AI Toolkit for Healthcare Imaging

MONAI Tutorials

Implementations of recent research prototypes/demonstrations using MONAI.

MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

MONAI Label is an intelligent open source image labeling and learning tool.

(NeurIPS 2022 CellSeg Challenge - 1st Winner) Open source code for "MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy"

Segmentation deep learning ALgorithm based on MONai toolbox: single and multi-label segmentation software developed by QIMP team-Vienna.

MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.

MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.

Developing a UNet3D model for accurate MRI skull stripping using the Calgary Campinas 359 dataset, enhancing neuroimaging preprocessing workflows.

A 3D Slicer extension to use AMASSS, ALI-CBCT and ALI-IOS

Repository to train Latent Diffusion Models on Chest X-ray data (MIMIC-CXR) using MONAI Generative Models

Automatic Segmentation of Vestibular Schwannoma with MONAI (PyTorch)

Code for the paper published in Deep Generative Models for Health Workshop at the Neurips 2023.

This is Pooya Mohammadi, Open Source Enthusiast, AI Developer & Researcher

cardiAc ultrasound Segmentation & Color-dopplEr dealiasiNg Toolbox (ASCENT)

MONAIViz - 3D Slicer Extension

Config-based framework for organized and reproducible deep learning. MONAI Bundle + PyTorch Lightning.

An open source library for streaming and preprocessing point-of-care ultrasound video.

teeth segmentation using pytorch and monai