The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Noise reduction for magnetic resonance images via adaptive multiscale products thresholding
Abstract
Edge-preserving denoising is of great interest in medical image processing. This paper presents a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images. A Canny edge detector-like dyadic wavelet transform is employed. This results in the significant features in images evolving with high magnitude across wavelet scales, while noise decays rapidly. To exploit the wavelet interscale dependencies we multiply the adjacent wavelet subbands to enhance edge structures while weakening noise. In the multiscale products, edges can be effectively distinguished from noise. Thereafter, an adaptive threshold is calculated and imposed on the products, instead of on the wavelet coefficients, to identify important features. Experiments show that the proposed scheme better suppresses noise and preserves edges than other wavelet-thresholding denoising methods.
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Citations
Cites
A Computational Approach to Edge Detection
Canny, J. (1986) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1986.4767851 · Cited by 30,004
Daubechies, I. (1992) · doi:10.1137/1.9781611970104 · Cited by 15,979
Cited by
Canny edge detection enhancement by scale multiplication
Bao, P., Zhang, L., & Wu, X. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.173 · Cited by 601
Self-citationDenoising 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
- Bao, P., & Zhang, L.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 2003-09
- Volume
- 22
- Issue
- 9
- Pages
- 1089-1099
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2108207814
- Cited by
- 295
- References
- 2
- FWCI
- 11.29
- Type
- journal article
- Language
- en
- Open access
- closed
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