Abstract
Low signal-to-noise ratio has been a significant limitation for clinical applications of magnetic resonance spectroscopic imaging (MRSI). This paper investigates a new scheme for denoising MRSI data, incorporating both an anatomically-adapted spatial-smoothness constraint and an autoregressive spectral constraint within the penalized maximum-likelihood framework. Both theoretical analysis and simulation results are provided to characterize the denoising performance of this approach.
| Original language | English (US) |
|---|---|
| Title of host publication | 2010 7th IEEE International Symposium on Biomedical Imaging |
| Subtitle of host publication | From Nano to Macro, ISBI 2010 - Proceedings |
| Pages | 720-723 |
| Number of pages | 4 |
| DOIs | |
| State | Published - Aug 9 2010 |
| Event | 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Rotterdam, Netherlands Duration: Apr 14 2010 → Apr 17 2010 |
Other
| Other | 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 |
|---|---|
| Country | Netherlands |
| City | Rotterdam |
| Period | 4/14/10 → 4/17/10 |
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ASJC Scopus subject areas
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
Cite this
Denoising of MR spectroscopic imaging data with spatial-spectral regularization. / Nguyen, Hien M.; Haldar, Justin P.; Do, Minh N; Liang, Zhi-Pei.
2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings. 2010. p. 720-723 5490073.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Denoising of MR spectroscopic imaging data with spatial-spectral regularization
AU - Nguyen, Hien M.
AU - Haldar, Justin P.
AU - Do, Minh N
AU - Liang, Zhi-Pei
PY - 2010/8/9
Y1 - 2010/8/9
N2 - Low signal-to-noise ratio has been a significant limitation for clinical applications of magnetic resonance spectroscopic imaging (MRSI). This paper investigates a new scheme for denoising MRSI data, incorporating both an anatomically-adapted spatial-smoothness constraint and an autoregressive spectral constraint within the penalized maximum-likelihood framework. Both theoretical analysis and simulation results are provided to characterize the denoising performance of this approach.
AB - Low signal-to-noise ratio has been a significant limitation for clinical applications of magnetic resonance spectroscopic imaging (MRSI). This paper investigates a new scheme for denoising MRSI data, incorporating both an anatomically-adapted spatial-smoothness constraint and an autoregressive spectral constraint within the penalized maximum-likelihood framework. Both theoretical analysis and simulation results are provided to characterize the denoising performance of this approach.
UR - http://www.scopus.com/inward/record.url?scp=77955208795&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77955208795&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2010.5490073
DO - 10.1109/ISBI.2010.5490073
M3 - Conference contribution
AN - SCOPUS:77955208795
SN - 9781424441266
SP - 720
EP - 723
BT - 2010 7th IEEE International Symposium on Biomedical Imaging
ER -