HeLaCytoNuc: fluorescence microscopy dataset with segmentation masks for cell nuclei and cytoplasm

Data Description: 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]. 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]. 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. File Description: The file structure of the zip files is as follows: HeLaCytoNuc_{train/validation/test}.zip -> - images -> {filename}.tif - nuclei_masks -> {filename}.tif - cytoplasm_masks -> {filename}.tif HeLaCytoNuc_raw_images.zip -> {filename}.tif HeLaCytoNuc_test_cellprofiler_masks.zip -> - nuclei_masks -> {filename}.tif - cytoplasm_masks -> {filename}.tif References: 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." BMC genomics 15 (2014): 1-18. 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." Genome biology 7 (2006): 1-11.数据集说明：本数据集包含经特异性标记的海拉（HeLa）细胞荧光显微图像，可区分细胞核与细胞细胞质。该图像集为一项已发表于文献[1]的高内涵筛选研究的技术校准实验所采集。 海拉（HeLa）细胞系（ATCC-CCL-2）是实验室研究中广泛应用的永生细胞系，本数据集采用的细胞均在标准培养条件下增殖。培养结束后，对细胞进行固定并使用荧光染料染色，以实现细胞核与细胞质的可视化成像。细胞核采用DAPI（4',6-二脒基-2-苯基吲哚）染色，该物质为蓝色荧光DNA染料；同时使用荧光标记的鬼笔环肽标记肌动蛋白丝，以勾勒细胞质轮廓。细胞培养、固定、染色及成像的全流程均严格遵循文献[1]中记载的实验方案。 预处理后的数据集包含2676张8位RGB图像，单张图像像素分辨率为520×696。该类图像仅使用RGB通道中的两个：红色通道对应细胞质信号，蓝色通道对应细胞核信号。 数据集按照70:20:10的比例划分为训练集、验证集与测试集三个子集。全数据集配套有通过专用CellProfiler [2]软件生成的细胞核与细胞质实例分割掩码。值得注意的是，测试子集的标注由专业人员手动完成，以保障标注质量。 原始未预处理的图像分辨率更高，为1040×1392像素，位深度为16位，可为高级分析提供更丰富的细节信息。 文件说明：压缩包的文件结构如下： HeLaCytoNuc_{train/validation/test}.zip → - images → {filename}.tif - nuclei_masks → {filename}.tif - cytoplasm_masks → {filename}.tif HeLaCytoNuc_raw_images.zip → {filename}.tif HeLaCytoNuc_test_cellprofiler_masks.zip → - nuclei_masks → {filename}.tif - cytoplasm_masks → {filename}.tif 参考文献： 1. Rämö Pauli, Drewek Anna, Arrieumerlou Cécile, Beerenwinkel Niko, Ben-Tekaya Houchaima, Cardel Bettina, Casanova Alain 等. “大规模RNAi病原体侵入筛选的同步分析”. 《BMC基因组学》, 15(2014): 1-18. 2. Carpenter Anne E., Jones Thouis R., Lamprecht Michael R., Clarke Colin, Kang In Han, Friman Ola, Guertin David A 等. “CellProfiler：用于细胞表型识别与定量的图像分析软件”. 《基因组生物学》, 7(2006): 1-11.