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Denoising of Dynamic Contrast-Enhanced MR Images Using Dynamic Nonlocal Means

Gal, Y. (författare)
Mehnert, Andrew, 1967 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Bradley, A. P. (författare)
visa fler...
McMahon, K. (författare)
Kennedy, D. (författare)
Crozier, S. (författare)
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 (creator_code:org_t)
2010
2010
Engelska.
Ingår i: IEEE Transactions on Medical Imaging. - 0278-0062. ; 29:2, s. 302-310
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • This paper presents a new algorithm for denoising dynamic contrast-enhanced (DCE) MR images. It is a novel variation on the nonlocal means (NLM) algorithm. The algorithm, called dynamic nonlocal means (DNLM), exploits the redundancy of information in the temporal sequence of images. Empirical evaluations of the performance of the DNLM algorithm relative to seven other denoising methods-simple Gaussian filtering, the original NLM algorithm, a trivial extension of NLM to include the temporal dimension, bilateral filtering, anisotropic diffusion filtering, wavelet adaptive multiscale products threshold, and traditional wavelet thresholding-are presented. The evaluations include quantitative evaluations using simulated data and real data (20 DCE-MRI data sets from routine clinical breast MRI examinations) as well as qualitative evaluations using the same real data (24 observers: 14 image/signal-processing specialists, 10 clinical breast MRI radiographers). The results of the quantitative evaluation using the simulated data show that the DNLM algorithm consistently yields the smallest MSE between the denoised image and its corresponding original noiseless version. The results of the quantitative evaluation using the real data provide evidence, at the alpha = 0.05 level of significance, that the DNLM algorithm yields the smallest MSE between the denoised image and its corresponding original noiseless version. The results of the qualitative evaluation provide evidence, at the alpha = 0.05 level of significance, that the DNLM algorithm performs visually better than all of the other algorithms. Collectively the qualitative and quantitative results suggest that the DNLM algorithm more effectively attenuates noise in DCE MR images than any of the other algorithms.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Nyckelord

noise removal
dynamic contrast-enhanced (dce) magnetic resonance imaging (mri)
magnetic-resonance images
anisotropic diffusion
perfusion
robust
dynamic nonlocal means (dnlm)
rician noise
denoising
noise
nonlocal means
space
filter
breast

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