title: A novel automatic suspicious mass regions identification using Havrda & Charvat entropy and Otsu's N thresholding.
abstract: Mass detection is a very important process for breast cancer diagnosis and computer aided systems. It can be very complex when the mass is small or invisible because of dense breast tissue. Therefore, the extraction of suspicious mass region can be very challenging. This paper proposes a novel segmentation algorithm to identify mass candidate regions in mammograms. The proposed system includes three parts: breast region and pectoral muscle segmentation, image enhancement and suspicious mass regions identification. The first two parts have been examined in previous studies. In this study, we focused on suspicious mass regions identification using a combination of Havrda & Charvat entropy method and Otsu's N thresholding method. An open access Mammographic Image Analysis Society (MIAS) database, which contains 59 masses, was used for the study. The proposed system obtained a 93% sensitivity rate for suspicious mass regions identification in 56 abnormal and 40 normal images.
authors.affiliation: School of Computer Engineering, Department of Medical Informatics, Trabzon, Turkey. Electronic address: burcinnkurt@gmail.com.
authors.forename: Burçin
authors.initials: B
authors.lastname: Kurt
authors.affiliation: Computer Engineering, Trabzon, Turkey. Electronic address: vasif@ktu.edu.tr.
authors.forename: Vasif V
authors.initials: VV
authors.lastname: Nabiyev
authors.affiliation: Medical Informatics Karadeniz Technical University, Trabzon, Turkey. Electronic address: kturhan.tr@gmail.com.
authors.forename: Kemal
authors.initials: K
authors.lastname: Turhan
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis*; D019277:Entropy; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D010369:Pectoralis Muscles / Q000000981:diagnostic imaging / Q000473:pathology; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Breast region segmentation; Havrda & Charvat entropy; Image enhancement; Otsu's N thresholding; Pectoral muscle segmentation; Suspicious mass regions identification