NDLI: An Information Theoretic Approach Characterizing Diffusion Anisotropy in Diffusion-weighted Magnetic Resonance Images

Content Provider	IEEE Xplore Digital Library
Author	Metwalli, N.S. LaConte, S.M. Hu, X.P.
Copyright Year	2006
Description	Author affiliation: Wallace H. Coulter Dept. of Biomed. Eng., Georgia Inst. of Technol., Atlanta, GA (Metwalli, N.S.)
Abstract	We propose an alternative approach that does not rely on tensor models for characterizing diffusion anisotropy from diffusion-weighted magnetic resonance images. Information content inherent in the diffusion attenuation values are the only measures needed for our characterization. We explore the information content inherent in these values. We calculate Shannon's entropy on the diffusion attenuation values measured across the applied diffusion-sensitizing gradient directions. This method is evaluated with data generated with different diffusion gradient encoding schemes demonstrating the validity of our approach and its potential use to better differentiate between brain tissue types over tensor-based measures
Sponsorship	IEEE EMB
Starting Page	2260
Ending Page	2263
File Size	245166
Page Count	4
File Format	PDF
ISBN	1424400325
ISSN	1557170X
DOI	10.1109/IEMBS.2006.259870
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Anisotropic magnetoresistance Magnetic resonance Entropy Diffusion tensor imaging Biomedical engineering Tensile stress Biomedical measurements Biomedical imaging Attenuation measurement Information theory
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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