title: Segmentation for the enhancement of microcalcifications in digital mammograms.
abstract: Microcalcification clusters appear as groups of small, bright particles with arbitrary shapes on mammographic images. They are the earliest sign of breast carcinomas and their detection is the key for improving breast cancer prognosis. But due to the low contrast of microcalcifications and same properties as noise, it is difficult to detect microcalcification. This work is devoted to developing a system for the detection of microcalcification in digital mammograms. After removing noise from mammogram using the Discrete Wavelet Transformation (DWT), we first selected the region of interest (ROI) in order to demarcate the breast region on a mammogram. Segmenting region of interest represents one of the most important stages of mammogram processing procedure. The proposed segmentation method is based on a filtering using the Sobel filter. This process will identify the significant pixels, that belong to edges of microcalcifications. Microcalcifications were detected by increasing the contrast of the images obtained by applying Sobel operator. In order to confirm the effectiveness of this microcalcification segmentation method, the Support Vector Machine (SVM) and k-Nearest Neighborhood (k-NN) algorithm are employed for the classification task using cross-validation technique.
authors: Department of Computer Engineering, Faculty of Technical Sciences, University of Kragujevac, Cacak, Serbia.
authors: Marina
authors: M
authors: Milosevic
authors: Department of Computer Science, Faculty of Electronic Engineering, University of Nis, Nis, Serbia.
authors: Dragan
authors: D
authors: Jankovic
authors: Department of Computer Engineering, Faculty of Technical Sciences, University of Kragujevac, Cacak, Serbia.
authors: Aleksandar
authors: A
authors: Peulic
mesh_terms: D000465:Algorithms; D001941:Breast Diseases / Q000175:diagnosis*; D001943:Breast Neoplasms / Q000175:diagnosis; D002114:Calcinosis / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D058067:Wavelet Analysis
keywords: Discrete Wavelet Transformation; Mammography; Sobel operator; cross-validation; microcalcifications detection