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A fully automated scheme for mammographic segmentation and classification based on breast density and asymmetry
Authors:Tzikopoulos Stylianos D  Mavroforakis Michael E  Georgiou Harris V  Dimitropoulos Nikos  Theodoridis Sergios
Affiliation:a National and Kapodistrian University of Athens, Dept. of Informatics and Telecommunications, Panepistimiopolis, Ilissia, Athens 15784, Greece
b University of Houston, Department of Computer Science, 501 P.G. Hoffman Hall, Houston, TX 77204-3010, USA
c Delta Digital Imaging, Semitelou 6, Athens 11528, Greece
Abstract:This paper presents a fully automated segmentation and classification scheme for mammograms, based on breast density estimation and detection of asymmetry. First, image preprocessing and segmentation techniques are applied, including a breast boundary extraction algorithm and an improved version of a pectoral muscle segmentation scheme. Features for breast density categorization are extracted, including a new fractal dimension-related feature, and support vector machines (SVMs) are employed for classification, achieving accuracy of up to 85.7%. Most of these properties are used to extract a new set of statistical features for each breast; the differences among these feature values from the two images of each pair of mammograms are used to detect breast asymmetry, using an one-class SVM classifier, which resulted in a success rate of 84.47%. This composite methodology has been applied to the miniMIAS database, consisting of 322 (MLO) mammograms -including 15 asymmetric pairs of images-, obtained via a (noisy) digitization procedure. The results were evaluated by expert radiologists and are very promising, showing equal or higher success rates compared to other related works, despite the fact that some of them used only selected portions of this specific mammographic database. In contrast, our methodology is applied to the complete miniMIAS database and it exhibits the reliability that is normally required for clinical use in CAD systems.
Keywords:Automated mammogram segmentation   Breast boundary   Pectoral muscle   Breast density   Breast asymmetry   Nipple detection
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