Breast cancer diagnosis based on ultrasound RF echo modeling and physician's level of confidence

Abstract

A number of researchers have shown that the ultrasound RF echo from tissue exhibits (1/f ) /sup /spl beta// characteristics and developed tissue characterization methods based on the fractal parameter of the received signal. In this paper a new model for the received ultrasound RF data has been proposed, namely the fractional differencing auto regressive moving-average (FARMA) model, whose parameters were investigated for their ability to differentiate between benign and malignant tumors. Along with the FARMA model parameters, the patient's age and the radiologist's pre-biopsy level of suspicion (LOS) were used as additional features to increase the characterization performance. 120 in vivo B-scan images obtained from 90 patients were used during the modeling and estimation procedures. The area under the receiver operator characteristics (ROC) curve yields a value of 0.8723, with a confidence interval of [0.8512, 0.8945], at a significance level of 0.05. These results indicate that the proposed tissue characterization method can be used as a second opinion to aid the radiologist decision criteria.