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.

数据集描述：
本数据集包含经过特异性标记以区分细胞核与细胞细胞质的海拉（HeLa）细胞荧光显微图像。本批图像作为一项已发表于文献[1]的高内涵筛选研究的技术校准数据采集所得。
海拉细胞系（ATCC-CCL-2）是实验室研究中广泛使用的永生化细胞系，以标准培养条件进行培养。培养完成后，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：细胞核使用DAPI（4',6-二脒基-2-苯基吲哚，一种蓝色荧光DNA染料）染色，而荧光标记的鬼笔环肽则用于检测肌动蛋白丝并勾勒细胞质轮廓。细胞培养、固定、染色及成像的全流程严格遵循文献[1]中描述的实验方案。
预处理后的数据集包含2676张8位RGB图像，单张图像的像素分辨率为520×696。本批图像仅使用RGB通道中的两个：红色通道对应细胞质，蓝色通道对应细胞核。数据集按照70:20:10的比例划分为训练集、验证集与测试集子集。本数据集配套有通过专用CellProfiler软件生成的细胞核与细胞质实例分割掩码。值得注意的是，测试集子集由专业人员手动标注，以确保标注质量。
原始未处理图像拥有更高的分辨率（1040×1392像素）与16位色深，可为进阶分析提供更为丰富的细节信息。

文件描述：
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, Anna Drewek, Cécile Arrieumerlou, Niko Beerenwinkel, Houchaima Ben-Tekaya, Bettina Cardel, Alain Casanova 等. 《病原体入侵相关大规模RNAi筛选的同步分析》. BMC基因组学（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 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（Genome biology）, 7(2006): 1-11.

搜集汇总

背景与挑战

背景概述

该数据集是一个包含2,676张HeLa细胞荧光显微镜图像的专业数据集，专门用于细胞核和细胞质的实例分割研究。图像使用DAPI和荧光标记鬼笔环肽染色，以红色和蓝色通道分别表示细胞质和细胞核，并已按70:20:10比例划分为训练、验证和测试子集，同时提供高质量的手动标注分割掩码。数据集还包含高分辨率原始图像，适用于高级图像分析和机器学习模型训练。