Adaptive Multiresolution Non-Local Means Filter for 3D MR Image Denoising - Archive ouverte HAL Access content directly
Journal Articles IET Image Processing Year : 2011

Adaptive Multiresolution Non-Local Means Filter for 3D MR Image Denoising

Pierrick Coupé
José V. Manjón
  • Function : Author
Montserrat Robles
  • Function : Author

Abstract

In this paper, an adaptive multiresolution version of the Blockwise Non-Local (NL-) means filter is presented for 3D Magnetic Resonance (MR) images. Based on an adaptive soft wavelet coefficient mixing, the proposed filter implicitly adapts the amount of denoising according to the spatial and frequency information contained in the image. Two versions of the filter are described for Gaussian and Rician noise. Quantitative validation was carried out on Brainweb datasets by using several quality metrics. The results show that the proposed multiresolution filter obtained competitive performance compared to recently proposed Rician NL-means filters. Finally, qualitative experiments on anatomical and Diffusion-Weighted MR images show that the proposed filter efficiently removes noise while preserving fine structures in classical and very noisy cases. The impact of the proposed denoising method on fiber tracking is also presented on a HARDI dataset.

Domains

Medical Imaging
Fichier principal
Vignette du fichier
Coupe_IETIP2011.pdf (1.36 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00645538 , version 1 (28-11-2011)

Identifiers

  • HAL Id : hal-00645538 , version 1

Cite

Pierrick Coupé, José V. Manjón, Montserrat Robles, Louis D. Collins. Adaptive Multiresolution Non-Local Means Filter for 3D MR Image Denoising. IET Image Processing, 2011. ⟨hal-00645538⟩
856 View
1088 Download

Share

Gmail Facebook X LinkedIn More