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In this paper a method for detection of microcalcifications (MCCs), which appear at the beginning stages of breast cancer, is presented by using mathematical morphology. This method consists of four steps. At the first step the contrast of suspicious regions on the image is enhanced by contrast stretching. In the next step a morphological filtering process is applied by using six different structured elements (SEs). At the same step substruction image is obtained by substructing the filtered image from the original image. In the next step a black and white image is generated from this substraction image by applying a threshold, which is calculated by using histogam. Finally, healthy regions are classified by refiltering black and white image using morphological opening. The proposed method was tested on 17 mammograms and 82.2% success rate was observed.
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Computer Engineering Department, Faculty of Engineering & Architecture, Anadolu University, 26470, Eskisehir, Turkey
Özgür Özsen
- Özgür Özsen
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KES International, 2nd Floor, 145-157 St John Street, EC1V 4PY, London, United Kingdom
Mircea Gh. Negoita
Centre for SMART systems Engineering Research Centre, University of Brighton, BN2 4GJ, Moulsecoomb, Brighton, UK
Robert J. Howlett
School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia
Lakhmi C. Jain
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© 2004 Springer-Verlag Berlin Heidelberg
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Özsen, Ö. (2004). Early Detection of Breast Cancer Using Mathematical Morphology. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_81
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