“A Logarithmic Threshold Contourlet Based Method for Speckle Noise Reduction of Medical Ultrasound Images”

Medical practitioners are increasingly using digital images during disease diagnosis several stateof-the-art medical equipments are producing images of different organs, which are used during various stages of analysis. Examples of such devices include MRI, CT, ultrasound and X-Ray. In medical image processing, image denoising has become a very essential exercise all through the diagnose because Ultrasound images are normally affected by speckle noise. The noise in the image has two disadvantages, the first being the degradation of the image quality and the second, more important, obscures important information required for accurate diagnosis. Arbitration between the perpetuation of useful diagnostic information and noise suppression must be treasured in medical images. In general we rely on the intervention of a proficient to control the quality of processed images. In certain cases, for instance in Ultrasound images, the noise can restrain information which is valuable for the general practitioner. Consequently medical images are very inconsistent, and it is crucial to operate case to case. This paper presents a waveletbased thresholding scheme for noise suppression in Ultrasound images and provides the knowledge about adaptive and anisotropic diffusion techniques for speckle noise removal from different types of images like Ultrasound. One of the inherent properties of coherent imaging is the presence of speckle noise. This noise impacts valuable properties and important information of the image and it is difficult to remove or efficiently reduce it. The tradeoff between noise reducing and holding image information should be such that image recognition process would be done properly. For this purpose, many methods have been presented. The most appropriate of which are the wavelet transform and directional contourlet transform. In this paper, a suitable algorithm based on contourlet transform, with logarithmic threshold is presented. The obtained results by applying the proposed method on real image are better than those of using other algorithms. We use the signal to noise ratio as a measure of visual quality of resulted images Ultrasound method is one of the best imaging methods for soft tissues of body, because it is portable, no ionic radiation is used and it is relatively cheap, but the main disadvantage of images taken by this method is the low quality of images that is in turn due to the presence of a multiplicative noise. KeywordsSpeckle Noise, Ultrasound Images, Noise Filters, MATLAB.