HeLa cell images with four labels (nuclear envelope, nucleus, rest of the cell, and background) for deep learning architecture training.
DOI10.5281/zenodo.3874949Zenodo3874949MaRDI QIDQ6705190
Dataset published at Zenodo repository.
Author name not available (Why is that?)
Publication date: 19 May 2020
Copyright license: No records found.
This is a data set that contains labeledHeLa cell images, generated in MATLAB Image Labeler, indicating the four different classes - nuclear envelope, nucleus, rest of the cell, and backgroundfor deep learning architecture training. Details of the imaging and preparation have been published in: CefaKarabağ,Martin L.Jones,Christopher J.Peddie,Anne E.Weston,Lucy M.Collinson,Constantino CarlosReyes-Aldasoro. Segmentation and Modelling of the Nuclear Envelope of HeLa Cells Imaged with Serial Block Face Scanning Electron Microscopy.J. Imaging2019,5(9), 75;https://doi.org/10.3390/jimaging5090075 and Thedata setsare freely available through EMPIAR: http://dx.doi.org/10.6019/EMPIAR-10094 EMPIAR. Details on the segmentationand analysis ofHeLa cellshave been published in: CefaKarabağ,Martin L.Jones,Christopher J.Peddie,Anne E.Weston,Lucy M.Collinson,Constantino CarlosReyes-Aldasoro. Semantic Segmentation of HeLa Cells: An Objective Comparison between one Traditional Algorithm and Three Deep-Learning Architectures,BioRxiv,https://doi.org/10.1101/2020.03.05.978478 and CefaKarabağ,Martin L.Jones,Christopher J.Peddie,Anne E.Weston,Lucy M.Collinson,Constantino CarlosReyes-Aldasoro. Segmentation and Modelling of the Nuclear Envelope of HeLa Cells Imaged with Serial Block Face Scanning Electron Microscopy.J. Imaging2019,5(9), 75;https://doi.org/10.3390/jimaging5090075
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