Awesome Biological
Image Analysis 
Tools and resources for biological image analysis.
Biological image analysis aims to increase our understanding of
biology through the use of various computational techniques and
approaches to obtain valuable information from images.
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.
- BioImageXD - Free, open source
software package for analyzing, processing and visualizing
multi-dimensional microscopy images.
- 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.
- 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.
- GPim - Gaussian
processes and Bayesian optimization for images and hyperspectral
data.
- 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.
- 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.
- Brainreg-napari
- Automated 3D brain registration in napari 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.
- Cellfinder-napari
- Efficient cell detection in large images using cellfinder in napari.
- 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.
- RivuletPy -
Robust 3D Neuron Tracing / General 3D tree structure extraction in
Python for 3D images powered by the Rivulet2 algorithm.
- 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.
- DIRT -
Digital Imaging of Root Traits: Extract trait measurements from images
of monocot and dicot roots.
- 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.
- DECODE - Python
and PyTorch based deep learning tool for single molecule localization
microscopy.
- 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.
- Noise2Void - Learning
denoising from single noisy images.
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.
- SimpleElastix -
Multi-lingual medical image registration library.
- 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
Similar lists and
repositories
biologicalimageanalysis.md
Github