NDLI: Multimodal EEG, MRI and PET data fusion for Alzheimer's disease diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Polikar, R. Tilley, C. Hillis, B. Clark, C.M.
Copyright Year	2010
Description	Author affiliation: Electrical and Computer Eng., Dept. at Rowan University, Glassboro, NJ 08028, USA (Polikar, R.; Tilley, C.; Hillis, B.) \|\| Department of Neurology, University of Pennsylvania, Philadelphia, USA (Clark, C.M.)
Abstract	Alarmingly increasing prevalence of Alzheimer's disease (AD) due to the aging population in developing countries, combined with lack of standardized and conclusive diagnostic procedures, make early diagnosis of Alzheimer's disease a major public health concern. While no current medical treatment exists to stop or reverse this disease, recent dementia specific pharmacological advances can slow its progression, making early diagnosis all the more important. Several noninvasive biomarkers have been proposed, including P300 based EEG analysis, MRI volumetric analysis, PET based metabolic activity analysis, as alternatives to neuropsychological evaluation, the current gold standard of diagnosis. Each of these approaches, have shown some promising outcomes, however, a comprehensive data fusion analysis has not yet been conducted to investigate whether these different modalities carry complementary information, and if so, whether they can be combined to provide a more accurate analysis. In this effort, we provide a first look at such an analysis in combining EEG, MRI and PET data using an ensemble of classifiers based decision fusion approach, to determine whether a strategic combination of these different modalities can improve the diagnostic accuracy over any of the individual data sources when used with an automated classifier. Results show an improvement of up to 10%–20% using this approach compared to the classification performance obtained when using each individual data source.
Starting Page	6058
Ending Page	6061
File Size	479774
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5627621
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance imaging Positron emission tomography Electroencephalography Accuracy Biomarkers Dementia
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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