Conference proceeding
Spatiotemporal denoising of MR spectroscopic imaging data by low-rank approximations
2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.857-860
03/2011
DOI: 10.1109/ISBI.2011.5872539
Abstract
This paper addresses the denoising problem associated with magnetic resonance spectroscopic imaging (MRSI), where low signal-to-noise ratio (SNR) has been a critical problem. A new scheme is proposed, which exploits two low-rank structures that exist in MRSI data, one due to partial separability and the other is due to linear predictability. Experimental results from practical data demonstrate that the proposed method provides an effective way to denoise MRSI data while preserving spatial-spectral features in a wide range of SNR values.
Details
- Title: Subtitle
- Spatiotemporal denoising of MR spectroscopic imaging data by low-rank approximations
- Creators
- Hien M Nguyen - University of Illinois Urbana-ChampaignXi Peng - University of Illinois Urbana-ChampaignMinh N Do - University of Illinois Urbana-ChampaignZhi-Pei Liang - University of Illinois Urbana-Champaign
- Resource Type
- Conference proceeding
- Publication Details
- 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.857-860
- DOI
- 10.1109/ISBI.2011.5872539
- ISSN
- 1945-7928
- eISSN
- 1945-8452
- Publisher
- IEEE
- Language
- English
- Date published
- 03/2011
- Academic Unit
- Radiology
- Record Identifier
- 9984446403102771
Metrics
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