From 433fd62721727c2d3bb236cc02ff2c64a361afcc Mon Sep 17 00:00:00 2001 From: Virginia Fernandez Date: Mon, 16 Sep 2024 16:45:54 +0100 Subject: [PATCH] Adding autoencoder info to README. Signed-off-by: Virginia Fernandez --- README.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/README.md b/README.md index 7e7ca7aaf..f90ffb862 100644 --- a/README.md +++ b/README.md @@ -331,6 +331,12 @@ Example shows the use cases of applying SPADE normalization to a latent diffusio ##### [Diffusion Models for Implicit Image Segmentation Ensembles](./image_to_image_translation) Example shows the use cases of how to use MONAI for 2D segmentation of images using DDPMs. The same structure can also be used for conditional image generation, or image-to-image translation. +##### [Spatial variational autoencoder for 2D modelling and synthesis](./2d_autoencoderkl) +Example shows the use cases of applying a spatial VAE to a 2D synthesis example. To obtain realistic results, the model is trained on the original VAE losses, as well as perceptual and adversarial ones. + +##### [Spatial variational autoencoder for 3D modelling and synthesis](./3d_autoencoderkl) +Example shows the use cases of applying a spatial VAE to a 3D synthesis example. To obtain realistic results, the model is trained on the original VAE losses, as well as perceptual and adversarial ones. + ##### [Evaluate Realism and Diversity of the generated images](./realism_diversity_metrics) Example shows the use cases of using MONAI to evaluate the performance of a generative model by computing metrics such as Frechet Inception Distance (FID) and Maximum Mean Discrepancy (MMD) for assessing realism, as well as MS-SSIM and SSIM for evaluating image diversity.