Real-Time Speckle and Impulsive Noise Suppression in 3-D Ultrasound Imaging

Abstract

Ultrasound imaging is considered one of the most powerful techniques for medical diagnosis and is often preferred over other medical imaging modalities because of noninvasive, portable, versatile and low-cost properties (Webb, 2002; Abd-Elmoniem, 2002; Porter, 2001; Shekhar, 2002). A fundamental problem in the field of ultrasound imaging is the speckle noise influence, which is a major limitation on image quality in ultrasound imaging. Imaging speckle is a phenomenon that occurs when a coherent source and a noncoherent detector are used to interrogate a medium, which is rough on the scale of the wavelength. Speckle noise occurs especially in images of the liver and kidney whose underlying structures are too small to be resolved using long ultrasound wavelength. The presence of speckle noise affects the human interpretation of the images as well the accuracy of computer-assisted diagnostic techniques (Nikolaidis, 2000; Kim & Park, 2001) The goal of this chapter is the capability and real-time processing features of the robust MML (Median M-type L) filters to remove speckle and impulsive noise in 3-D ultrasound images (Gallegos-Funes et al., 2008, Varela-Benitez et al., 2007). The Texas Instruments DSP TMS320C6711 is used to implement the algorithms (Texas Instruments, 1998; Kehtarnavaz, 2001). Based on the processing time values of each a 3-D filter, different configurations of sweeping cubes (voxels) are used to obtain a balance between the processing time and quality of the restoration of 3-D images (Nikolaidis, 2000). The criteria used to measure the performance of filters are: the peak signal-to-noise ratio (PSNR) to characterize the noise suppression, and the mean absolute error (MAE) to evaluate the preservation of edges and fine details (Bovik, 2000; Astola & Kuosmanen, 1997; Kotropoulos & Pitas, 2001; Pitas & Venetsanopoulos, 1990). Extensive simulation results have demonstrated that the proposed filters can consistently outperform other filters used as comparative by balancing the tradeoff between noise suppression, detail preservation, and processing time.