Automatic cell segmentation and nuclear-to-cytoplasmic ratio analysis for third harmonic generated microscopy medical images

Gwo-Giun Lee, Huan Hsiang Lin, Ming Rung Tsai, Sin Yo Chou, Wen Jeng Lee, Yi Hua Liao, Chi Kuang Sun, Chun Fu Chen

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Traditional biopsy procedures require invasive tissue removal from a living subject, followed by time-consuming and complicated processes, so noninvasive in vivo virtual biopsy, which possesses the ability to obtain exhaustive tissue images without removing tissues, is highly desired. Some sets of in vivo virtual biopsy images provided by healthy volunteers were processed by the proposed cell segmentation approach, which is based on the watershed-based approach and the concept of convergence index filter for automatic cell segmentation. Experimental results suggest that the proposed algorithm not only reveals high accuracy for cell segmentation but also has dramatic potential for noninvasive analysis of cell nuclear-to-cytoplasmic ratio (NC ratio), which is important in identifying or detecting early symptoms of diseases with abnormal NC ratios, such as skin cancers during clinical diagnosis via medical imaging analysis.

Original languageEnglish
Article number6509989
Pages (from-to)158-168
Number of pages11
JournalIEEE Transactions on Biomedical Circuits and Systems
Volume7
Issue number2
DOIs
Publication statusPublished - 2013 May 7

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Biomedical Engineering

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