\n* 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\n    * Theoretically it could be brightfield, but it was made with fluorescence in mind.\n\n# Macros/Code in this repo\n### All are .ijm files written in the ImageJ macro programming language. They can be dragged and dropped into Fiji or installed using the Plugins \u003e Macros \u003e Install... menu.\n### Manual_cell_segmentation.ijm\n* Performs user-assisted segmentation of cells using a magic wand tool\n### Automatic_cell_segmentation.ijm\n* Performs automatic segmentation of cells, specifically made with tiled images with uneven illumination in mind\n### ROI_manual_remover.ijm\n* Opens images and their associated ROIs from automatic or manual methods and allows the user to remove (or add, technically) ROIs\n* Useful with the automatic method to correct for any inaccurate segmentation\n### Quad_basket_quant.ijm\n* Divides cell ROIs generated from previous two macros into quadrants\n* Removes the center (to prevent a single bouton from being counted in all quadrants)\n* Segments the innervation/fiber channel\n* Quantifies the fiber area in each quadrant per cell\n### Region_labeler.ijm\n* Creates user-defined region ROIs for subregions within an image (e.g. cortical layer, hippocampal subfields)\n### Region_analyzer.ijm\n* Will sort cell ROIs from a previous manual or automatic segmentation method into the region ROIs made with Region_labeler.ijm\n    \n# How to cite this repo:\n### 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)\n\n## If you experience any issues... Please feel free to raise it to me using the Issues section\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frsenft1%2Fauto-basket-detector-2d","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frsenft1%2Fauto-basket-detector-2d","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frsenft1%2Fauto-basket-detector-2d/lists"}