Reverse Dependencies of monai

The following projects have a declared dependency on monai:

• 2404-segmentation-pipeline — no summary
• AbdomenAtlas — A package for 3D medical image segmentation using deep learning techniques.
• bioimage_embed — no summary
• bkh-pytorch-utils — A rapid prototyping tool for MONAI & PyTorch Lightning
• BrainLes-AURORA — Segmentation models for cancer metastasis in brain MR.
• crashs — CRASHS: Cortical Reconstruction for Automated Segmentation of Hippocampal Subfields (ASHS)
• csc-mlops — An MLOps framework for development of clinical applications
• ct-counterfactuals — Models and methods to generate counterfactuals for computed tomography scans
• cyto-dl — Collection of representation learning models, techniques, callbacks, utils, used to create latent variable models of cell shape, morphology and intracellular organization.
• deep-labelprop — Label propagation using deep registration
• DeepMuon — Interdisciplinary Deep Learning Platform
• delia — DICOM Extraction for Large-scale Image Analysis (DELIA).
• dsbundle — Streamline your data science setup with dsbundle in one effortless install.
• edanif — EDA-NIf creates a dataframe containing meta information of NIfTi files and provides several useful features.
• EMCqMRI — A distribution of a general tool for training and inference of QMRI models
• EmphysemaSeg — Lobe segmentation and emphysema quantification for chest CT
• fastMONAI — fastMONAI library
• fedbiomed-cli — no summary
• fl4health — Federated Learning for Health
• fluospotter — Python library designed for nuclei segmentation and puncta detection in fluorescence microscopy images.
• fuse-med-ml — A python framework accelerating ML based discovery in the medical field by encouraging code reuse. Batteries included :)
• gandlf — PyTorch-based framework that handles segmentation/regression/classification using various DL architectures for medical imaging.
• ganslate — GAN image-to-image translation framework made simple and extensible.
• geowatch — no summary
• imsy-htc — Framework for automatic classification and segmentation of hyperspectral images.
• instanseg-torch — Package for instanseg-torch PyPi
• interactivenet — InteractiveNet, a framework for minimally interactive medical image segmentation.
• kaiko-eva — Evaluation Framework for oncology foundation models.
• landmarker — A PyTorch-based toolkit for (anatomical) landmark detection in images.
• meddlr — Meddlr is a config-driven framework built to simplify ML-based medical image reconstruction and analysis.
• medical-data — Helpful data utilities for deep learning in medical image analysis/medical image computing
• medical-dl-utils — Helpful utilities for deep learning in medical image analysis/medical image computing
• MedicalMultitaskModeling — Multitask learning framework for medical data
• membrain-seg — membrane segmentation in 3D for cryo-ET
• mircat-seg — Segmentation library for Mirshahi CT Analysis Toolkit (MirCAT).
• mircato — Add your description here
• mist-medical — MIST is a simple, fully automated framework for 3D medical imaging segmentation.
• mmv-im2im — A python package for deep learing based image to image transformation
• monai-generative — Installer to help to use the prototypes from MONAI generative models in other projects.
• monai-nvflare — MONAI NVIDIA FLARE integration
• monailabel — Active Learning Toolkit for Healthcare Imaging
• monailabel-weekly — Active Learning Toolkit for Healthcare Imaging
• monaistream — Streaming Inference Extension for MONAI
• morphospaces — a library for creating and exploring morphospaces.
• multi_med_image_ml — Deep learning library to encode multiple brain images and other electronic health record data in disease detection.
• napari-cellseg3d — Plugin for cell segmentation in 3D
• napari-unicell — universal cell segmentation models
• novas3d — no summary
• p-mod-api — Propelwise Modules
• p2022 — Propelwise Modules
• p2t2 — no summary
• project-lighter — YAML-based automated rapid prototyping framework for deep learning experiments
• pycyclops — Framework for healthcare ML implementation
• qim3d — QIM tools and user interfaces for volumetric imaging
• RandAugment3d — Implementation of RandAugment in 3D
• rhizonet-package — Python package for RhizoNet-package
• scalingtheunet — This project is the source code to our paper.
• serotiny — A framework of tools to structure, configure and drive deep learning projects
• shapeaxi — Shape Analysis Exploration and Interpretability
• skm-tea — A package for interacting with, visualizing, and benchmarking the SKM-TEA dataset
• synthcity — Synthetic data generator and evaluator!
• torchmetrics — PyTorch native Metrics
• trans-utils — no summary
• UniCell — Universal cell segmentation
• ViNeSeg — Image Polygonal Annotation with Python combined with Auto-Segmentation
• viscy — computer vision for image-based phenotyping of single cells
• yucca — The modern framework for sandbox experimentation and out-of-the box machine learning on medical data.