The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time
Abstract
In this paper, we introduce a new method for image smoothing based on a fourth-order PDE model. The method is tested on a broad range of real medical magnetic resonance images, both in space and time, as well as on nonmedical synthesized test images. Our algorithm demonstrates good noise suppression without destruction of important anatomical or functional detail, even at poor signal-to-noise ratio. We have also compared our method with related PDE models.
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Cites
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Magnetic Resonance Imaging: Physical Principles and Sequence Design
Brown, R. W., Cheng, Y. N., Haacke, E. M., Thompson, M. R., & Venkatesan, R. (2014) · doi:10.1002/9781118633953 · Cited by 2,688
Image Selective Smoothing and Edge Detection by Nonlinear Diffusion. II
Alvarez, L., Lions, P.-L., & Morel, J.-M. (1992) · SIAM Journal on Numerical Analysis · doi:10.1137/0729052 · Cited by 2,208
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Image Selective Smoothing and Edge Detection by Nonlinear Diffusion
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Nonlinear anisotropic filtering of MRI data
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A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
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Fourth-order partial differential equations for noise removal
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Cited by
An overview of deep learning in medical imaging focusing on MRI
Lundervold, A. S., & Lundervold, A. (2019) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2018.11.002 · Cited by 2,058
Self-citationA New Alternating Minimization Algorithm for Total Variation Image Reconstruction
Wang, Y., Yang, J., Yin, W., & Zhang, Y. (2008) · SIAM Journal on Imaging Sciences · doi:10.1137/080724265 · Cited by 1,975
Wu, C., & Tai, X.-C. (2010) · SIAM Journal on Imaging Sciences · doi:10.1137/090767558 · Cited by 615
Self-citationAn efficient algorithm for compressed MR imaging using total variation and wavelets
Ma, S., Yin, W., Zhang, Y., & Chakraborty, A. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587391 · Cited by 334
A survey on the magnetic resonance image denoising methods
Mohan, J., Krishnaveni, V., & Guo, Y. (2014) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2013.10.007 · Cited by 295
Metadata
- Authors
- Lysaker, M., Lundervold, A., & Tai, X.-C.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2003-12
- Volume
- 12
- Issue
- 12
- Pages
- 1579-1590
- ISSN
- 1057-7149 (ISSN-L)
- OpenAlex
- W2135036909
- Cited by
- 911
- References
- 17
- FWCI
- 10.20
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lysaker, M., Lundervold, A., & Tai, X.-C. (2003). Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time. IEEE Transactions on Image Processing. https://doi.org/10.1109/tip.2003.819229
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
