Comparing Methods for segmentation of Microcalcification Clusters in Digitized Mammograms
The appearance of microcalcifications in mammograms is one of the early signs of breast cancer. So, early detection of microcalcification clusters (MCCs) in mammograms can be helpful for cancer diagnosis and better treatment of breast cancer. In this paper a computer system devised to support a radiologist in detection MCCs in digital mammography has been proposed. First, to facilitate and improve detection step, the mammogram images have been enhanced with wavelet transformation and morphology operation. Then for segmentation of suspicious MCCs, two methods have been investigated. The considered methods are: adaptive threshold and Watershed segmentation. The purpose of this paper is to find out which segmentation method is more appropriate for extracting suspicious areas that contain MCCs in mammograms. Finally the MCCs detection areas in different algorithms will be compared.
Keywords: Mammograms, Microcalcification Clusters, Segmentation, Compare
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ABOUT THE AUTHORS
Hajar Moradmand
Department of Biomedical Radiation Engineering, Amirkabir University of Technology Tehran, Iran
Saeed Setayeshi
Department of Biomedical Radiation Engineering, Amirkabir University of Technology Tehran, Iran
Hossein Khazaei Targhi
Department of Electrical and Computer Engineering, Isfahan University of Technology Isfahan, Iran
Hajar Moradmand
Department of Biomedical Radiation Engineering, Amirkabir University of Technology Tehran, Iran
Saeed Setayeshi
Department of Biomedical Radiation Engineering, Amirkabir University of Technology Tehran, Iran
Hossein Khazaei Targhi
Department of Electrical and Computer Engineering, Isfahan University of Technology Isfahan, Iran
