Integrative analysis on histopathological image for identifying cellular heterogeneity

Young Hwan Chang; Guillaume Thibault; Brett Johnson; Adam Margolin; Joe W. Gray

doi:10.1117/12.2250428

1 March 2017 Integrative analysis on histopathological image for identifying cellular heterogeneity

Young Hwan Chang, Guillaume Thibault, Brett Johnson, Adam Margolin, Joe W. Gray

Author Affiliations +

Proceedings Volume 10140, Medical Imaging 2017: Digital Pathology; 101400T (2017) https://doi.org/10.1117/12.2250428
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

This study has brought together image processing, clustering and spatial pattern analysis to quantitatively analyze hematoxylin and eosin-stained (HE) 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 HE 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.

Citation Download Citation

Young Hwan Chang, Guillaume Thibault, Brett Johnson, Adam Margolin, and Joe W. Gray "Integrative analysis on histopathological image for identifying cellular heterogeneity", Proc. SPIE 10140, Medical Imaging 2017: Digital Pathology, 101400T (1 March 2017); https://doi.org/10.1117/12.2250428

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