Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Saltz, Joel; Gupta, Rajarsi; Hou, Le; Kurç, Tahsin; K. Singh, Pankaj; Nguyen, Vu; Samaras, Dimitris; R. Shroyer, Kenneth; Zhao, Tianhao; Batiste, Rebecca; Van Arnam, John; Johnson, Rory; A. Demchok, John; Felau, Ina; Kasapi, Melpomeni; L. Ferguson, Martin; M. Hutter, Carolyn; J. Sofia, Heidi; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; C. Zenklusen, Jean; Zhang, Jiashan; Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; Defreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; I. Heiman, David; Kim, Jaegil; S. Lawrence, Michael; Lin, Pei; Meier, Sam; S. Noble, Michael; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; M. Reynolds, Sheila; Shmulevich, Ilya; Thórsson, Vésteinn; Thorsson, Vésteinn; Zhang, Wei; Akbani, Rehan; M. Broom, Bradley; M. Hegde, Apurva; Ju, Zhenlin; S. 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doi:10.1016/j.celrep.2018.03.086

Public

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Published in Cell Reports • Apr 1, 2018

Authors:

Joel Saltz

Rajarsi Gupta

Le Hou

Abstract

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived throu...

Subject

Convolutional neural network

Tumor-infiltrating lymphocytes

Biology

Research Assistant

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