SU-E-J-16: Noise Reduction with Detail Preservation for Low-Dose KV CBCT Using Non-Local Means: Simulated Patient Study

2011 ◽  
Vol 38 (6Part7) ◽  
pp. 3445-3445 ◽  
Author(s):  
W Lu ◽  
W Yao ◽  
J Wang ◽  
D Yang
Keyword(s):  
Noise Reduction ◽  
Low Dose ◽  
Simulated Patient ◽  
Patient Study ◽  
Local Means ◽  
Non Local

scholarly journals Application of Fast Non-Local Means Algorithm for Noise Reduction Using Separable Color Channels in Light Microscopy Images

2021 ◽  
Vol 18 (6) ◽  
pp. 2903
Author(s):  
Seong-Hyeon Kang ◽  
Ji-Youn Kim
Keyword(s):  
Light Microscopy ◽  
Noise Reduction ◽  
Natural Image ◽  
Search Window ◽  
Local Means ◽  
Image Characteristics ◽  
Non Local ◽  
Spatial Quality ◽  
Evaluation Parameters ◽  
Color Channels

The purpose of this study is to evaluate the various control parameters of a modeled fast non-local means (FNLM) noise reduction algorithm which can separate color channels in light microscopy (LM) images. To achieve this objective, the tendency of image characteristics with changes in parameters, such as smoothing factors and kernel and search window sizes for the FNLM algorithm, was analyzed. To quantitatively assess image characteristics, the coefficient of variation (COV), blind/referenceless image spatial quality evaluator (BRISQUE), and natural image quality evaluator (NIQE) were employed. When high smoothing factors and large search window sizes were applied, excellent COV and unsatisfactory BRISQUE and NIQE results were obtained. In addition, all three evaluation parameters improved as the kernel size increased. However, the kernel and search window sizes of the FNLM algorithm were shown to be dependent on the image processing time (time resolution). In conclusion, this work has demonstrated that the FNLM algorithm can effectively reduce noise in LM images, and parameter optimization is important to achieve the algorithm’s appropriate application.

Optimizing non-local means for denoising low dose CT

2009 ◽  
Author(s):  
Zachary S. Kelm ◽  
Daniel Blezek ◽  
Brian Bartholmai ◽  
Bradley J. Erickson
Keyword(s):  
Low Dose ◽  
Low Dose Ct ◽  
Local Means ◽  
Non Local

scholarly journals Noise Reduction in Medical Images using an Unbiased Non-local Means Method

IJARCCE ◽  
2017 ◽  
Vol 6 (5) ◽  
pp. 702-706
Author(s):  
Sushma C ◽  
Kavitha G
Keyword(s):  
Noise Reduction ◽  
Medical Images ◽  
Local Means ◽  
Non Local

scholarly journals Low-Dose Computed Tomography Filtering Using Geodesic Distances

2020 ◽  
Author(s):  
Daniel A. Góes ◽  
Nelson D. A. Mascarenhas
Keyword(s):  
Computed Tomography ◽  
Low Dose ◽  
Convex Sets ◽  
Projection Onto Convex Sets ◽  
Local Means ◽  
Gamma Distributions ◽  
Non Local ◽  
Geodesic Distances ◽  
Low Dose Computed Tomography

Due to the concerns related to patient exposure to X-ray, the dosage used in computed tomography must be reduced (Low-dose Computed Tomography - LDCT). One of the effects of LDCT is the degradation in the quality of the final reconstructed image. In this work, we propose a method of filtering LDCT sinograms that are subject to signal-dependent Poisson noise. To filter this type of noise, we use a Bayesian approach, changing the Non-local Means (NLM) algorithm to use geodesic stochastic distances for Gamma distribution, the conjugate prior to Poisson, as a similarity metric between each projection point. Among the geodesic distances evaluated, we found a closed solution for the Shannon entropy for Gamma distributions. We compare our method with the following methods based on NLM: PoissonNLM, Stochastic Poisson NLM, Stochastic Gamma NLM and the original NLM after Anscombe transform. We also compare with BM3D after Anscombe transform. Comparisons are made on the final images reconstructed by the Filtered-Back Projection (FBP) and Projection onto Convex Sets (POCS) methods using the metrics PSNR and SSIM.

Locally optimized non-local means denoising for low-dose X-ray backscatter imagery

2014 ◽  
Vol 22 (5) ◽  
pp. 569-586
Author(s):  
Brian H. Tracey ◽  
Eric L. Miller ◽  
Yue Wu ◽  
Christopher Alvino ◽  
Markus Schiefele ◽  
...  
Keyword(s):  
Low Dose ◽  
X Ray ◽  
Local Means ◽  
Non Local

Image Noise Reduction in Computed Tomography with Non-Local Means Algorithm Based on Adaptive Filtering Coefficients

2020 ◽  
Vol 40 (7) ◽  
pp. 0710001
Author(s):  
蔡玉芳 Cai Yufang ◽  
陈桃艳 Chen Taoyan ◽  
王珏 Wang Jue ◽  
姚功杰 Yao Gongjie
Keyword(s):  
Computed Tomography ◽  
Noise Reduction ◽  
Adaptive Filtering ◽  
Image Noise ◽  
Local Means ◽  
Image Noise Reduction ◽  
Non Local

Adaptive colour-guided non-local means algorithm for compound noise reduction of depth maps

2020 ◽  
Vol 14 (12) ◽  
pp. 2768-2779
Author(s):  
Mostafa M. Ibrahim ◽  
Qiong Liu ◽  
You Yang
Keyword(s):  
Noise Reduction ◽  
Depth Maps ◽  
Local Means ◽  
Non Local
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