title: Automatic cell segmentation and nuclear-to-cytoplasmic ratio analysis for third harmonic generated microscopy medical images.
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.
authors.affiliation: Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan. clee@mail.ncku.edu.tw
authors.forename: Gwo Giun
authors.initials: GG
authors.lastname: Lee
authors.forename: Huan-Hsiang
authors.initials: HH
authors.lastname: Lin
authors.forename: Ming-Rung
authors.initials: MR
authors.lastname: Tsai
authors.forename: Sin-Yo
authors.initials: SY
authors.lastname: Chou
authors.forename: Wen-Jeng
authors.initials: WJ
authors.lastname: Lee
authors.forename: Yi-Hua
authors.initials: YH
authors.lastname: Liao
authors.forename: Chi-Kuang
authors.initials: CK
authors.lastname: Sun
authors.forename: Chun-Fu
authors.initials: CF
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D001706:Biopsy; D002467:Cell Nucleus / Q000473:pathology*; D017076:Computer-Aided Design; D003593:Cytoplasm / Q000473:pathology*; D064368:Healthy Volunteers; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008853:Microscopy; D015999:Multivariate Analysis; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012878:Skin Neoplasms / Q000175:diagnosis