Published October 26, 2023
| Version v1
Dataset
Open
Deep learning segmentation projects of FIB-SEM dataset of U2-OS cell
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1.
University of Helsinki
Contributors
Others:
-
1.
University of Warmia and Mazury in Olsztyn
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2.
University of Ljubljana
Description
This submission includes ground truth datasets that were used to segment the nuclear envelope (NE), mitochondria, endoplasmic reticulum (ER) and Golgi from a human bone osteosarcoma epithelial cell (U2-OS) imaged using focused-ion beam scanning electron microscopy (FIB-SEM).
The full FIB-SEM dataset is deposited to EMPIAR (https://www.ebi.ac.uk/empiar, EMPIAR-11746).
Methods
Training of convolutional neural network models and prediction of datasets were done in DeepMIB tool of Microscopy Image Browser (https://mib.helsinki.fi/)
Notes
For the full description see:
- "Datasets and DeepMIB projects for segmentation of organelles of U2OS cell.pdf" document attached to this deposition
- Explanation video on youtube.com (https://youtu.be/-IXB4Da9VMw)
Files
0_Segmentation.zip
Files
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Additional details
Related works
- Is supplement to
- Video/Audio: 10.5281/zenodo.10024015 (DOI)
References
- Microscopy Image Browser: A platform for segmentation and analysis of multidimensional datasets I. Belevich, M. Joensuu, D. Kumar, H. Vihinen and E. Jokitalo PLoS Biology 2016 Jan 4;14(1):e1002340. doi: 10.1371/journal.pbio.1002340
- DeepMIB: User-friendly and open-source software for training of deep learning network for biological image segmentation I. Belevich, and E. Jokitalo PLoS Comput Biol. 2021 Mar 2;17(3):e1008374. doi: 10.1371/journal.pcbi.1008374