The Use of Dual-Tree Complex Wavelet Transform (DTCWT) Based Feature for Mammogram Classification
Lowis, Hendra Hendra, Lavinia · International Journal of Signal Processing Image Processing and Pattern Recognition · 2015
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.