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 Awesome Biological Image Analysis !Awesome (https://awesome.re/badge.svg) (https://awesome.re)
 Awesome Biological Image Analysis !Awesome (https://awesome.re/badge.svg) (https://awesome.re)
 
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- DeepSlide (https://github.com/BMIRDS/deepslide) - A sliding window framework for classification of high resolution microscopy images.
- EBImage (https://github.com/aoles/EBImage) - Image processing toolbox for R.
- GPim (https://github.com/ziatdinovmax/GPim) - Gaussian processes and Bayesian optimization for images and hyperspectral data.
- MAPS (https://github.com/mahmoodlab/MAPS) - MAPS (Machine learning for Analysis of Proteomics in Spatial biology) is a machine learning approach facilitating rapid and precise cell type identification with 
human-level accuracy from spatial proteomics data.
- MicroSAM (https://github.com/computational-cell-analytics/micro-sam) - Tools for segmentation and tracking in microscopy build on top of SegmentAnything. Segment and track objects in microscopy images 
interactively.
- MAPS (https://github.com/mahmoodlab/MAPS) - MAPS (Machine learning for Analysis of Proteomics in Spatial biology) is a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from 
spatial proteomics data.
- MicroSAM (https://github.com/computational-cell-analytics/micro-sam) - Tools for segmentation and tracking in microscopy build on top of SegmentAnything. Segment and track objects in microscopy images interactively.
- MorpholibJ (https://github.com/ijpb/MorphoLibJ) - Collection of mathematical morphology methods and plugins for ImageJ.
- PartSeg (https://github.com/4DNucleome/PartSeg) - A GUI and a library for segmentation algorithms.
- PyImSegm (https://github.com/Borda/pyImSegm) - Image segmentation - general superpixel segmentation and center detection and region growing.
- Squidpy (https://github.com/scverse/squidpy) - Python framework that brings together tools from omics and image analysis to enable scalable description of spatial molecular data, such as transcriptome or 
multivariate proteins.
- Squidpy (https://github.com/scverse/squidpy) - Python framework that brings together tools from omics and image analysis to enable scalable description of spatial molecular data, such as transcriptome or multivariate proteins.
- StarDist (https://github.com/stardist/stardist) - Object detection with Star-convex shapes.
- Suite2p (https://github.com/MouseLand/suite2p) - Pipeline for processing two-photon calcium imaging data.
- SyMBac (https://github.com/georgeoshardo/SyMBac) - Accurate segmentation of bacterial microscope images using synthetically generated image data.
- Trainable Weka Segmentation (https://github.com/fiji/Trainable_Segmentation) - Fiji plugin and library that combines a collection of machine learning algorithms with a set of selected image features to produce
pixel-based segmentations.
- Trainable Weka Segmentation (https://github.com/fiji/Trainable_Segmentation) - Fiji plugin and library that combines a collection of machine learning algorithms with a set of selected image features to produce pixel-based 
segmentations.
Ecology
- PAT-GEOM (http://ianzwchan.com/my-research/pat-geom/) - A software package for the analysis of animal colour pattern.
@@ -97,8 +95,8 @@
- SNT (https://github.com/morphonets/SNT/) - ImageJ framework for semi-automated tracing and analysis of neurons.
- TrailMap (https://github.com/AlbertPun/TRAILMAP/) - Software package to extract axonal data from cleared brains.
- Wholebrain (https://github.com/tractatus/wholebrain) - Automated cell detection and registration of whole-brain images with plot of cell counts per region and Hemishpere.
- ZVQ - Zebrafish Vascular Quantification (https://github.com/ElisabethKugler/ZFVascularQuantification) - Image analysis pipeline to perform 3D quantification of the total or regional zebrafish brain vasculature
using the image analysis software Fiji.
- ZVQ - Zebrafish Vascular Quantification (https://github.com/ElisabethKugler/ZFVascularQuantification) - Image analysis pipeline to perform 3D quantification of the total or regional zebrafish brain vasculature using the image analysis
software Fiji.
@@ -148,11 +146,11 @@
- CellMigration (https://github.com/quantixed/CellMigration) - Analysis of 2D cell migration in Igor.
- TrackMate (https://github.com/fiji/TrackMate) - User-friendly interface that allows for performing tracking, data visualization, editing results and track analysis in a convenient way.
- TrackMateR (https://github.com/quantixed/TrackMateR) - R package to analyze cell migration and particle tracking experiments using outputs from TrackMate.
- TracX (https://gitlab.com/csb.ethz/tracx) - MATLAB generic toolbox for cell tracking from various microscopy image modalities such as Bright-field (BF), phase contrast (PhC) or fluorescence (FL) with an 
automated track quality assessment in
- TracX (https://gitlab.com/csb.ethz/tracx) - MATLAB generic toolbox for cell tracking from various microscopy image modalities such as Bright-field (BF), phase contrast (PhC) or fluorescence (FL) with an automated track quality 
assessment in
absence of a ground truth.
- TraJClassifier (https://imagej.net/plugins/trajclassifier) - Fiji plugin that loads trajectories from TrackMate, characterizes them using TraJ and classifiies them into normal diffusion, subdiffusion, confined
diffusion and directed/active motion by a random forest approach (through Renjin).
- TraJClassifier (https://imagej.net/plugins/trajclassifier) - Fiji plugin that loads trajectories from TrackMate, characterizes them using TraJ and classifiies them into normal diffusion, subdiffusion, confined diffusion and 
directed/active motion by a random forest approach (through Renjin).
- QuimP (https://github.com/CellDynamics/QuimP) - Software for tracking cellular shape changes and dynamic distributions of fluorescent reporters at the cell membrane.
- Usiigaci (https://github.com/oist/usiigaci) - Stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning.
@@ -184,13 +182,12 @@
Other
- AICSImageIO (https://github.com/AllenCellModeling/aicsimageio) - Image reading, metadata conversion, and image writing for nicroscopy images in Python.
- Biobeam (https://maweigert.github.io/biobeam) - Open source software package that is designed to provide fast methods for in-silico optical experiments with an emphasize on image formation in biological 
tissues.
- Biobeam (https://maweigert.github.io/biobeam) - Open source software package that is designed to provide fast methods for in-silico optical experiments with an emphasize on image formation in biological tissues.
- BoneJ (https://github.com/bonej-org/BoneJ2) - Collection of Fiji/ImageJ plug-ins for skeletal biology.
- CaPTk (https://github.com/CBICA/CaPTk) - Cancer Imaging Phenomics Toolkit: A software platform to perform image analysis and predictive modeling tasks.
- ColiCoords (https://github.com/Jhsmit/ColiCoords) - Python project for analysis of fluorescence microscopy data from rodlike cells.
- CompactionAnalyzer (https://github.com/davidbhr/CompactionAnalyzer) - Python package to quantify the tissue compaction (as a measure of the contractile strength) generated by cells or multicellular spheroids 
that are embedded in fiber materials.
- CompactionAnalyzer (https://github.com/davidbhr/CompactionAnalyzer) - Python package to quantify the tissue compaction (as a measure of the contractile strength) generated by cells or multicellular spheroids that are embedded in fiber
materials.
- Cytominer-database (https://github.com/cytomining/cytominer-database) - Command-line tools for organizing measurements extracted from images.
- DetecDiv (https://github.com/gcharvin/DetecDiv) - Comprehensive set of tools to analyze time microscopy images using deep learning methods.
- MIA (https://github.com/mianalysis/mia) - Fiji plugin which provides a modular framework for assembling image and object analysis workflows.
@@ -203,8 +200,7 @@
- Pycytominer (https://github.com/cytomining/pycytominer) - Data processing functions for profiling perturbations.
- Pyotf (https://github.com/david-hoffman/pyotf) - A simulation software package for modelling optical transfer functions (OTF)/point spread functions (PSF) of optical microscopes written in Python.
- PyScratch (https://bitbucket.org/vladgaal/pyscratch_public.git/src) - Open source tool that autonomously performs quantitative analysis of in vitro scratch assays.
- Quanfima (https://github.com/rshkarin/quanfima) - Quantitative Analysis of Fibrous Materials: A collection of useful functions for morphological analysis and visualization of 2D/3D data from various areas of 
material science.
- Quanfima (https://github.com/rshkarin/quanfima) - Quantitative Analysis of Fibrous Materials: A collection of useful functions for morphological analysis and visualization of 2D/3D data from various areas of material science.
- SimpleElastix (https://github.com/SuperElastix/SimpleElastix) - Multi-lingual medical image registration library.
- Vaa3D (https://alleninstitute.org/what-we-do/brain-science/research/products-tools/vaa3d/) - Open-source software for 3D/4D/5D image visualization and analysis.
- XitoSBML (https://github.com/spatialsimulator/XitoSBML) - ImageJ plugin which creates a Spatial SBML model from segmented images.
@@ -216,13 +212,11 @@
Publications
- A Hitchhiker's guide through the bio-image analysis software universe (https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.14451) - An article presenting a curated guide and glossary of bio-image 
analysis terms and tools.
- A Hitchhiker's guide through the bio-image analysis software universe (https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.14451) - An article presenting a curated guide and glossary of bio-image analysis terms and tools.
- Biological imaging software tools (https://dx.doi.org/10.1038%2Fnmeth.2084) - The steps of biological image analysis and the appropriate tools for each step.
- Data-analysis strategies for image-based cell profiling (https://doi.org/10.1038/nmeth.4397) - In-detail explanations of image analysis pipelines.
- Large-scale image-based screening and profiling of cellular phenotypes (https://onlinelibrary.wiley.com/doi/10.1002/cyto.a.22909) - A workflow for phenotype extraction from high throughput imaging experiments.
- Workflow and metrics for image quality control in large-scale high-content screens (https://linkinghub.elsevier.com/retrieve/pii/S2472555222075943) - Approaches for quality control in high-content imaging 
screens.
- Workflow and metrics for image quality control in large-scale high-content screens (https://linkinghub.elsevier.com/retrieve/pii/S2472555222075943) - Approaches for quality control in high-content imaging screens.
Footnotes
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