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    Awesome Biological Image Analysis

    A curated collection of resources and projects focused on Biological Image Analysis.

    Contents

    General image analysis software

    • 3D Slicer - Free, open source and multi-platform software package widely used for medical, biomedical, and related imaging research.
    • BiaPy - Open source ready-to-use all-in-one library that provides deep-learning workflows for a large variety of bioimage analysis tasks.
    • Cell-ACDC - A GUI-based Python framework for segmentation, tracking, cell cycle annotations and quantification of microscopy data.
    • CellProfiler - Open-source software helping biologists turn images into cell measurements.
    • CellProfiler Analyst - Open-source software for exploring and analyzing large, high-dimensional image-derived data.
    • Fiji - A “batteries-included” distribution of ImageJ — a popular, free scientific image processing application.
    • Flika - An interactive image processing program for biologists written in Python.
    • Icy - Open community platform for bioimage informatics, providing software resources to visualize, annotate and quantify bioimaging data.
    • Ilastik - Simple, user-friendly tool for interactive image classification, segmentation and analysis.
    • ImageJ - Public domain software for processing and analyzing scientific images.
    • ImageJ2 - A Rewrite of ImageJ for multidimensional image data, with a focus on scientific imaging.
    • ImagePy - Open source image processing framework written in Python.
    • Napari - Fast, interactive, multi-dimensional image viewer for Python.
    • OpenCV - Open source computer vision and machine learning software library.
    • PYME - Open-source application suite for light microscopy acquisition, data storage, visualization, and analysis.
    • Scikit-image - Collection of algorithms for image processing.

    Image processing and segmentation

    • Ark-Analysis - A pipeline toolbox for analyzing multiplexed imaging data.
    • AtomAI - PyTorch-based package for deep/machine learning analysis of microscopy data.
    • Cellpose - A generalist algorithm for cell and nucleus segmentation.
    • CellSAM - A foundation model for cell segmentation trained on a diverse range of cells and data types.
    • Cellshape - 3D single-cell shape analysis of cancer cells using geometric deep learning.
    • CellVit++ - A framework for lightweight cell segmentation model training and inference.
    • Classpose - A foundation model-driven whole slide image-scale cell phenotyping method with QuPath integration.
    • CLIJ2 - GPU-accelerated image processing library for ImageJ/Fiji, Icy, MATLAB and Java.
    • DeepCell - Deep learning library for single cell analysis.
    • DeepSlide - A sliding window framework for classification of high resolution microscopy images.
    • EBImage - Image processing toolbox for R.
    • FlashDeconv - High-performance spatial transcriptomics deconvolution for cell type mapping using structure-preserving randomized sketching.
    • GPim - Gaussian processes and Bayesian optimization for images and hyperspectral data.
    • HistoPLUS - Pre-trained model for cell nuclei segmentation and classification in histology images.
    • HoVer-Net - A multi-branch network for nuclear instance segmentation and classification with pre-trained weights.
    • 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 - Tools for segmentation and tracking in microscopy build on top of SegmentAnything. Segment and track objects in microscopy images interactively.
    • MorpholibJ - Collection of mathematical morphology methods and plugins for ImageJ.
    • Nellie - Automated organelle segmentation, tracking, and hierarchical feature extraction in 2D/3D live-cell microscopy.
    • PartSeg - A GUI and a library for segmentation algorithms.
    • Proseg : A cell segmentation method for in situ spatial transcriptomics.
    • PyImSegm - Image segmentation - general superpixel segmentation and center detection and region growing.
    • Salem² - Segment Anything in Light and Electron Microscopy via Membrane Guidance.
    • 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.
    • SplineDist - Object detection with spline curves.
    • StarDist - Object detection with Star-convex shapes.
    • Suite2p - Pipeline for processing two-photon calcium imaging data.
    • SyMBac - Accurate segmentation of bacterial microscope images using synthetically generated image data.
    • Trainable Weka 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 - A software package for the analysis of animal colour pattern.
    • ThermImageJ - ImageJ functions and macros for working with thermal image files.

    Neuroscience

    • AxonDeepSeg - Segment axon and myelin from microscopy data using deep learning.
    • BG-atlasAPI - A lightweight Python module to interact with atlases for systems neuroscience.
    • Brainreg - Automated 3D brain registration with support for multiple species and atlases.
    • Brainrender - Python package for the visualization of three dimensional neuro-anatomical data.
    • CaImAn - Computational toolbox for large scale Calcium Imaging Analysis.
    • Cellfinder - Automated 3D cell detection and registration of whole-brain images.
    • CloudVolume - Read and write Neuroglancer datasets programmatically.
    • NeuroAnatomy Toolbox - R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
    • Neuroglancer - WebGL-based viewer for volumetric data.
    • NeuronJ - An ImageJ plugin for neurite tracing and analysis.
    • Panda - Pipeline for Analyzing braiN Diffusion imAges: A MATLAB toolbox for pipeline processing of diffusion MRI images.
    • PyTorch Connectomics - Deep learning framework for automatic and semi-automatic annotation of connectomics datasets, powered by PyTorch.
    • SNT - ImageJ framework for semi-automated tracing and analysis of neurons.
    • TrailMap - Software package to extract axonal data from cleared brains.
    • Wholebrain - Automated cell detection and registration of whole-brain images with plot of cell counts per region and Hemishpere.
    • ZVQ - Zebrafish Vascular Quantification - Image analysis pipeline to perform 3D quantification of the total or regional zebrafish brain vasculature using the image analysis software Fiji.

    Plant science

    • Aradeepopsis - A versatile, fully open-source pipeline to extract phenotypic measurements from plant images.
    • LeafByte - Free and open source mobile app for measuring herbivory quickly and accurately.
    • PaCeQuant - An ImageJ-based tool which provides a fully automatic image analysis workflow for PC shape quantification.
    • PhenotyperCV - Header-only C++11 library using OpenCV for high-throughput image-based plant phenotyping.
    • PlantCV - Open-source image analysis software package targeted for plant phenotyping.
    • PlantSeg - Tool for cell instance aware segmentation in densely packed 3D volumetric images.
    • RhizoTrak - Open source tool for flexible and efficient manual annotation of complex time-series minirhizotron images.
    • Rhizovision Explorer - Free and open-source software developed for estimating root traits from images acquired from a flatbed scanner or camera.
    • RootPainter - Deep learning segmentation of biological images with corrective annotation.

    Fluoresence in situ hybridization

    • Big-fish - Python package for the analysis of smFISH images.
    • DypFISH - Python library for spatial analysis of smFISH images.
    • RS-FISH - Fiji plugin to detect FISH spots in 2D/3D images which scales to very large images.
    • Spotiflow - A deep learning-based, threshold-agnostic, and subpixel-accurate spot detection method developed for spatial transcriptomics workflows.
    • TissUUmaps - Visualizer of NGS data, plot millions of points and interact, gate, export. ISS rounds and base visualization.

    Electron and super resolution microscopy

    • ASI_MTF - ImageJ macro to calculate the modulation transfer function (MTF) based on a knife edge (or slanted edge) measurement.
    • Empanada - Panoptic segmentation algorithms for 2D and 3D electron microscopy images.
    • Em-scalebartools - Fiji/ImageJ macros to quickly add a scale bar to an (electron microscopy) image.
    • Picasso - A collection of tools for painting super-resolution images.
    • SMAP - A modular super-resolution microscopy analysis platform for SMLM data.
    • ThunderSTORM - A comprehensive ImageJ plugin for SMLM data analysis and super-resolution imaging.

    Image restoration and quality assessment

    • CSBDeep - A deep learning toolbox for microscopy image restoration and analysis.
    • Ijp-color - Plugins for ImageJ - color space conversions and color calibration.
    • Image Quality - Open source software library for Image Quality Assessment (IQA).
    • LLSpy - Python library to facilitate lattice light sheet data processing.
    • NCS - Noise correction algorithm for sCMOS cameras.

    Cell migration and particle tracking

    • CellMigration - Analysis of 2D cell migration in Igor.
    • TrackMate - User-friendly interface that allows for performing tracking, data visualization, editing results and track analysis in a convenient way.
    • TrackMateR - R package to analyze cell migration and particle tracking experiments using outputs from TrackMate.
    • Trackpy - Fast and Flexible Particle-Tracking Toolkit.
    • 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 - 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 - Software for tracking cellular shape changes and dynamic distributions of fluorescent reporters at the cell membrane.
    • Ultrack - Versatile cell tracking method for 2D, 3D, and multichannel timelapses, overcoming segmentation challenges in complex tissues.
    • Usiigaci - Stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning.

    Pathology

    • FastPathology - Open-source software for deep learning-based digital pathology.
    • HistoClean - Tool for the preprocessing and augmentation of images used in deep learning models.
    • Minerva - Image viewer designed specifically to make it easy for non-expert users to interact with complex tissue images.
    • Orbit - A versatile image analysis software for biological image-based quantification using machine learning, especially for whole slide imaging.
    • PathML - An open-source toolkit for computational pathology and machine learning.
    • PAQUO - A library for interacting with QuPath from Python.
    • QuPath - Open source software for digital pathology image analysis.

    Mycology

    Microbiology

    • BactMap - A command-line based R package that allows researchers to transform cell segmentation and spot detection data generated by different programs into various plots.
    • BacStalk - Interactive and user-friendly image analysis software tool to investigate the cell biology of common used bacterial species.
    • BiofilmQ - Advanced biofilm analysis tool for quantifying the properties of cells inside large 3-dimensional biofilm communities in space and time.

    Yeast imaging

    • BABY - An image processing pipeline for accurate single-cell growth estimation of budding cells from bright-field stacks.
    • htsimaging - Python package for high-throughput single-cell imaging analysis.
    • YeastMate - Neural network-assisted segmentation of mating and budding events in S. cerevisiae.
    • YeaZ - An interactive tool for segmenting yeast cells using deep learning.

    Other

    • AICSImageIO - Image reading, metadata conversion, and image writing for nicroscopy images in Python.
    • 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 - Collection of Fiji/ImageJ plug-ins for skeletal biology.
    • CaPTk - Cancer Imaging Phenomics Toolkit: A software platform to perform image analysis and predictive modeling tasks.
    • ColiCoords - Python project for analysis of fluorescence microscopy data from rodlike cells.
    • 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 - Command-line tools for organizing measurements extracted from images.
    • DetecDiv - Comprehensive set of tools to analyze time microscopy images using deep learning methods.
    • MIA - Fiji plugin which provides a modular framework for assembling image and object analysis workflows.
    • MorphoGraphX - Open source application for the visualization and analysis of 4D biological datasets.
    • Napari-aicsimageio - Multiple file format reading directly into napari using pure Python.
    • NEFI2 - Python tool created to extract networks from images.
    • Neurite - Neural networks toolbox focused on medical image analysis.
    • Nd2reader - A pure-Python package that reads images produced by NIS Elements 4.0+.
    • OAD - Collection of tools and scripts useful to automate microscopy workflows in ZEN Blue using Python and Open Application Development tools.
    • Pycytominer - Data processing functions for profiling perturbations.
    • Pyotf - A simulation software package for modelling optical transfer functions (OTF)/point spread functions (PSF) of optical microscopes written in Python.
    • PyScratch - Open source tool that autonomously performs quantitative analysis of in vitro scratch assays.
    • 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.
    • SimpleITK - Open-source multi-dimensional image analysis in Python, R, Java, C#, Lua, Ruby, TCL and C++.
    • Vaa3D - Open-source software for 3D/4D/5D image visualization and analysis.
    • XitoSBML - ImageJ plugin which creates a Spatial SBML model from segmented images.
    • Z-stack Depth Color Code - ImageJ/Fiji plugin to colorcode Z-stacks/hyperstacks.
    • ZeroCostDL4Mic - Google Colab to develop a free and open-source toolbox for deep-Learning in microscopy.
    • ZetaStitcher - Tool designed to stitch large volumetric images such as those produced by light-sheet fluorescence microscopes.

    Publications

    Footnotes

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