<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Digital mammograms are a useful tool for breast cancer detection. The quality of digital mammogram image can have a negative effect on the computer-aided diagnosis system. We investigate the use of automatic image thresholding methods for microcalcification detection in mammographic images. Experimental results on the BI-RADS 4 images dataset confirm the proposed approach.</p>
</abstract>

Digital mammograms are a useful tool for breast cancer detection. The quality of digital mammogram image can have a negative effect on the computer-aided diagnosis system. We investigate the use of automatic image thresholding methods for microcalcification detection in mammographic images. Experimental results on the BI-RADS 4 images dataset confirm the proposed approach.

Evaluation of Binarization Algorithms in Preprocessing of Digital Mammographies

Dept. of Electronics, Telecommunications and Energetics

The Scientific Bulletin of Electrical Engineering Faculty

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Evaluation of Binarization Algorithms in Preprocessing of Digital Mammographies"}

Digital mammograms are a useful tool for breast cancer detection. The quality of digital mammogram image can have a negative effect on the computer-aided...

Evaluation of Binarization Algorithms in Preprocessing of Digital Mammographies

Published Online: Nov 02, 2016

Page range: -

DOI: https://doi.org/10.1515/sbeef-2016-0020

Keywords
digital mammogram, breast cancer detection, automatic image thresholding

© 2016 B. Tene et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Evaluation of Binarization Algorithms in Preprocessing of Digital Mammographies

Published Online: Nov 02, 2016

Page range: -

DOI: https://doi.org/10.1515/sbeef-2016-0020

Keywordsdigital mammogram, breast cancer detection, automatic image thresholding

© 2016 B. Tene et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
digital mammogram, breast cancer detection, automatic image thresholding