@inproceedings{e872f531917f435b9f73791632c20904,
title = "Spatiotemporal denoising of MR spectroscopic imaging data by low-rank approximations",
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.",
keywords = "Cadzow enhancement, denoising, low-rank approximation, MR spectroscopic imaging, partially-separable functions",
author = "Nguyen, {Hien M.} and Xi Peng and Do, {Minh N} and Zhi-Pei Liang",
year = "2011",
doi = "10.1109/ISBI.2011.5872539",
language = "English (US)",
isbn = "9781424441280",
series = "Proceedings - International Symposium on Biomedical Imaging",
pages = "857--860",
booktitle = "2011 8th IEEE International Symposium on Biomedical Imaging",
note = "2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 ; Conference date: 30-03-2011 Through 02-04-2011",
}