Classification of benign and malignant masses in breast mammograms

Serifovic-Trbalic, A. and Trbalic, A. and Demirovic, D. and Prljaca, N. and Cattin, P. C.. (2014) Classification of benign and malignant masses in breast mammograms. In: 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2014 : 26 - 30 May 2014, Opatija, Croatia ; proceedings, Vol. 1. Piscataway, NJ, pp. 228-233.

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Official URL: http://edoc.unibas.ch/dok/A6348363

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An accurate and efficient computer-aided mammography diagnosis system plays an important role as a second opinion to assist radiologists. Finding an accurate and robust computer-aided diagnosis system for classification of the abnormalities in the mammograms as malignant or benign still remains a challenge in the digital mammography. In this paper, a fully autonomous classification system is presented and it consists of the three stages. The input Regions of Interest (ROIs) are obtained using an efficient Otsu's N thresholding and further subjected to a number of preprocessing stages. After preprocessing stage, from the ROIs, a group of 32 Zernike moments with different orders and iterations have been extracted. These moments have been applied to the neural network classifier. The experimental results show that the proposed algorithm is efficient comparing to the ground truth table given in the Mammography Image Analysis Society (MIAS) database.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedical Engineering > Imaging and Computational Modelling > Center for medical Image Analysis & Navigation (Cattin)
UniBasel Contributors:Cattin, Philippe Claude
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Note:Publication type according to Uni Basel Research Database: Conference paper
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Last Modified:04 Sep 2015 14:32
Deposited On:03 Jul 2015 08:53

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