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BREAST CANCER HISTOPATHOLOGY IMAGE ANALYSIS PIPELINE FOR TUMOR PURITY ESTIMATION.
Azimi, Vahid; Chang, Young Hwan; Thibault, Guillaume; Smith, Jaclyn; Tsujikawa, Takahiro; Kukull, Benjamin; Jensen, Bradden; Corless, Christopher; Margolin, Adam; Gray, Joe W.
Afiliação
  • Azimi V; Oregon Health and Science University (OHSU).
  • Chang YH; Oregon Health and Science University (OHSU).
  • Thibault G; Oregon Health and Science University (OHSU).
  • Smith J; Oregon Health and Science University (OHSU).
  • Tsujikawa T; Oregon Health and Science University (OHSU).
  • Kukull B; Oregon Health and Science University (OHSU).
  • Jensen B; Oregon Health and Science University (OHSU).
  • Corless C; Oregon Health and Science University (OHSU).
  • Margolin A; Oregon Health and Science University (OHSU).
  • Gray JW; Oregon Health and Science University (OHSU).
Proc IEEE Int Symp Biomed Imaging ; 2017: 1137-1140, 2017 Apr.
Article em En | MEDLINE | ID: mdl-30364881
ABSTRACT
The translation of genomic sequencing technology to the clinic has greatly advanced personalized medicine. However, the presence of normal cells in tumors is a confounding factor in genome sequence analysis. Tumor purity, or the percentage of cancerous cells in whole tissue section, is a correction factor that can be used to improve the clinical utility of genomic sequencing. Currently, tumor purity is estimated visually by expert pathologists; however, it has been shown that there exist vast inter-observer discrepancies in tumor purity scoring. In this paper, we propose a quantitative image analysis pipeline for tumor purity estimation and provide a systematic comparison between pathologists' scores and our image-based tumor purity estimation.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article