AI Toolkit for Healthcare Imaging
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Updated
Jun 22, 2024 - Python
AI Toolkit for Healthcare Imaging
A deep learning model and training/testing/inference library in PyTorch for segmentation, classification, object detection and self-supervised learning using radiology data.
Config-based framework for organized and reproducible deep learning. MONAI Bundle + PyTorch Lightning.
MONAI Label is an intelligent open source image labeling and learning tool.
cardiAc ultrasound Segmentation & Color-dopplEr dealiasiNg Toolbox (ASCENT)
A 3D Slicer extension to use AMASSS, ALI-CBCT and ALI-IOS
Medical image augmentation tool that can be integrated with Pytorch & MONAI.
Implementations of recent research prototypes/demonstrations using MONAI.
Brain Tumor Segmentation Pipeline for BraTS Challenge
All the code used in our YouTube videos (starting from 2024 videos) can be found here.
(NeurIPS 2022 CellSeg Challenge - 1st Winner) Open source code for "MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy"
Semantic segmentation and image-to-image translation based on AI
A microservice to expose a latent diffusion model for 3D Brain T1-weighted Image generation
Code for the paper published in Deep Generative Models for Health Workshop at the Neurips 2023.
A collection of pre-built dataset classes for medical datasets.
Automatic Segmentation of Vestibular Schwannoma with MONAI (PyTorch)
Project for creating synthetic tumor images from existing source images to train neural networks for lung tumor segmentation
cardiac segmentation with 3d slicer
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