title: Computer-aided US diagnosis of breast lesions by using cell-based contour grouping.
abstract: OBJECTIVE
  To develop a computer-aided diagnostic algorithm with automatic boundary delineation for differential diagnosis of benign and malignant breast lesions at ultrasonography (US) and investigate the effect of boundary quality on the performance of a computer-aided diagnostic algorithm.
  
  
  METHODS
  This was an institutional review board-approved retrospective study with waiver of informed consent. A cell-based contour grouping (CBCG) segmentation algorithm was used to delineate the lesion boundaries automatically. Seven morphologic features were extracted. The classifier was a logistic regression function. Five hundred twenty breast US scans were obtained from 520 subjects (age range, 15-89 years), including 275 benign (mean size, 15 mm; range, 5-35 mm) and 245 malignant (mean size, 18 mm; range, 8-29 mm) lesions. The newly developed computer-aided diagnostic algorithm was evaluated on the basis of boundary quality and differentiation performance. The segmentation algorithms and features in two conventional computer-aided diagnostic algorithms were used for comparative study.
  
  
  RESULTS
  The CBCG-generated boundaries were shown to be comparable with the manually delineated boundaries. The area under the receiver operating characteristic curve (AUC) and differentiation accuracy were 0.968 +/- 0.010 and 93.1% +/- 0.7, respectively, for all 520 breast lesions. At the 5% significance level, the newly developed algorithm was shown to be superior to the use of the boundaries and features of the two conventional computer-aided diagnostic algorithms in terms of AUC (0.974 +/- 0.007 versus 0.890 +/- 0.008 and 0.788 +/- 0.024, respectively).
  
  
  CONCLUSIONS
  The newly developed computer-aided diagnostic algorithm that used a CBCG segmentation method to measure boundaries achieved a high differentiation performance.
authors.affiliation: Institute of Biomedical Engineering, College of Medicine, and College of Engineering, National Taiwan University, #1, Sec. 1, Jen-Ai Road, Taipei 100, Taiwan.
authors.forename: Jie-Zhi
authors.initials: JZ
authors.lastname: Cheng
authors.forename: Yi-Hong
authors.initials: YH
authors.lastname: Chou
authors.forename: Chiun-Sheng
authors.initials: CS
authors.lastname: Huang
authors.forename: Yeun-Chung
authors.initials: YC
authors.lastname: Chang
authors.forename: Chui-Mei
authors.initials: CM
authors.lastname: Tiu
authors.forename: Kuei-Wu
authors.initials: KW
authors.lastname: Chen
authors.forename: Chung-Ming
authors.initials: CM
authors.lastname: Chen
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001941:Breast Diseases / Q000000981:diagnostic imaging* / Q000473:pathology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D012372:ROC Curve; D012189:Retrospective Studies; D016217:Ultrasonography, Mammary