Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
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 deriv …
Keywords
National Center for Biotechnology Information
NCBI
NLM
MEDLINE
humans
pubmed abstract
nih
national institutes of health
national library of medicine
research support
non-u.s. gov't
u.s. gov't
non-p.h.s.
N.I.H.
Extramural
computer-assisted / methods*
image interpretation
neoplasms / pathology*
pmid:29617659
pmc5943714
doi:10.1016/j.celrep.2018.03.086
joel saltz
rajarsi gupta
vésteinn thorsson
deep learning*
lymphocytes
tumor-infiltrating / metabolism
tumor-infiltrating / pathology*
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120348
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