title: A computer-aided diagnosis system for dynamic contrast-enhanced MR images based on level set segmentation and ReliefF feature selection.
abstract: This study established a fully automated computer-aided diagnosis (CAD) system for the classification of malignant and benign masses via breast magnetic resonance imaging (BMRI). A breast segmentation method consisting of a preprocessing step to identify the air-breast interfacing boundary and curve fitting for chest wall line (CWL) segmentation was included in the proposed CAD system. The Chan-Vese (CV) model level set (LS) segmentation method was adopted to segment breast mass and demonstrated sufficiently good segmentation performance. The support vector machine (SVM) classifier with ReliefF feature selection was used to merge the extracted morphological and texture features into a classification score. The accuracy, sensitivity, and specificity measurements for the leave-half-case-out resampling method were 92.3%, 98.2%, and 76.2%, respectively. For the leave-one-case-out resampling method, the measurements were 90.0%, 98.7%, and 73.8%, respectively.
authors: School of Physics and Engineering, Sun Yat-sen University, Guangzhou 510275, China.
authors: Zhiyong
authors: 0000-0003-3608-291X
authors: Z
authors: Pang
authors: School of Physics and Engineering, Sun Yat-sen University, Guangzhou 510275, China.
authors: Dongmei
authors: D
authors: Zhu
authors: School of Physics and Engineering, Sun Yat-sen University, Guangzhou 510275, China.
authors: Dihu
authors: 0000-0001-5432-8149
authors: D
authors: Chen
authors: Imaging Diagnosis and Interventional Center, Cancer Center, The Sun Yat-sen University, Guangzhou 510060, China.
authors: Li
authors: L
authors: Li
authors: School of Physics and Engineering, Sun Yat-sen University, Guangzhou 510275, China.
authors: Yuanzhi
authors: 0000-0002-1606-4055
authors: Y
authors: Shao
mesh_terms: D000328:Adult; D000368:Aged; D000388:Air; D000465:Algorithms; D001940:Breast / Q000473:pathology; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D003287:Contrast Media / Q000737:chemistry*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D060388:Support Vector Machine
chemical_list: D003287:Contrast Media
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