TY - GEN
T1 - A computer aided system for breast cancer detection and diagnosis
AU - Al-Absi, Hamada R.H.
AU - Samir, Brahim Belhaouari
AU - Sulaiman, Suziah
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/7/30
Y1 - 2014/7/30
N2 - Breast cancer has become a significant health problem worldwide as it is considered one of the primary causes for deaths amongst females. In order to prevent the increase of deaths caused by breast cancer, early diagnosis through computer aided diagnosis systems has been very effective. This paper introduces a computer aided system for detecting and classifying suspicious regions in digital mammograms. The system starts by extracting regions of interest that are suspicious of containing cancerous cells. Then, all these regions are classified to check whether they are normal or abnormal. For the detection phase, template matching techniques are utilized. As for the classification phase, a 3-step process is applied which enclose feature extraction with wavelet transform, feature selection with statistical techniques and classification with clustering K-Nearest Neighbor classifier. A preliminary result shows a 97.73 % accuracy rate.
AB - Breast cancer has become a significant health problem worldwide as it is considered one of the primary causes for deaths amongst females. In order to prevent the increase of deaths caused by breast cancer, early diagnosis through computer aided diagnosis systems has been very effective. This paper introduces a computer aided system for detecting and classifying suspicious regions in digital mammograms. The system starts by extracting regions of interest that are suspicious of containing cancerous cells. Then, all these regions are classified to check whether they are normal or abnormal. For the detection phase, template matching techniques are utilized. As for the classification phase, a 3-step process is applied which enclose feature extraction with wavelet transform, feature selection with statistical techniques and classification with clustering K-Nearest Neighbor classifier. A preliminary result shows a 97.73 % accuracy rate.
KW - Breast cancer
KW - Classification
KW - Computer aided diagnosis
KW - Region of interest
UR - http://www.scopus.com/inward/record.url?scp=84938806065&partnerID=8YFLogxK
U2 - 10.1109/ICCOINS.2014.6868355
DO - 10.1109/ICCOINS.2014.6868355
M3 - Conference contribution
AN - SCOPUS:84938806065
T3 - 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings
BT - 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 International Conference on Computer and Information Sciences, ICCOINS 2014
Y2 - 3 June 2014 through 5 June 2014
ER -