Title: Medical feature based qualitative evaluation of denoising techniques for ultrasound liver images
Authors: Vibhakar Shrimali, R.S. Anand, Vinod Kumar, R.K. Srivastav
Addresses: Biomedical Research Group, Department of Electrical Engineering, Indian Institute of Technology, Roorkee-(Uttarakhand)-247667, India. ' Biomedical Research Group, Department of Electrical Engineering, Indian Institute of Technology, Roorkee-(Uttarakhand)-247667, India. ' Biomedical Research Group, Department of Electrical Engineering, Indian Institute of Technology, Roorkee-(Uttarakhand)-247667, India. ' Himalayan Institute of Medical Sciences, Swami Rama Nagar, P.O. Doiwala, Dehradun-(Uttarakhand)-248140, India
Abstract: This paper presents a qualitative evaluation of three fundamentally different filtering algorithms for the improvement of low Signal-to-Noise Ratio (SNR), inherent in ultrasound liver images. The implemented and assessed algorithms include Adaptive Weighted Median Filter (AWMF), Aggressive Region Growing Filter (ARGF) and the Wavelet Domain Filter. The evaluation has been performed to help the radiologists to analyse the diffused liver disease images in a better way, and to differentiate a simple liver cyst from the complicated ones. The evaluation parameters for assessing the quality of the denoised images have been selected in consultation with a group of radiologists. The processed images were then assessed, on the basis of these selected parameters by another group of radiologists. A multi-point rank order method has been used to identify small differences or trends in observation. In the present observations, ARGF performed better than the other implemented filters.
Keywords: denoising; thresholding; ultrasound images; speckle; wavelet filter; aggressive region growing filter; adaptive weighted median filter; medical features; medical imaging; liver images; liver cysts.
DOI: 10.1504/IJSISE.2008.020920
International Journal of Signal and Imaging Systems Engineering, 2008 Vol.1 No.2, pp.135 - 144
Published online: 24 Oct 2008 *
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