DICOM converted Slide Microscopy images for the TCGA-DLBC collection

This dataset corresponds to a collection of images and/or image-derived data available from National Cancer Institute Imaging Data Commons (IDC) [1]. This dataset was converted into DICOM representation and ingested by the IDC team. You can explore and visualize the corresponding images using IDC Portal here: TCGA-DLBC. You can use the manifests included in this Zenodo record to download the content of the collection following the Download instructions below. Collection description There is no available description page for this collection. Citation guidelines can be found on the Citing TCGA in Publications and Presentations information page. Files included A manifest file's name indicates the IDC data release in which a version of collection data was first introduced. For example, collection_id-idc_v8-aws.s5cmd corresponds to the contents of the collection_id collection introduced in IDC data release v8. If there is a subsequent version of this Zenodo page, it will indicate when a subsequent version of the corresponding collection was introduced. tcga_dlbc-idc_v18-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets tcga_dlbc-idc_v18-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets tcga_dlbc-idc_v18-dcf.dcf: Gen3 manifest (for details see https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids) Note that manifest files that end in -aws.s5cmd reference files stored in Amazon Web Services (AWS) buckets, while -gcs.s5cmd reference files in Google Cloud Storage. The actual files are identical and are mirrored between AWS and GCP. Download instructions Each of the manifests include instructions in the header on how to download the included files. To download the files using .s5cmd manifests: install idc-index package: pip install --upgrade idc-index download the files referenced by manifests included in this dataset by passing the .s5cmd manifest file: idc download manifest.s5cmd. To download the files using .dcf manifest, see manifest header. Acknowledgments Imaging Data Commons team has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Task Order No. HHSN26110071 under Contract No. HHSN261201500003l. References [1] Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H. J. W., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R. National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence. RadioGraphics (2023). https://doi.org/10.1148/rg.230180本数据集对应美国国家癌症研究所影像数据公共库（National Cancer Institute Imaging Data Commons, IDC）[1] 收录的图像及/或图像衍生数据集合。该数据集已被转换为医学数字成像和通信（Digital Imaging and Communications in Medicine, DICOM）格式，并由IDC团队完成数据摄入。你可通过此处的IDC门户探索并可视化对应图像：TCGA-DLBC。你可借助本Zenodo记录中包含的清单文件，按照下方的下载说明下载该集合的内容。 集合说明 本集合暂无可用的说明页面。 引用规范可参见《在出版物及演示文稿中引用癌症基因组图谱（The Cancer Genome Atlas, TCGA）》信息页面。 包含文件 清单文件名标识了该集合数据版本首次被引入的IDC数据发布版本。例如，collection_id-idc_v8-aws.s5cmd 对应于IDC数据发布版本v8中引入的collection_id集合内容。若本Zenodo页面存在后续版本，将标注对应集合后续版本的引入时间。 tcga_dlbc-idc_v18-aws.s5cmd：可从公开亚马逊云服务（Amazon Web Services, AWS）存储桶下载的文件清单 tcga_dlbc-idc_v18-gcs.s5cmd：可从公开谷歌云存储（Google Cloud Storage, GCS）存储桶下载的文件清单 tcga_dlbc-idc_v18-dcf.dcf：Gen3格式清单文件（详情参见 https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids） 请注意，后缀为-aws.s5cmd的清单文件指向存储于AWS存储桶中的文件，而-gcs.s5cmd后缀的清单文件则指向谷歌云存储中的文件。实际文件内容完全一致，且在AWS与谷歌云平台（Google Cloud Platform, GCP）间实现了镜像同步。 下载说明 每份清单文件的头部均包含了如何下载其中包含文件的说明。 使用.s5cmd格式清单下载文件： 安装idc-index工具包：pip install --upgrade idc-index 通过传入.s5cmd格式的清单文件，下载本数据集中清单文件所引用的所有文件：idc download manifest.s5cmd 使用.dcf格式清单下载文件，请参见清单文件头部的说明。 致谢 影像数据公共库团队的全部或部分研究经费由美国国家癌症研究所、美国国立卫生研究院的联邦资金资助，项目任务订单编号为HHSN26110071，合同编号为HHSN261201500003l。 参考文献 [1] Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H. J. W., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R. 美国国家癌症研究所影像数据公共库：迈向影像人工智能的透明化、可复现性与可扩展性. 放射学图谱（RadioGraphics）, 2023. https://doi.org/10.1148/rg.230180