Enhancement of Medical Ultrasound Images Using Multiscale Discrete Shearlet Transform Based Thresholding

Abstract

Feature preserved enhancement is of great interest in medical ultrasound images. Speckle is a main factor which affects the quality, contrast resolution and most importantly texture information present in ultrasound images and can make the post-processing difficult. This paper presents a new enhancement approach which is based on discrete shearlet transform (DST) and thresholding scheme. The DST, a new efficient multiscale geometric representation with the different features of anisotropy, localization, directionality and multiscale, is employed to provide effective representation of the noisy coefficients. Thresholding schemes are applied to the noisy DST coefficients to improve the denoising efficiency and preserve the edge features effectively with this consideration that blurring associated with speckle reduction should be less and fine details are enhanced/preserved properly for the visual enhancement of ultrasound images. The presented algorithm also helps to improve the visual quality of the ultrasound images. Experimental results demonstrate the ability of proposed method for noise suppression, feature and edge preservation defined in terms of different performance measures.