Feasibility of newly designed fast non local means (FNLM)-based noise reduction filter for X-ray imaging: A simulation study

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초록

In the diagnostic radiology field, reducing the radiation dose for patient lead to increased noise in image. Since increases of noise decrease the diagnosis rate, to reduce the noise is necessary. In this study quantitatively evaluates the four widely used and newly verified filters which remove noise in image: median, Wiener, total variation, and fast non local means (FNLM). For that purpose, X-ray and computed tomography (CT) images are acquired using MATLAB simulation with 3D voxelized phantom. To evaluate image performance, normalized noise power spectrum (NNPS), contrast to noise ratio (CNR) and coefficient of variation (COV) were used. As a result, we can efficiently remove noise in X-ray image when FNLM filter was used compared with frequently used filters. In conclusion, our results demonstrated that our proposed FNLM filter shows superior denoising performance, which is expected to enhance the detection of diseases in clinical images with low dose. (C) 2018 Elsevier GmbH. All rights reserved.

키워드

Median filter; Wiener filter; Total variation (TV) filter; Fast non local means (FNLM) filter; Image performance evaluation; Simulation study; NONLOCAL ALGORITHM
제목
Feasibility of newly designed fast non local means (FNLM)-based noise reduction filter for X-ray imaging: A simulation study
저자
Shim, Jina; Yoon, Myonggeun; Lee, Youngjin
DOI
10.1016/j.ijleo.2018.01.101
발행일
2018
유형
Article
저널명
Optik
권
160
페이지
124 ~ 130