Integrative analysis on histopathological image for identifying cellular heterogeneity

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2017
Subtitle of host publicationDigital Pathology
PublisherSPIE
Volume10140
ISBN (Electronic)9781510607255
DOIs
StatePublished - 2017
EventMedical Imaging 2017: Digital Pathology - Orlando, United States
Duration: Feb 12 2017Feb 13 2017

Other

OtherMedical Imaging 2017: Digital Pathology
CountryUnited States
CityOrlando
Period2/12/172/13/17

Fingerprint

Spatial Analysis
Lymphocytes
Spatial distribution
Tumors
lymphocytes
Tissue
spatial distribution
Hematoxylin
tumors
Eosine Yellowish-(YS)
Infiltration
Cluster Analysis
Neoplasms
Image processing
infiltration
cells
complement
quantitative analysis
image processing
Chemical analysis

Keywords

  • H&E stained image
  • Heterogeneity
  • Spatial pattern analysis

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Integrative analysis on histopathological image for identifying cellular heterogeneity. / Chang, Young Hwan; Thibault, Guillaume; Johnson, Brett; Margolin, Adam; Gray, Joe.

Medical Imaging 2017: Digital Pathology. Vol. 10140 SPIE, 2017. 101400T.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chang, YH, Thibault, G, Johnson, B, Margolin, A & Gray, J 2017, Integrative analysis on histopathological image for identifying cellular heterogeneity. in Medical Imaging 2017: Digital Pathology. vol. 10140, 101400T, SPIE, Medical Imaging 2017: Digital Pathology, Orlando, United States, 2/12/17. https://doi.org/10.1117/12.2250428
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