Title :
Speckle Suppression in Medical Ultrasound Images Using Two Dimensional GARCH Model
Author :
Amirmazlaghani, Maryam ; Amindavar, Hamidreza
Author_Institution :
Amirkabir Univ. of Technol., Tehran
Abstract :
In this paper, we introduce a novel speckle suppression method for medical ultrasound images, based on statistical model of wavelet coefficients. We use two-dimensional generalized autoregressive conditional heteroscedasticity (GARCH) model for statistical modeling of images wavelet coefficients. By using two-dimensional GARCH model on the wavelet coefficients, we are capable of taking into account important characteristics of wavelet coefficients, such as non-stationarity, heavy tailed marginal distribution, and the dependencies between the coefficients. Furthermore, we use minimum mean square error (MMSE) estimator for estimating the clean image wavelet coefficients. Here, to prove the performance of this method in speckle suppression, we have compared our proposed method with various speckle suppression methods applied on actual ultrasound medical images and we verify the performance improvement in utilizing the new strategy.
Keywords :
autoregressive processes; biomedical ultrasonics; least mean squares methods; medical image processing; statistical analysis; ultrasonic imaging; wavelet transforms; medical ultrasound images; minimum mean square error; speckle suppression; statistical modeling; two dimensional GARCH model; two-dimensional generalized autoregressive conditional modelheteroscedasticity; wavelet coefficients; Biomedical imaging; Mean square error methods; Medical diagnostic imaging; Noise reduction; Speckle; Stochastic processes; Ultrasonic imaging; Wavelet coefficients; Wavelet transforms; Wiener filter;
Conference_Titel :
Communications, Computers and Signal Processing, 2007. PacRim 2007. IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4244-1189-4
Electronic_ISBN :
1-4244-1190-4
DOI :
10.1109/PACRIM.2007.4313304