Technology and Health Care 22 (2014) 701–715 DOI 10.3233/THC-140841 IOS Press

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Segmentation for the enhancement of microcalcifications in digital mammograms Marina Milosevica,∗, Dragan Jankovicb and Aleksandar Peulica a Department

of Computer Engineering, Faculty of Technical Sciences, University of Kragujevac, Cacak, Serbia b Department of Computer Science, Faculty of Electronic Engineering, University of Nis, Nis, Serbia Received 5 June 2014 Accepted 25 June 2014 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. Keywords: Mammography, microcalcifications detection, Discrete Wavelet Transformation, Sobel operator, cross-validation

1. Introduction Mass noncommunicable diseases, such as cancer, are the leading cause of death worldwide. Breast cancer is the most common cancer among women in the world [1]. Breast cancer screening with mammography has been shown to be effective for preventing breast cancer death. Microcalcifications are an early sign of breast cancer. When a cancerous process in the breast is still at a very early stage, clusters of microcalcifications may appear as the only sign. Thus, the detection of microcalcification is a major part of diagnosis in early stage breast cancer. Microcalcifications are tiny calcium deposits in breast parenchymal tissue structures, which appear as small bright spots on mammograms [2]. Since microcalcifications are small and subtle abnormalities, they may be overlooked by an examining radiologist. Many missed radiologist diagnoses can be attributed to human factors such as subjective or varying decision criteria or distraction by other image features [3]. The effectiveness of the mammography ∗ Corresponding author: Marina Milosevic, Department of Computer Engineering, Faculty of Technical Sciences, University of Kragujevac, Svetog Save 65, 32000 Cacak, Serbia. E-mail: [email protected].

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Segmentation for the enhancement of microcalcifications in digital mammograms.

Microcalcification clusters appear as groups of small, bright particles with arbitrary shapes on mammographic images. They are the earliest sign of br...
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