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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.
References
-
-
1)
-
5. Buades, A., Coll, B., Morel, J.-M.: ‘A non-local algorithm for image denoising’. Proc. IEEE Conf. on Computer Vision and Pattern Recognition, San Diego, CA, USAJune 2005, 2 pp. 60–65.
-
2)
-
1. Rudin, L., Osher, S., Fatemi, E.: ‘Nonlinear total variation based noise removal algorithms’, Physica D, 1992, 60(1–4), pp. 259–268 (doi: 10.1016/0167-2789(92)90242-F).
-
3)
-
4)
-
3. Tomasi, C., Manduchi, R.: ‘Bilateral filtering for gray and color images’. Proc. of 6th Int. Conf. on Computer Vision, Bombay, IndiaJanuary 1998, pp. 839–846.
-
5)
-
4. Manjón, JV., Carbonell-Caballero, J., Lull, JJ, Garcia-Martí, G., Martí-Bonmatí, L., Robles, M.: ‘MRI denoising using non-local means’. Med Image Anal, 200812(4), pp. 514–23 (doi: 10.1016/j.media.2008.02.004).
-
6)
-
2. Perona, P., Malik, J.: ‘Scale space and edge detection using anisotropic diffusion’, IEEE Trans. Pattern Anal. Mach. Intell., 199012(7), pp. 629–639 (doi: 10.1109/34.56205).
-
7)
-
6. Buades, A., Coll, B., Morel, J.-M.: ‘Nonlocal image and movie denoising,’ Int. J. Comput. Vis., 200876(2), pp. 123–139 (doi: 10.1007/s11263-007-0052-1).
-
8)
-
A. Buades ,
B. Coll ,
J.-M. Morel
.
Nonlocal image and movie denoising,.
Int. J. Comput. Vis.
,
2 ,
123 -
139
-
9)
-
Buades, A., Coll, B., Morel, J.-M.: `A non-local algorithm for image denoising', Proc. IEEE Conf. on Computer Vision and Pattern Recognition, June 2005, San Diego, CA, USA, 2, p. 60–65.
-
10)
-
BrainWeb: Simulated Brain Database. Available from: http://www.bic.mni.mcgill.ca/brainweb/.
-
11)
-
L. Rudin ,
S. Osher ,
E. Fatemi
.
Nonlinear total variation based noise removal algorithms.
Physica D
,
259 -
268
-
12)
-
J.V. Manjón ,
J. Carbonell-Caballero ,
J.J. Lull ,
G. García-Martí ,
L. Martí-Bonmatí ,
M. Robles
.
MRI denoising using non-local means.
Med. Image Anal.
,
12 ,
514 -
523
-
13)
-
Tomasi, C., Manduchi, R.: `Bilateral filtering for gray and color images', Proc. of 6th Int. Conf. on Computer Vision, January 1998, Bombay, India, p. 839–846.
-
14)
-
P. Perona ,
J. Malik
.
Scale-space and edge detection using anistropic diffusion.
IEEE Trans. Pattern Anal. Mach. Intell.
,
7 ,
629 -
639
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2012.3602
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