Project-MONAI/GenerativeModels

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

Jupyter NotebookPythonShellmedical-imaginggenerative-adversarial-networkimage-translationanomaly-detectiongenerative-modelsimage-synthesismri-reconstructiondiffusion-modelsmonai
This is stars and forks stats for /Project-MONAI/GenerativeModels repository. As of 08 May, 2024 this repository has 339 stars and 46 forks.

MONAI Generative Models Prototyping repository for generative models to be integrated into MONAI core, MONAI tutorials, and MONAI model zoo. Features Network architectures: Diffusion Model, Autoencoder-KL, VQ-VAE, Autoregressive transformers, (Multi-scale) Patch-GAN discriminator. Diffusion Model Noise Schedulers: DDPM, DDIM, and PNDM. Losses: Adversarial losses, Spectral losses, and Perceptual losses (for 2D and 3D data using LPIPS, RadImageNet, and 3DMedicalNet pre-trained models). Metrics: Multi-Scale...
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