DICOM converted Slide Microscopy images for the HTAN-WUSTL 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: HTAN-WUSTL. You can use the manifests included in this Zenodo record to download the content of the collection following the Download instructions below. Collection description The Human Tumor Atlas Network (HTAN) [2], part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. Please see the HTAN-WUSTL information page to learn more about the images and to obtain any supporting metadata for this collection. Citation guidelines can be found on the HTAN Publication Policy 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. htan_wustl-idc_v10-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets htan_wustl-idc_v10-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets htan_wustl-idc_v10-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 Collection of the images that were converted by IDC was supported through the Human Tumor Atlas Network, grants U2CCA233303-01 "Washington University Human Tumor Atlas Research Center" and 1U24CA233243-01 "Human Tumor Atlas Network: Data Coordinating Center" from National Cancer Institute. 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 [2] Rozenblatt-Rosen, O., Regev, A., Oberdoerffer, P., Nawy, T., Hupalowska, A., Rood, J. E., Ashenberg, O., Cerami, E., Coffey, R. J., Demir, E., Ding, L., Esplin, E. D., Ford, J. M., Goecks, J., Ghosh, S., Gray, J. W., Guinney, J., Hanlon, S. E., Hughes, S. K., Hwang, E. S., Iacobuzio-Donahue, C. A., Jané-Valbuena, J., Johnson, B. E., Lau, K. S., Lively, T., Mazzilli, S. A., Pe’er, D., Santagata, S., Shalek, A. K., Schapiro, D., Snyder, M. P., Sorger, P. K., Spira, A. E., Srivastava, S., Tan, K., West, R. B., Williams, E. H. & Human Tumor Atlas Network. The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution. Cell 181, 236–249 (2020). http://dx.doi.org/10.1016/j.cell.2020.03.053本数据集源自美国国家癌症研究所影像数据共享库（National Cancer Institute Imaging Data Commons, IDC）[1] 收录的图像及图像衍生数据集合。本数据集已被IDC团队转换为医学数字成像与通信（Digital Imaging and Communications in Medicine, DICOM）格式并完成入库。您可通过IDC门户的HTAN-WUSTL页面探索并可视化对应图像。您可遵循下方的下载说明，使用本Zenodo记录中包含的清单文件下载该数据集的全部内容。 数据集概况 人类肿瘤图谱网络（Human Tumor Atlas Network, HTAN）[2] 是美国国家癌症研究所（NCI）癌症登月计划的组成部分，旨在搭建临床、实验、计算与组织框架，为多种肿瘤类型生成信息丰富且易于获取的癌症演进三维图谱。 请访问HTAN-WUSTL信息页面，了解本数据集图像的更多详情，并获取相关支撑元数据。引用规范请参见HTAN出版政策信息页面。 包含文件 清单文件名可标识该数据集版本首次发布的IDC数据发布批次。例如，collection_id-idc_v8-aws.s5cmd对应于IDC数据发布v8中首次推出的collection_id数据集内容。若本Zenodo页面后续更新，将标注对应数据集后续版本的发布时间。 - htan_wustl-idc_v10-aws.s5cmd：用于从IDC公共亚马逊云科技（Amazon Web Services, AWS）存储桶下载文件的清单 - htan_wustl-idc_v10-gcs.s5cmd：用于从IDC公共谷歌云存储（Google Cloud Storage, GCS）存储桶下载文件的清单 - htan_wustl-idc_v10-dcf.dcf：Gen3格式清单（详情请参见https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids） 请注意，后缀为-aws.s5cmd的清单文件对应存储于AWS存储桶中的文件，而-gcs.s5cmd后缀的清单文件对应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（GCP）间互为镜像。 下载说明 所有清单文件的文件头均包含对应包含文件的下载说明。 1. 使用.s5cmd格式清单下载文件： - 安装idc-index工具包：执行命令 `pip install --upgrade idc-index` - 通过传入.s5cmd格式清单文件，下载本数据集中清单所引用的文件：`idc download manifest.s5cmd` 2. 使用.dcf格式清单下载文件，请参见清单文件头中的说明。 致谢 IDC团队完成的图像采集与转换工作得到了人类肿瘤图谱网络的支持，相关资助来自美国国家癌症研究所的两项项目：U2CCA233303-01“华盛顿大学人类肿瘤图谱研究中心”以及1U24CA233243-01“人类肿瘤图谱网络：数据协调中心”。 影像数据共享库团队的研发经费全部或部分来自美国国家癌症研究所与美国国立卫生研究院的联邦拨款，相关项目合同编号为HHSN261201500003l，任务订单编号为HHSN26110071。 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共享库：迈向影像人工智能的透明化、可复现性与可扩展性. RadioGraphics, 2023. https://doi.org/10.1148/rg.230180 [2] Rozenblatt-Rosen, O., Regev, A., Oberdoerffer, P., Nawy, T., Hupalowska, A., Rood, J. E., Ashenberg, O., Cerami, E., Coffey, R. J., Demir, E., Ding, L., Esplin, E. D., Ford, J. M., Goecks, J., Ghosh, S., Gray, J. W., Guinney, J., Hanlon, S. E., Hughes, S. K., Hwang, E. S., Iacobuzio-Donahue, C. A., Jané-Valbuena, J., Johnson, B. E., Lau, K. S., Lively, T., Mazzilli, S. A., Pe’er, D., Santagata, S., Shalek, A. K., Schapiro, D., Snyder, M. P., Sorger, P. K., Spira, A. E., Srivastava, S., Tan, K., West, R. B., Williams, E. H. & Human Tumor Atlas Network. 人类肿瘤图谱网络：以单细胞分辨率绘制肿瘤时空演进图谱. Cell, 181, 236–249, 2020. http://dx.doi.org/10.1016/j.cell.2020.03.053