five

The Cancer Genome Atlas Liver Hepatocellular Carcinoma Collection (TCGA-LIHC)

收藏
DataCite Commons2025-06-01 更新2024-07-13 收录
下载链接:
https://www.cancerimagingarchive.net/collection/tcga-lihc/
下载链接
链接失效反馈
官方服务:
资源简介:
The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) data collection is part of a larger effort to build a research community focused on connecting cancer phenotypes to genotypes by providing clinical images matched to subjects from The Cancer Genome Atlas (TCGA). Clinical, genetic, and pathological data resides in the Genomic Data Commons (GDC) Data Portal while the radiological data is stored on The Cancer Imaging Archive (TCIA). Matched TCGA patient identifiers allow researchers to explore the TCGA/TCIA databases for correlations between tissue genotype, radiological phenotype and patient outcomes. Tissues for TCGA were collected from many sites all over the world in order to reach their accrual targets, usually around 500 specimens per cancer type. For this reason the image data sets are also extremely heterogeneous in terms of scanner modalities, manufacturers and acquisition protocols. In most cases the images were acquired as part of routine care and not as part of a controlled research study or clinical trial.

癌症基因组图谱肝脏肝细胞癌(TCGA-LIHC)数据集属于一项更大规模研究项目的组成部分,该项目旨在构建专注于癌症表型与基因型关联研究的科研共同体,通过为来自癌症基因组图谱(The Cancer Genome Atlas, TCGA)的受试者匹配临床影像以达成目标。临床、遗传与病理数据存储于基因组数据共享(Genomic Data Commons, GDC)数据门户,而放射学影像数据则归档于癌症影像档案(The Cancer Imaging Archive, TCIA)。匹配后的TCGA患者标识符可支持研究人员检索TCGA与TCIA数据库,以探究组织基因型、放射学表型与患者预后之间的关联关系。TCGA的组织样本采集自全球众多站点,以达成其样本积累目标——通常每种癌症类型的样本量约为500份。正因如此,该影像数据集在扫描仪模态、设备厂商与采集协议等方面均呈现出极强的异质性。在多数情况下,这些影像均为常规诊疗流程中所采集,而非受控研究或临床试验的组成部分。
提供机构:
The Cancer Imaging Archive
创建时间:
2016-01-29
搜集汇总
数据集介绍
main_image_url
背景与挑战
背景概述
该数据集是癌症基因组图谱中肝细胞癌(TCGA-LIHC)的集合,旨在通过匹配临床影像与TCGA受试者,连接癌症表型和基因型以促进研究。数据分为两部分:临床、遗传和病理数据存储在Genomic Data Commons(GDC)数据门户,放射学数据存储在The Cancer Imaging Archive(TCIA),允许研究人员利用匹配的患者标识符探索组织基因型、放射学表型与患者结果之间的关联。数据集具有高度异质性,因为影像数据来自全球多个站点,涉及不同扫描仪模态、制造商和采集协议,且多为常规护理而非受控研究的一部分。
以上内容由遇见数据集搜集并总结生成
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作