Published December 19, 2023
| Version 0.1.0
Model
Open
StarDist Model for Nuclei Segmentation in Synthetic Lifeact-RFP Images
- 1. Universidad Carlos III de Madrid Escuela Politécnica Superior
Description
The StarDist model is specialized in performing nuclei segmentation on synthetic Lifeact-RFP images, which were initially generated from sir-DNA images using the Pix2Pix model. This model is an integral part of a pipeline that begins with image generation via Pix2Pix, followed by nuclei segmentation using StarDist.
StarDist has been fine-tuned using the ZeroCostDL4Mic notebook, with a specific training dataset sourced from Zenodo.
- Fine-Tuning Notebook:StarDist Notebook
- Training Dataset: Zenodo Dataset
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Additional details
References
- Schmidt, U., Weigert, M., Broaddus, C., & Myers, G. (2018). Cell detection with star-convex polygons. In Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part II 11 (pp. 265-273). Springer International Publishing.
- von Chamier, L., Laine, R. F., Jukkala, J., Spahn, C., Krentzel, D., Nehme, E., ... & Henriques, R. (2021). Democratising deep learning for microscopy with ZeroCostDL4Mic. Nature communications, 12(1), 2276.