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titleDataset Citation

Saltz, J., Gupta, R., Hou, L., Kurc, T., Singh, P., Nguyen, V., … Thorsson, V. (2018). Tumor-Infiltrating Lymphocytes Maps from TCGA H&E Whole Slide Pathology Images [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/k9/tcia.2018.y75f9w1

Description

Mappings of tumor-infiltrating lymphocytes (TILs), based on H&E images from 13 TCGA tumor types are available here. These TIL maps are derived through computational staining, using a convolutional neural network trained to classify patches of images. In addition to the TIL Maps, the analysis codes and the software used to extract TILs are also available. The accompanying paper contains detailed information about our methods and our findings.

TCGA Tumor Types Used in this Study

BLCABladder urothelial carcinoma
BRCABreast invasive carcinoma
CESCCervical squamous cell carcinoma and endocervical adenocarcinoma
COADColon adenocarcinoma
LUADLung adenocarcinoma
LUSCLung squamous cell carcinoma
PAADPancreatic adenocarcinoma
PRADProstate adenocarcinoma
READRectum adenocarcinoma
SKCMSkin Cutaneous Melanoma
STADStomach adenocarcinoma
UCECUterine Corpus Endometrial Carcinoma
UVMUveal Melanoma


Info
titlePublication Citation

Saltz, J., Gupta, R., Hou, L., Kurc, T., Singh, P., Nguyen, V., . . . Thorsson, V. Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images. Cell Reports, 23(1), 181-193.e187. https://doi.org/10.1016/j.celrep.2018.03.086

 


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