| license: mit | |
| tags: | |
| - diffusion-model | |
| - image-segmentation | |
| - pathology | |
| - nuclei-segmentation | |
| - medical-imaging | |
| # DiffMix | |
| This repository contains pretrained semantic diffusion model checkpoints from | |
| [DiffMix: Diffusion Model-based Data Synthesis for Nuclei Segmentation and Classification in Imbalanced Pathology Image Datasets](https://arxiv.org/abs/2306.14132), presented at MICCAI 2023. | |
| ## Checkpoints | |
| - `consep-ema_0.9999_010000.pt`: checkpoint trained for the CoNSeP dataset. | |
| - `glysac-ema_0.9999_010000.pt`: checkpoint trained for the GLySAC dataset. | |
| Use each checkpoint with the corresponding scripts in the [official implementation](https://github.com/hvcl/DiffMix), specifically `semantic-diffusion-model/scripts_ddim_sample/`. | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{oh2023diffmix, | |
| title={Diffmix: Diffusion model-based data synthesis for nuclei segmentation and classification in imbalanced pathology image datasets}, | |
| author={Oh, Hyun-Jic and Jeong, Won-Ki}, | |
| booktitle={International conference on medical image computing and computer-assisted intervention}, | |
| pages={337--345}, | |
| year={2023}, | |
| organization={Springer} | |
| } | |
| ``` | |