CellSighter Test Dataset: CRC Multiplexed Images
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Description: This dataset contains multiplexed protein images from colorectal cancer (CRC) patients, used to benchmark the CellSighter algorithm. The images were derived from a subset of the publicly available CRC-FFPE-CODEX collection hosted by The Cancer Imaging Archive (TCIA): https://www.cancerimagingarchive.net/collection/crc_ffpe-codex_cellneighs/ Original dataset citation: Schürch, C. M., Bhate, S., Barlow, G., Phillips, D., Noti, L., Zlobec, I., Chu, P., Black, S., Demeter, J., McIlwain, D., Samusik, N., Goltsev, Y., & Nolan, G. (2020). High-dimensional imaging of colorectal carcinoma and other tumors with 50+ markers [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2020.FQN0-0326 Derived Annotations: The images were re-segmented using DeepCell (https://www.deepcell.org/). Cell type classifications were generated using CellTune (https://celltune.org/). These segmentations and classifications are original contributions and do not appear in the TCIA dataset. Images, segmentations, and classifications were formatted for use with CellSighter. Usage Policy: This dataset is shared under the terms of TCIA’s data usage policy. It must not be used in any way that could identify individuals. Users must cite both the original dataset and this derived dataset appropriately and use in accordance with TCIA guidelines. TCIA data usage policy: https://www.cancerimagingarchive.net/data-usage-policies-and-restrictions/ Use Case: This dataset was used to evaluate CellSighter, as described in: Amitay, Y., Bussi, Y., Feinstein, B. et al. CellSighter: a neural network to classify cells in highly multiplexed images. Nat Commun 14, 4302 (2023). https://doi.org/10.1038/s41467-023-40066-7
数据集描述： 本数据集包含结直肠癌（colorectal cancer, CRC）患者的多重蛋白质成像（multiplexed protein images）数据，用于对CellSighter（CellSighter）算法进行性能基准测试。 该数据集的成像数据源自美国癌症影像档案库（The Cancer Imaging Archive, TCIA）托管的公开CRC-FFPE-CODEX数据集子集，数据集链接：https://www.cancerimagingarchive.net/collection/crc_ffpe-codex_cellneighs/ 原始数据集引用信息： Schürch, C. M.、Bhate, S.、Barlow, G.、Phillips, D.、Noti, L.、Zlobec, I.、Chu, P.、Black, S.、Demeter, J.、McIlwain, D.、Samusik, N.、Goltsev, Y. 与Nolan, G.（2020）。《使用50余种标记物对结直肠癌及其他肿瘤进行高维成像》[数据集]。美国癌症影像档案库。https://doi.org/10.7937/TCIA.2020.FQN0-0326 衍生标注说明： 本数据集的成像数据已通过DeepCell（DeepCell）进行了重新分割；细胞类型分类则通过CellTune（CellTune）生成。上述分割结果与细胞分类均为本次衍生工作的原创贡献，未在原始TCIA数据集中出现。所有成像数据、分割结果及细胞分类均已适配CellSighter的使用格式。 使用政策： 本数据集遵循美国癌症影像档案库的数据使用政策进行共享。严禁以任何可识别个体身份的方式使用本数据集。用户需恰当引用原始数据集与本次衍生数据集，并严格遵循美国癌症影像档案库的使用规范。 美国癌症影像档案库数据使用政策：https://www.cancerimagingarchive.net/data-usage-policies-and-restrictions/ 应用场景： 本数据集用于评估CellSighter算法，相关研究详见： Amitay, Y.、Bussi, Y.、Feinstein, B. 等。《CellSighter：用于高多重成像中细胞分类的神经网络》。《自然-通讯》，14卷，4302（2023）。https://doi.org/10.1038/s41467-023-40066-7
