Dataset Open Access
De, Trina;
Urbanski, Adrian;
Thangamani, Subasini;
Wyrzykowska, Maria;
Yakimovich, Artur
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"title": "HeLaCytoNuc: fluorescence microscopy dataset with segmentation masks for cell nuclei and cytoplasm",
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"affiliation": "Center for Advanced Systems Understanding, Helmholtz-Zentrum Dresden-Rossendorf",
"orcid": "0000-0003-1111-9851",
"name": "De, Trina"
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"affiliation": "Center for Advanced Systems Understanding, Helmholtz-Zentrum Dresden-Rossendorf",
"orcid": "0009-0008-6619-3665",
"name": "Urbanski, Adrian"
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"affiliation": "Center for Advanced Systems Understanding, Helmholtz-Zentrum Dresden-Rossendorf",
"name": "Thangamani, Subasini"
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"affiliation": "Center for Advanced Systems Understanding, Helmholtz-Zentrum Dresden-Rossendorf",
"name": "Wyrzykowska, Maria"
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"affiliation": "Center for Advanced Systems Understanding, Helmholtz-Zentrum Dresden-Rossendorf",
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"name": "Yakimovich, Artur"
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"keywords": [
"Fluorescence microscopy",
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"description": "<p><strong>Data Description:</strong></p>\n\n<p>This dataset comprises fluorescence micrographs of HeLa cells, specifically labelled to identify nuclei and cell cytoplasm. These images were acquired as a technical calibration for a high-content screening study detailed and published in [1].</p>\n\n<p>The HeLa cell line (ATCC-CCL-2), a widely used immortalised cell line in laboratory research, was cultured under standard conditions. Post-cultivation, the cells were fixed and stained with fluorescent dyes to visualise the nuclei and cytoplasm. The nuclei were stained with DAPI (4',6-diamidino-2-phenylindole), a blue-fluorescent DNA stain, while fluorescent-labeled phalloidin was used to detect actin filaments and delineate the cytoplasm. The entire process of cell culture, fixation, staining, and imaging adhered strictly to the protocols described in [1].</p>\n\n<p>The preprocessed dataset includes 2,676 8-bit RGB images, each with a pixel resolution of 520 x 696 pixels. In these images, only two of the RGB channels are utilized: the red channel represents the cytoplasm, and the blue channel represents the nuclei. The dataset is divided into training, validation, and test subsets in a 70:20:10 ratio. The entire dataset is accompanied by instance segmentation masks for nuclei and cytoplasm objects obtained through a specialised CellProfiler [2] software. Notably, the test subset was annotated manually by a specialist, ensuring high-quality annotations. The original raw images are of a higher resolution, 1040 x 1392 pixels, and have a bit depth of 16 bits, providing more detailed information for advanced analyses.</p>\n\n<p><br>\n<strong>File Description:</strong></p>\n\n<p>The file structure of the zip files is as follows:</p>\n\n\n\n<p>HeLaCytoNuc_{train/validation/test}.zip -></p>\n\n<p>- images -> {filename}.tif</p>\n\n<p>- nuclei_masks -> {filename}.tif</p>\n\n<p>- cytoplasm_masks -> {filename}.tif</p>\n\n\n\n<p>HeLaCytoNuc_raw_images.zip -> {filename}.tif</p>\n\n\n\n<p>HeLaCytoNuc_test_cellprofiler_masks.zip -></p>\n\n<p>- nuclei_masks -> {filename}.tif</p>\n\n<p>- cytoplasm_masks -> {filename}.tif </p>\n\n\n\n<p><strong>References:</strong></p>\n\n<p>1. Rämö, Pauli, Anna Drewek, Cécile Arrieumerlou, Niko Beerenwinkel, Houchaima Ben-Tekaya, Bettina Cardel, Alain Casanova et al. "Simultaneous analysis of large-scale RNAi screens for pathogen entry." <em>BMC genomics</em> 15 (2014): 1-18.</p>\n\n<p>2. Carpenter, Anne E., Thouis R. Jones, Michael R. Lamprecht, Colin Clarke, In Han Kang, Ola Friman, David A. Guertin et al. "CellProfiler: image analysis software for identifying and quantifying cell phenotypes." <em>Genome biology</em> 7 (2006): 1-11.</p>",
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| All versions | This version | |
|---|---|---|
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