title: Fast non local means denoising for 3D MR images.
abstract: One critical issue in the context of image restoration is the problem of noise removal while keeping the integrity of relevant image information. Denoising is a crucial step to increase image conspicuity and to improve the performances of all the processings needed for quantitative imaging analysis. The method proposed in this paper is based on an optimized version of the Non Local (NL) Means algorithm. This approach uses the natural redundancy of information in image to remove the noise. Tests were carried out on synthetic datasets and on real 3T MR images. The results show that the NL-means approach outperforms other classical denoising methods, such as Anisotropic Diffusion Filter and Total Variation.
authors.affiliation: Unit/Project VisAGeS U746, INSERM - INRIA - CNRS - Univ-Rennes 1, IRISA campus Beaulieu 35042 Rennes Cedex, France. pcoupe@irisa.fr
authors.forename: Pierrick
authors.initials: P
authors.lastname: Coupé
authors.forename: Pierre
authors.initials: P
authors.lastname: Yger
authors.forename: Christian
authors.initials: C
authors.lastname: Barillot
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity