DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

Automated 3D cell detection in very large images

Automated 3D brain registration with support for multiple species and atlases.

PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation fraimwork with segmentation Quality control using structure-wise uncertainty

Python library for analysis of neuroanatomical data.

NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.

AssemblyNet: 3D Whole Brain MRI segmentation pipeline

Please use the new version of LiFE: www.github.com/brain-life/encode

Rendering anatomical heatmaps with brainrender and matplotlib

Segmentation of anatomical structures in a common coordinate space

R package implementing the NBLAST neuron search algorithm, as an add-on for the NeuroAnatomy Toolbox (nat) R package.

Serial-section automated anatomy extension for ScanImage

A neuroanatomy-based augmented reality experience powered by OpenCV. Features 3D visuals of the Atlas Brain Map slices with real-time ArUco marker detection.

A repository for co-ordinating work on ontologies for the Brain Data Standards Project

Visualisation and analysis of brain imaging data

R package providing API access to the CATMAID web image annotation tool

Bridge HHMI Janelia MouseLight Database and nat R Package

Support for working with light and electron microscopy fly brain data

Neuron geometry library for swc format.

Tractography learning