1 March 2017 Integrative analysis on histopathological image for identifying cellular heterogeneity
Author Affiliations +
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.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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); doi: 10.1117/12.2250428; https://doi.org/10.1117/12.2250428


Texture-based CT Image analysis of asthma
Proceedings of SPIE (March 28 2013)
Segmentation methods in image cytometry
Proceedings of SPIE (April 30 1990)
Digital Image Analysis Of Cervical Biopsies
Proceedings of SPIE (May 24 1989)
Microscopic image analysis in GDR
Proceedings of SPIE (October 31 1990)

Back to Top