Medical Open Network for AI

Getting Started

Install monai

You can quickly get started with the Python Package Index (PyPI) or via several alternative installation approaches

2D Classification Examples

Image classification with MedNIST dataset
2D image classification demo

2D Segmentation Examples

Training and evaluation code examples for 2D medical image segmentation
2D image segmentation with Unet

3D Classification Examples

Training and evaluation code examples for 3D medical image classification
Brain MRI classification examples

Training and evaluation code examples for 3D medical image classification (with PyTorch Ignite)
Brain MRI classification examples with Ignite

3D Segmentation Examples

Brain tumor 3D segmentation
Brats segmentation tutorial

Abdominal CT segmentation
Spleen segmentation tutorial

Abdominal CT segmentation (with PyTorch Lightning)
Spleen segmentation tutorial with Lightning

Training and evaluation code examples for 3D medical image segmentation
Volumetric image segmentation examples

Training and evaluation code examples for 3D medical image segmentation (with PyTorch Ignite)
Volumetric image segmentation examples with Ignite

Build a segmentation workflow (with PyTorch Ignite)
Segmentation workflow demo with Ignite

Build a segmentation workflow (with Catalyst framework)
Segmentation workflow demo with Catalyst

Performance Acceleration

Training and evaluation code examples with Distributed Training supports
Distributed training examples

3D segmentation with Automatic Mixed Precision supports
Spleen segmentation tutorial with AMP supports

Accelerate model training by caching methods
Comparisons between different loading methods

Fast training under MONAI features
Fast training demo

Data-parallel training with multiple-GPUs
Multi-GPU training demo

GPU-based preprocessing in native PyTorch
GPU-based pipeline demo

Modules Demo

Histology image transformation demo
2D transformation demo

Volumetric image transformation demo
3D transformation tutorial

Integrate 3rd party transforms
Integrate BatchGenerator, TorchIO, Rising and ITK transforms

Load medical images in MONAI
Tutorial for loading different formats of medical images in MONAI

GAN tutorial with MedNIST dataset
Generate medical images with GAN

GAN workflow with MedNIST dataset
Train a GAN model to reconstruct images of Hand CT scans

Models ensemble with MONAI
Models ensemble demo with MONAI

Read Nifti files with MONAI
Tutorial for loading Nifti files with MONAI

Post transforms tutorial
Post transforms demo for model output

Public Datasets tutorial
Easily use and create public Datasets

Train on Decathlon datasets with DynUNet
Tutorial for training on all 10 decathlon datasets with DynUNet

Training and evaluation code examples with MONAI engines
GAN and Image segmentation workflow examples with MONAI engines