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Role of Filters in Speckle Reduction in Medical Ultrasound Images- A Comparative Study

To diagnose and predict complex disorders in human body, various Medical Imaging Techniques are used. Widely accepted technique among them is the Ultrasound imaging modality, because of its low cost and noninvasive nature. But the images produced by ultrasound scanning are of low quality and amenable to faster degradation due to the presence of speckle noise. This led to various studies for effectively removing speckle noise from ultrasound images. In this paper, an endeavor is made for a comparative analysis of chosen set of post filtering methods for Speckle reduction, VIZ Anisotropic Diffusion, Wavelet, Adaptive Median Filter, Hybrid Algorithm, Modified Fourier Transform and Sparse Code Shrinkage using ICA. The different methods are tested on a collection of ultrasound images and their performance evaluated with the Normalized Cross Correlation metric (NCC), Peak Signal to Noise Ratio (PSNR), Structural Content (SC), Universal Quality Index (UQI), Edge Preservation Index (EPI) and Structural Similarity Index (SSI). Further relative execution time of different approaches are also analyzed. On analysis of the values of different metrics and execution time, Wavelet Based Hybrid Thresholding is found to outperform the other filters considered.