DocumentCode
1844422
Title
Automated Analysis of 1H Magnetic Resonance Metabolic Imaging Data as an Aid to Clinical Decision-Making in the Evaluation of Intracranial Lesions
Author
Shungu, D.C. ; Du, S. ; Xiangling Mao ; Heier, L.A. ; Pannullo, S.C. ; Sajda, P.
Author_Institution
Cornell Univ., New York
fYear
2007
fDate
22-26 Aug. 2007
Firstpage
4327
Lastpage
4330
Abstract
Proton magnetic resonance spectroscopic imaging ( 1H MRSI) is a noninvasive metabolic imaging technique that has emerged as a potentially powerful tool for complementing structural magnetic resonance imaging (MRI) in the clinical evaluation of neurological disorders and diagnostic decision making. However, the relative complexity of methods that are currently available for analyzing the derived multi-dimensional metabolic imaging data has slowed incorporation of the technique into routine clinical practice. This paper discusses this impediment to widespread clinical use of 1H MRSI and then describes an automated data analysis approach that promises to facilitate use of the technique in the evaluation of intracranial lesions, with the potential to enhance the specificity of MRI and improve clinical decision-making.
Keywords
biomedical MRI; medical signal processing; neurophysiology; patient diagnosis; 1H MRSI data automated analysis; automated data analysis; clinical decision making; diagnostic decision making; intracranial lesion evaluation; magnetic resonance metabolic imaging; neurological disorder clinical evaluation; noninvasive metabolic imaging technique; proton magnetic resonance spectroscopic imaging; Data analysis; Decision making; Image analysis; Impedance; Lesions; Magnetic analysis; Magnetic resonance; Magnetic resonance imaging; Protons; Spectroscopy; Brain; Brain Neoplasms; Diagnosis, Differential; Humans; Magnetic Resonance Imaging; Protons;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location
Lyon
ISSN
1557-170X
Print_ISBN
978-1-4244-0787-3
Type
conf
DOI
10.1109/IEMBS.2007.4353294
Filename
4353294
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