IRIS-HSVD for automatic MRS data quantification

Author

Wang, Xin ; Lee, Jing-Huei

Author_Institution

Dept. of Biomed. Eng., Univ. of Cincinnati, Cincinnati, OH

fYear

2008

fDate

4-7 May 2008

Abstract

One of the most difficult problems in magnetic resonance spectroscopy (MRS) data processing is to separate the targeted chemical compoundspsila signal from a distorted baseline in very noisy data. In this work, we propose a new quantification scheme based on the iterative reduction of interference signal hankel singular value decomposition (IRIS-HSVD) algorithm for accurate, robust and automatic quantification of multidimensional human brain ³¹P MRS data.

Keywords

biomagnetism; brain; iterative methods; magnetic resonance spectroscopy; medical signal processing; singular value decomposition; IRIS-HSVD; automatic MRS data quantification; iterative reduction of interference signal hankel singular value decomposition; magnetic resonance spectroscopy; multidimensional human brain; Chemical compounds; Chemical processes; Data processing; Distortion; Interference; Magnetic noise; Magnetic resonance; Signal processing; Singular value decomposition; Spectroscopy; estimation; magnetic resonance spectroscopy; signal processing; singular value decomposition;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on

Conference_Location

Niagara Falls, ON

ISSN

0840-7789

Print_ISBN

978-1-4244-1642-4

Electronic_ISBN

0840-7789

Type

conf

DOI

10.1109/CCECE.2008.4564861

Filename

4564861