Abstract
A novel speckle suppression method for medical ultrasound images is presented. First, the logarithmic transform of the original image is analyzed into the multiscale wavelet domain. We show that the subband decompositions of ultrasound-images have significantly non-Gaussian statistics that are best described by families of heavy-tailed distributions such as the alpha-stable. Then, we design a Bayesian estimator that exploits these statistics. We use the alpha-stable model to develop a blind noise-removal processor that performs a nonlinear operation on the data. Finally, we compare our technique with current state-of-the-art soft and hard thresholding methods applied on actual ultrasound medical images and we quantify the achieved performance improvement.
Original language | English (US) |
---|---|
Pages (from-to) | 772-783 |
Number of pages | 12 |
Journal | IEEE transactions on medical imaging |
Volume | 20 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2001 |
Externally published | Yes |
Keywords
- Alpha-stable distributions
- Bayesian estimation
- Ultrasound speckle
- Wavelet decomposition
ASJC Scopus subject areas
- Software
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering