A hope for a cheap and reliable automatic diagnostic system for breast cancer

This work expands the limit of the currently used clinical ultrasonography by employing a quantitative tissue breast characterization method that assists the radiologist by extracting structural tissue information not seen on the B-scan image under examination. A novel decomposition of the radio frequency (RF) ultrasound signal into its coherent and diffused components is proposed. This decomposition is based on thresholding the energy of the wavelet transform of the RF signal. The two components are modeled separately and the model parameters are estimated. The proposed algorithm is used to estimate structural parameters of the breast tissue such as the number and energy of coherent scatterers and the energy of the diffuse scatterers. Based on these individual parameters breast tissue characterization is performed. Individual estimated parameters are able to differentiate reliably between normal and abnormal tissue (area under the ROC curve A_z>0.93). Also, the differentiation between malignant and benign tissue is possible (A_z>0.89)