Speckle reduction in ultrasonic images through a maximum likelihood based adaptive filter.
Speckle poses serious problems in the interpretation of ultrasound images. It reduces contrast and resolution, making it difficult to identify the presence of abnormalities in B mode images. Using a recently proposed compound probability density function (pdf) for the statistics of the backscattered ultrasonic signals, an adaptive filter for speckle reduction is implemented and tested on B mode images of a tissue mimicking phantom. Results suggest that the adaptive filter based on a maximum likelihood approach improves the ability to classify targets in images while retaining the details in the original unprocessed image.
Shankar
P M
PM
Department of Electrical and Computer Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA. pshankar@coe.drexel.edu
D000465:Algorithms; D002138:Calibration; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016013:Likelihood Functions; D015233:Models, Statistical; D011336:Probability; D012542:Scattering, Radiation; D012815:Signal Processing, Computer-Assisted; D014465:Ultrasonics; D014463:Ultrasonography / Q000379:methods*