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README.md

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 # mnDINO: Accurate and robust segmentation of micronuclei with vision transformer networks
-This repository provides the pre-trained mnDINO model for our paper: [mnDINO: Accurate and robust segmentation of micronuclei with vision transformer networks](). The official PyTorch source code is publicly available on [GitHub](https://github.com/CaicedoLab/micronuclei-detection), and the annotated micronuclei dataset can be downloaded through the [Bioimage Archive](https://www.ebi.ac.uk/biostudies/bioimages/studies/S-BIAD2809). 
+This repository provides the pre-trained mnDINO model for our paper: [mnDINO: Accurate and robust segmentation of micronuclei with vision transformer networks](https://www.biorxiv.org/content/10.64898/2026.03.09.710648v2). The official PyTorch source code is publicly available on [GitHub](https://github.com/CaicedoLab/micronuclei-detection), and the annotated micronuclei dataset can be downloaded through the [Bioimage Archive](https://www.ebi.ac.uk/biostudies/bioimages/studies/S-BIAD2809). 
 
 The mnDINO model is specifically designed for highly efficient and accurate micronuclei segmentation in DNA-stained images across diverse experimental conditions. The model outputs both micronuclei and nuclei segmentation masks simultaneously. To accelerate future research in micronucleus (MN) biology. The dataset, code, and pre-trained model are made publicly available to facilitate future research in micronucleus (MN) biology.
 # Usage