Title :
Adaptive speckle reduction filter for log-compressed B-scan images
Author :
Dutt, Vinayak ; Greenleaf, James F.
Author_Institution :
Ultrasound Res. Lab., Mayo Clinic, Rochester, MN, USA
fDate :
12/1/1996 12:00:00 AM
Abstract :
A good statistical model of speckle formation is useful for designing a good adaptive filter for speckle reduction In ultrasound B-scan images. Previously, statistical models have been used, but they failed to account for the log compression of the echo envelope employed by clinical ultrasound systems. Log-compression helps in reducing the dynamic range of the B-scan Images for display on a monitor as well as enhancing weak backscatters. In this article, statistics of log-compressed echo images, using the K-distribution statistical model for the echo envelope, are used to derive a parameter that can be used to quantify the extent of speckle formation. This speckle quantification can be used with an unsharp masking filter to adaptively reduce speckle. The effectiveness of the filter is demonstrated on images of contrast detail phantoms and on in-vivo abdominal images obtained by a clinical ultrasound system with log-compression
Keywords :
adaptive filters; adaptive signal processing; biomedical ultrasonics; medical image processing; speckle; K-distribution statistical model; adaptive filter; adaptive speckle reduction filter; clinical ultrasound system; contrast detail phantoms; echo envelope; filter effectiveness; in-vivo abdominal images; log-compressed B-scan images; medical diagnostic imaging; speckle formation; statistical model; unsharp masking filter; weak backscatters enhancement; Adaptive filters; Backscatter; Condition monitoring; Displays; Dynamic range; Image coding; Imaging phantoms; Speckle; Statistics; Ultrasonic imaging;
Journal_Title :
Medical Imaging, IEEE Transactions on