Open AccessNoise reduction in magnetic resonance images using adaptive non‐local means filtering
Author(s) -
Kang B.,
Choi O.,
Kim J.D.,
Hwang D.
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2012.3602
Subject(s) - noise reduction , noise (video) , reduction (mathematics) , computer science , median filter , computer vision , artificial intelligence , ground truth , image (mathematics) , set (abstract data type) , noise measurement , algorithm , mathematics , image processing , geometry , programming language
Proposed is a noise reduction method for magnetic resonance (MR) images. This method can be considered a new adaptive non‐local means filtering technique since different weights based on the edgeness of an image are applied. Unlike conventional noise reduction methods, which typically fail in preserving detailed information, the proposed method preserves fine structures while significantly reducing noise in MR images. For comparing the proposed method with other noise reduction methods, both a simulated ground truth data set and real MR images were used. The experiment shows that the proposed method outperforms conventional methods in terms of both restoration accuracy and quality.