Name
Title | ||
|---|---|---|
Semiblind Spectral Factorization Approach for Magnetic Resonance Spectroscopy Quantification. |
Abstract | ||
|---|---|---|
An observed magnetic resonance (MR) spectrum is composed of a set of metabolites spectrum, baseline, and noise. Quantification of metabolites of interest in the MR spectrum provides great opportunity for early diagnosis of dangerous disease such as brain tumors. In this paper, a novel spectral factorization approach based on singular spectrum analysis (SSA) is proposed to quantify magnetic resonan... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TBME.2017.2770088 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Nuclear magnetic resonance,Covariance matrices,Algorithm design and analysis,Time-domain analysis,Time series analysis,Trajectory,Frequency-domain analysis | Computer science,Artificial intelligence,Nuclear magnetic resonance spectroscopy,Frequency domain,Computer vision,Algorithm design,Pattern recognition,Singular spectrum analysis,Covariance matrix,Metabolite,Nuclear magnetic resonance,Magnetic resonance imaging,Spectral theorem | Journal |
Volume | Issue | ISSN |
65 | 8 | 0018-9294 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saideh Ferdowsi | 1 | 147 | 10.85 |
| Vahid Abolghasemi | 2 | 274 | 22.58 |