NDLI: A novel eigenvector-based technique for spectral estimation of time-domain data in medical imaging

Content Provider	IEEE Xplore Digital Library
Author	Abousleman, G.P. Jordan, R. Asgharzadeh, A. Canady, L.D. Koechner, D. Griffey, R.H.
Copyright Year	1990
Description	Author affiliation: New Mexico Univ., Albuquerque, NM, USA (Abousleman, G.P.; Jordan, R.; Asgharzadeh, A.; Canady, L.D.; Koechner, D.; Griffey, R.H.)
Abstract	The use of a complex MUSIC (multiple signal classification) algorithm to signal average MR spectroscopic data from a 1-cm/sup 3/ voxel of diseased brain tissue for only five min and obtain diagnostically useful studies is discussed. A complex eigenvector-based method for performing spectral analysis of time-domain data independent of the signal-to-noise ratio is demonstrated. The implementation of the procedure requires no preprocessing of the time-domain data record. The technique is well suited for magnetic resonance spectroscopy and imaging, where the signal available from small regions corresponding to areas of diseased tissue in patients presenting for diagnosis is always dominated by the Johnson noise present in the receiver circuit.<>
Starting Page	426
Ending Page	431
File Size	234971
Page Count	6
File Format	PDF
ISBN	0818690402
DOI	10.1109/CBMSYS.1990.109429
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1990-06-03
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multiple signal classification Spectroscopy Time domain analysis Classification algorithms Brain Spectral analysis Signal to noise ratio Magnetic resonance Magnetic resonance imaging Circuit noise
Content Type	Text
Resource Type	Article

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