title: Computer-aided diagnosis for distinguishing between triple-negative breast cancer and fibroadenomas based on ultrasound texture features.
abstract: OBJECTIVE
  Triple-negative breast cancer (TNBC), an aggressive subtype, is frequently misclassified as fibroadenoma due to benign morphologic features on breast ultrasound (US). This study aims to develop a computer-aided diagnosis (CAD) system based on texture features for distinguishing between TNBC and benign fibroadenomas in US images.
  
  
  METHODS
  US images of 169 pathology-proven tumors (mean size, 1.65 cm; range, 0.7-3.0 cm) composed of 84 benign fibroadenomas and 85 TNBC tumors are used in this study. After a tumor is segmented out using the level-set method, morphological, conventional texture, and multiresolution gray-scale invariant texture feature sets are computed using a best-fitting ellipse, gray-level co-occurrence matrices, and the ranklet transform, respectively. The linear support vector machine with leave-one-out cross-validation schema is used as a classifier, and the diagnostic performance is assessed with receiver operating characteristic curve analysis.
  
  
  RESULTS
  The Az values of the morphology, conventional texture, and multiresolution gray-scale invariant texture feature sets are 0.8470 [95% confidence intervals (CIs), 0.7826-0.8973], 0.8542 (95% CI, 0.7911-0.9030), and 0.9695 (95% CI, 0.9376-0.9865), respectively. The Az of the CAD system based on the combined feature sets is 0.9702 (95% CI, 0.9334-0.9882).
  
  
  CONCLUSIONS
  The CAD system based on texture features extracted via the ranklet transform may be useful for improving the ability to discriminate between TNBC and benign fibroadenomas.
authors.affiliation: Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, Seoul 110-744, South Korea.
authors.forename: Woo Kyung
authors.initials: WK
authors.lastname: Moon
authors.affiliation: Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan, Republic of China.
authors.forename: Yao-Sian
authors.initials: YS
authors.lastname: Huang
authors.affiliation: Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan, Republic of China.
authors.forename: Chung-Ming
authors.initials: CM
authors.lastname: Lo
authors.affiliation: Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei 10041, Taiwan, Republic of China and Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan, Republic of China.
authors.forename: Chiun-Sheng
authors.initials: CS
authors.lastname: Huang
authors.affiliation: Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, Seoul 110-744, South Korea.
authors.forename: Min Sun
authors.initials: MS
authors.lastname: Bae
authors.affiliation: Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, Seoul 110-744, South Korea.
authors.forename: Won Hwa
authors.initials: WH
authors.lastname: Kim
authors.affiliation: Center for Functional Onco-Imaging and Department of Radiological Science, University of California, Irvine, California 92868 and Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung 82445, Taiwan, Republic of China.
authors.forename: Jeon-Hor
authors.initials: JH
authors.lastname: Chen
authors.affiliation: Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan, Republic of China and Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan, Republic of China.
authors.forename: Ruey-Feng
authors.initials: RF
authors.lastname: Chang
mesh_terms: D000328:Adult; D000368:Aged; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D005260:Female; D018226:Fibroadenoma / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008875:Middle Aged; D060388:Support Vector Machine; D064726:Triple Negative Breast Neoplasms / Q000000981:diagnostic imaging*; D014463:Ultrasonography