DocumentCode :
3252548
Title :
Wavelet based adaptive Bayesian despeckling for medical ultrasound images
Author :
Talukdar, A.K. ; Deka, B. ; Bora, P.K.
Author_Institution :
Dept. of Electron. & Commun. Eng., Tezpur Univ., Tezpur, India
fYear :
2009
fDate :
23-26 Jan. 2009
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a new wavelet domain adaptive despeckling technique for contrast enhancement of medical ultrasound (US) images for improving the clinical diagnosis. This method uses the Rayleigh distribution for modeling the speckle wavelet coefficients and the signal wavelet coefficients are approximated using the Gaussian distribution. Combining these as statistical priors, we have developed a context modeling based adaptive Bayesian shrinkage estimator for processing the wavelet coefficients of detail subbands. The experimental results using real ultrasound images demonstrate the superiority of the proposed technique both quantitatively and qualitatively as compared to other competitive schemes reported in the ultrasound image denoising literature.
Keywords :
Bayes methods; Gaussian distribution; biomedical ultrasonics; image denoising; medical image processing; ultrasonic imaging; wavelet transforms; Bayesian shrinkage estimator; Gaussian distribution; Rayleigh distribution; clinical diagnosis; contrast enhancement; image denoising; medical ultrasound images; wavelet based adaptive Bayesian despeckling; Bayesian methods; Biomedical imaging; Clinical diagnosis; Context modeling; Gaussian distribution; Medical diagnostic imaging; Speckle; Ultrasonic imaging; Wavelet coefficients; Wavelet domain; Bayesian shrinkage; Rayleigh distribution; adaptive; context modeing; despeckling; ultrasound;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2009 - 2009 IEEE Region 10 Conference
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-4546-2
Electronic_ISBN :
978-1-4244-4547-9
Type :
conf
DOI :
10.1109/TENCON.2009.5395875
Filename :
5395875
Link To Document :
بازگشت