dipy: DIPY is the paragon 3D/4D+ 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.
NeuroVault: Easy to use web database for statistical maps.
RegNet: Deformable Cross-modality MRI Registration Using 3D CNN
3DUnetCNN: Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
LiviaNET: This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"
3D-F-CNN-BrainStruct: This repository contains materials employed in our work to segment subcortical brain structures by employing a 3D fully Convolutional Neural Network.
BROCCOLI: BROCCOLI: Software for Fast fMRI Analysis on Many-Core CPUs and GPUs
image-registration-cnn: [Incomplete] A PyTorch implementation of CNN based MRI image registration based on MICCAI 2018 paper "Linear and Deformable Image Registration with 3D Convolutional Neural Networks"
3D-brain-segmentation: This is a repository containing code to Paper "Optimized High Resolution 3D Dense-U-Net Network for Brain and Spine Segmentation" published at MDPI Applied sciences journal - https://www.mdpi.com/2076-3417/9/3/404 .