The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Wavelet-based Rician noise removal for magnetic resonance imaging
Abstract
It is well known that magnetic resonance magnitude image data obey a Rician distribution. Unlike additive Gaussian noise, Rician "noise" is signal-dependent, and separating signal from noise is a difficult task. Rician noise is especially problematic in low signal-to-noise ratio (SNR) regimes where it not only causes random fluctuations, but also introduces a signal-dependent bias to the data that reduces image contrast. This paper studies wavelet-domain filtering methods for Rician noise removal. We present a novel wavelet-domain filter that adapts to variations in both the signal and the noise.
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Daubechies, I. (1992) · doi:10.1137/1.9781611970104 · Cited by 15,979
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Işın, A., Direkoğlu, C., & Şah, M. (2016) · Procedia Computer Science · doi:10.1016/j.procs.2016.09.407 · Cited by 766
Review of brain MRI image segmentation methods
Balafar, M. A., Ramli, A. R., Saripan, M. I., & Mashohor, S. (2010) · Artificial Intelligence Review · doi:10.1007/s10462-010-9155-0 · Cited by 438
Diffusion Weighted Image Denoising Using Overcomplete Local PCA
Manjón, J. V., Coupé, P., Concha, L., Buades, A., Collins, D. L., & Robles, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073021 · Cited by 417
Denoising of Dynamic Contrast-Enhanced MR Images Using Dynamic Nonlocal Means
Gal, Y., Mehnert, A. J. H., Bradley, A. P., McMahon, K., Kennedy, D., & Crozier, S. (2010) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2009.2026575 · Cited by 78
Metadata
- Authors
- Nowak, R. D.
- Venue
- IEEE Transactions on Image Processing
- Published
- 1999
- Volume
- 8
- Issue
- 10
- Pages
- 1408-1419
- ISSN
- 1057-7149 (ISSN-L)
- OpenAlex
- W2132140814
- Cited by
- 620
- References
- 1
- FWCI
- 7.27
- Type
- journal article
- Language
- en
- Open access
- closed
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- Nowak, R. D. (1999). Wavelet-based Rician noise removal for magnetic resonance imaging. IEEE Transactions on Image Processing. https://doi.org/10.1109/83.791966
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
