Update README.md

README.md

@@ -1,3 +1,41 @@
 ---
 license: mit
+language:
+- en
+tags:
+- 3d
+- medical
+- image-synthesis
+- image-generation
+- wavelet-transform
+arxiv: 2402.19043
 ---
+
+# WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis
+This is the officical model repository of the paper "[**WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis**](https://pfriedri.github.io/wdm-3d-io)" by Paul Friedrich, Julia Wolleb, Florentin Bieder, Alicia Durrer and Philippe C. Cattin.
+
+**WDM** is a wavelet-based medical image synthesis framework that can generate high-resolution medical images like CT or MR scans.
+For more information on our method, we refer to our [**project page**](https://pfriedri.github.io/wdm-3d-io) or the [**paper**](https://arxiv.org/abs/2402.19043).
+
+## Origial GitHub repository
+If you want to use the pre-trained models provided in this repository, download the model weights and follow the instructions in the official [GitHub repository](https://github.com/pfriedri/wdm-3d).
+
+## Pre-trained models
+We will soon provide models for different datasets and different image resolutions (starting with BraTs and LIDC-IDRI at resolutions of 128³ and 256³).
+
+## Hardware requirements
+To sample images from the provided models, you require a GPU with at least:
+- 3 GB VRAM - for 128 x 128 x 128 (model uses ~2.55 GB)
+- 8 GB VRAM - for 256 x 256 x 256 (model uses ~7.27 GB)
+
+The models were trained on a system with an an AMD Epyc 7742 CPU and a NVIDIA A100 (40GB) GPU.
+
+## Citation
+If you find this work useful, please cite:
+```bibtex
+@article{friedrich2024wdm,
+         title={WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis},
+         author={Paul Friedrich and Julia Wolleb and Florentin Bieder and Alicia Durrer and Philippe C. Cattin},
+         year={2024},
+         journal={arXiv preprint arXiv:2402.19043}}
+```