ABSTRACT
Diagnostic usage for ultrasound has greatly expanded over the past couple of decades because its advantages over low cost and non-invasive nature. Ultrasound, however, suffers from an inherent imaging artifact called speckle. A speckle depends up on the ultrasound system’s resolution limit. The ability of diagnosing ultrasound images to detect low contrast lesions is fundamentally limited by speckles. Speckle is a granular pattern formed due to constructive and destructive coherent interferences of backscattered signals due to unresolved tissue in-homogeneity. Because of its dependence on the microstructure of the tissue parenchyma, speckle is often used in diagnosis such as focal and diffuse liver diseases. So, handling speckles in ultrasound images is a critical task in medical image processing.
After removing speckles present in ultrasound images, depending up on the user needs, the image is passed into either Image registration for growth monitoring of pathology changes in liver or Feature extraction for classification & retrieval. This Chapter discusses about the importance of Speckles in medical images, different types of filter and Metrics for speckle reduction. Several non linear diffusion filtering methods are explained thoroughly.
