원문정보
보안공학연구지원센터(IJSIP)
International Journal of Signal Processing, Image Processing and Pattern Recognition
Vol.8 No.3
2015.03
pp.87-96
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Early detection of cancer is the best method to increase the chances of survival. In early stage, cancer can be detected using mammography, fine needle aspirate, and surgical biopsy. In this study, we propose the use of Dual-Tree Complex Wavelet Transform (DTCWT) based feature with neural network classifier for mammography image analysis. The result is evaluated using specificity, sensitivity, and accuracy. Computational experiments show the proposed method is superior compare to DWT with 96.3% accuracy.
목차
Abstract
1. Introduction
2. Material and Method
2.1. Mammogram Database
2.2. Classification Framework
3. Result and Discussion
3.1. Result
3.2. Discussion
4. Conclusion
Acknowledgements
References
1. Introduction
2. Material and Method
2.1. Mammogram Database
2.2. Classification Framework
3. Result and Discussion
3.1. Result
3.2. Discussion
4. Conclusion
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보