Unbiased noise estimation and denoising in parallel magnetic resonance imaging

Unbiased noise estimation and denoising in parallel magnetic resonance imaging (202 visite) (PDF privato 154 visite)

Borrelli P, Palma G, Comerci M, Alfano B

Icassp - Ieee International Conference On Acoustics - Speech And Signal Processing - Proceedings (ISSN: 1520-6149, 1520-61499781479928927), 2014 May; 10.1109/ICASSP.201: 1230-1234.

Tipo di articolo: Journal Article, Conference Paper,

Impact factor: 0, Impact factor a 5 anni: 0

Url: http://www.scopus.com/inward/record.url?eid=2-s2.0-84905234778&partnerID=40&md5=a99a24742c5bc0ee03b55ff111eb2070

Parole chiave: Denoising, Noise Estimation, Non-Local Means, Parallel Mri, Rician Noise, Algorithms, Image Denoising, Magnetic Resonance Imaging, Signal Processing, De-Noising, Acoustic Noise,

Affiliazioni:

*** IBB - CNR ***
University of Naples Federico II, Dept. of Advanced Biomedical Sciences, Via Pansini 5, 80131 Naples, Italy
National Research Council of Italy, Inst. of Biostructures and Bioimaging, Via De Amicis 95, 80145 Naples, Italy
Universita degli Studi di Napoli Federico II
Consiglio Nazionale delle Ricerche

Riferimenti:

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Pruessmann, K.P., Encoding and reconstruction in parallel mri (2006) NMR in Biomedicine, 19 (3), pp. 288-299

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Manjón, J.V., Coupé, P., Martí-Bonmatí, L., Louis Collins, D., Robles, M., Adaptive nonlocal means denoising of mr images with spatially varying noise levels (2010) Journal of Magnetic Resonance Imaging, 31 (1), pp. 192-203

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Palma, G., Piccialli, F., Comerci, M., De Michele, P., Borrelli, P., Cuomo, S., Alfano, B., 3d non-local means denoising via multi-gpu (2013) Proceedings of the 2013 Federated Conference on Computer Science and Information Systems, pp. 495-498

Aja-Fern ndez, S., Trist n-Vega, A., Alberola-L pez, C., Noise estimation in single-and multiple-coil magnetic resonance data based on statistical models (2009) Magnetic Resonance Imaging, 27 (10), pp. 1397-1409

Glockner, J. F., Hu, H. H., Stanley, D. W., Angelos, L., King, K., Parallel mr imaging: A users guide1 (2005) Radiographics, 25 (5), pp. 1279-1297

Pruessmann, K. P., Encoding and reconstruction in parallel mri (2006) NMR in Biomedicine, 19 (3), pp. 288-299

Griswold, M. A., Jakob, P. M., Heidemann, R. M., Nittka, M., Jellus, V., Wang, J., Kiefer, B., Haase, A., Generalized autocalibrating partially parallel acquisitions (grappa) (2002) Magnetic Resonance in Medicine, 47 (6), pp. 1202-1210

Pruessmann, K. P., Weiger, M., Scheidegger, M. B., Boesiger, P., Sense: Sensitivity encoding for fast mri (1999) Magnetic Resonance in Medicine, 42 (5), pp. 952-962

Coup, P., Yger, P., Prima, S., Hellier, P., Kervrann, C., Barillot, C., An optimized blockwise nonlocal means denoising filter for 3-d magnetic resonance images (2008) Medical Imaging, IEEE Transactions on, 27 (4), pp. 425-441

Manj n, J. V., Coup, P., Mart -Bonmat, L., Louis Collins, D., Robles, M., Adaptive nonlocal means denoising of mr images with spatially varying noise levels (2010) Journal of Magnetic Resonance Imaging, 31 (1), pp. 192-203

In magnetic resonance (MR) clinical practice, noise estimation is usually performed on Rayleigh-distributed background (no signal area) of magnitude images. Although noise variance in quadrature MR images is considered spatially independent, parallel MRI (pMRI) techniques as SENSE or GRAPPA generate spatially varying noise (SVN) distribution. In this scenario noise estimation from background may produce biased results. To address these limitations we introduce a novel noise estimation scheme based on local statistics. Our method turns out to be more accurate than the other pMRI noise estimation schemes previously described in the literature. Denoising performances, measured by visual inspection and peak signal-to-noise ratio (PSNR), of Non-Local Means denoising filters (NLM) are considerably improved using SVN-NLM in case of inhomogeneous noise. Furthermore, SVN-NLM behaves as well as standard NLM when homogeneous noise was added, thus proving to be a robust and powerful denoising algorithm for arbitrary MRI datasets. © 2014 IEEE.

Interrogazione effettuata: [atitle, keywords] "Denoising" OR [atitle, keywords] "Noise Estimation" OR [atitle, keywords] "Non-Local Means" OR [atitle, keywords] "Parallel Mri" OR [atitle, keywords] "Rician Noise" OR [atitle, keywords] "Algorithms" OR [atitle, keywords] "Image Denoising"

▼ Sviluppo di software General Purpose su GPU

Comerci Marco

Palma Giuseppe

Alfano Bruno

Tedeschi Enrico

Interrogazione effettuata: [ptitle] "Denoising" OR [ptitle] "Noise Estimation" OR [ptitle] "Non-Local Means" OR [ptitle] "Parallel Mri" OR [ptitle] "Rician Noise" OR [ptitle] "Algorithms" OR [ptitle] "Image Denoising"

3D Non-Local Means denoising via multi-GPU (dominio pubblico) (169 visite)

Descent Algorithms on Oblique Manifold for Source-Adaptive ICA Contrast (accesso riservato) (131 visite)

Improving SNR in Susceptibility Weighted Imaging by a NLM-based denoising scheme (accesso riservato) (162 visite)

Inter-patient image registration algorithms to disentangle regional dose bioeffects (dominio pubblico) (63 visite)

Unbiased noise estimation and denoising in parallel magnetic resonance imaging (accesso riservato) (154 visite)

Interrogazione effettuata: [btitle, keywords] "Denoising" [btitle, keywords] "Noise Estimation" [btitle, keywords] "Non-Local Means" [btitle, keywords] "Parallel Mri" [btitle, keywords] "Rician Noise" [btitle, keywords] "Algorithms" [btitle, keywords] "Image Denoising"

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