Improving the contrast of breast cancer masses in ultrasound using an autoregressive model based filter.
The assessment and diagnosis of breast cancer with ultrasound is a challenging problem due to the low contrast between cancer masses and benign tissue. Due to this low contrast it has proven to be difficult to achieve reliable segmentation results on breast cancer masses. An autoregressive model has been employed to filter out of the backscattered RF-signal from a tissue harmonic image which is not degraded by harmonic leakage. Measurements on the filtered image have shown a significant (up to 45%) increase in contrast between cancer masses and benign tissue.
Department of Engineering Science, University of Oxford, UK.
Etienne
E
von Lavante
J Alison
JA
Noble
D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D016217:Ultrasonography, Mammary / Q000379:methods*