@inproceedings{f218e7c7ba0341ae8452bc1fb5885692,
title = "Integrative analysis on histopathological image for identifying cellular heterogeneity",
abstract = "This study has brought together image processing, clustering and spatial pattern analysis to quantitatively analyze hematoxylin and eosin-stained (H&E) tissue sections. A mixture of tumor and normal cells (intratumoral heterogeneity) as well as complex tissue architectures of most samples complicate the interpretation of their cytological profiles. To address these challenges, we develop a simple but effective methodology for quantitative analysis for H&E section. We adopt comparative analyses of spatial point patterns to characterize spatial distribution of different nuclei types and complement cellular characteristics analysis. We demonstrate that tumor and normal cell regions exhibit significant differences of lymphocytes spatial distribution or lymphocyte infiltration pattern.",
keywords = "H&E stained image, Heterogeneity, Spatial pattern analysis",
author = "Chang, {Young Hwan} and Guillaume Thibault and Brett Johnson and Adam Margolin and Gray, {Joe W.}",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; Medical Imaging 2017: Digital Pathology ; Conference date: 12-02-2017 Through 13-02-2017",
year = "2017",
doi = "10.1117/12.2250428",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Gurcan, {Metin N.} and Tomaszewski, {John E.}",
booktitle = "Medical Imaging 2017",
}