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http://dx.doi.org/10.7742/jksr.2021.15.1.21

Median Modified Wiener Filter for Noise Reduction in Computed Tomographic Image using Simulated Male Adult Human Phantom  

Ju, Sunguk (Department of Radiologist Science, College of Health Science, Gachon University)
An, Byungheon (Department of Radiologist Science, College of Health Science, Gachon University)
Kang, Seong-Hyeon (Department of Radiologist Science, College of Health Science, Gachon University)
Lee, Youngjin (Department of Radiologist Science, College of Health Science, Gachon University)
Publication Information
Journal of the Korean Society of Radiology / v.15, no.1, 2021 , pp. 21-28 More about this Journal
Abstract
Computed tomography (CT) has the problem of having more radiation exposure compared to other radiographic apparatus. There is a low-dose imaging technique for reducing exposure, but it has a disadvantage of increasing noise in the image. To compensate for this, various noise reduction algorithms have been developed that improve image quality while reducing the exposure dose of patients, of which the median modified Wiener filter (MMWF) algorithm that can be effectively applied to CT devices with excellent time resolution has been presented. The purpose of this study is to optimize the mask size of MMWF algorithm and to see the excellence of noise reduction of MMWF algorithm for existing algorithms. After applying the MMWF algorithm with each mask sizes set from the MASH phantom abdominal images acquired using the MATLAB program, which includes Gaussian noise added, and compared the values of root mean square error (RMSE), peak signal-to-noise ratio (PSNR), coefficient correlation (CC), and universal image quality index (UQI). The results showed that RMSE value was the lowest and PSNR, CC and UQI values were the highest in the 5 x 5 mask size. In addition, comparing Gaussian filter, median filter, Wiener filter, and MMWF with RMSE, PSNR, CC, and UQI by applying the optimized mask size. As a result, the most improved RMSE, PSNR, CC, and UQI values were showed in MMWF algorithms.
Keywords
Computed tomography; MMWF algorithm; Male adult human phantom; Quantitative evaluation of image quality;
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