Dataset Open Access
De, Trina;
Urbanski, Adrian;
Thangamani, Subasini;
Wyrzykowska, Maria;
Yakimovich, Artur
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<foaf:name>Yakimovich, Artur</foaf:name>
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<dct:title>HeLaCytoNuc: fluorescence microscopy dataset with segmentation masks for cell nuclei and cytoplasm</dct:title>
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<dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2024</dct:issued>
<dcat:keyword>Fluorescence microscopy</dcat:keyword>
<dcat:keyword>high content microscopy</dcat:keyword>
<dcat:keyword>cytoskeleton</dcat:keyword>
<dcat:keyword>cell nuclei</dcat:keyword>
<dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2024-06-05</dct:issued>
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<dct:description><p><strong>Data Description:</strong></p> <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> <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&#39;,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> <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> <p><br> <strong>File&nbsp;Description:</strong></p> <p>The file structure of the zip files is as follows:</p> <p>HeLaCytoNuc_{train/validation/test}.zip -&gt;</p> <p>- images -&gt; {filename}.tif</p> <p>- nuclei_masks&nbsp; -&gt; {filename}.tif</p> <p>- cytoplasm_masks&nbsp; -&gt; {filename}.tif</p> <p>HeLaCytoNuc_raw_images.zip -&gt; {filename}.tif</p> <p>HeLaCytoNuc_test_cellprofiler_masks.zip -&gt;</p> <p>- nuclei_masks&nbsp; -&gt; {filename}.tif</p> <p>- cytoplasm_masks&nbsp; -&gt; {filename}.tif&nbsp;</p> <p><strong>References:</strong></p> <p>1.&nbsp;R&auml;m&ouml;, Pauli, Anna Drewek, C&eacute;cile Arrieumerlou, Niko Beerenwinkel, Houchaima Ben-Tekaya, Bettina Cardel, Alain Casanova et al. &quot;Simultaneous analysis of large-scale RNAi screens for pathogen entry.&quot;&nbsp;<em>BMC genomics</em>&nbsp;15 (2014): 1-18.</p> <p>2.&nbsp;Carpenter, Anne E., Thouis R. Jones, Michael R. Lamprecht, Colin Clarke, In Han Kang, Ola Friman, David A. Guertin et al. &quot;CellProfiler: image analysis software for identifying and quantifying cell phenotypes.&quot;&nbsp;<em>Genome biology</em>&nbsp;7 (2006): 1-11.</p></dct:description>
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