NDLI: Using local texture maps of brain MR images to detect Mild Cognitive Impairment

Content Provider	IEEE Xplore Digital Library
Author	Simoes, R. Slump, C. van Cappellen van Walsum, A.
Copyright Year	2012
Description	Author affiliation: Department of Anatomy, Radboud University Nijmegen Medical Centre, The Netherlands (van Cappellen van Walsum, A.) \|\| Signals and Systems Group, University of Twente, The Netherlands (Simoes, R.; Slump, C.)
Abstract	Early detection of Alzheimer's disease is expected to aid in the development and monitoring of more effective treatments. Classification methods have been proposed to distinguish Alzheimer's patients from normal controls using Magnetic Resonance Images. However, their performance drops when classifying patients at a prodromal stage, such as in Mild Cognitive Impairment. Most often, the features used in these classification tasks are related to structural measures such as volume, shape and tissue density. However, microstructural changes have been shown to arise even earlier than these larger-scale alterations. Taking this into account, we propose the use of local statistical texture maps that make no assumptions regarding the location of the affected brain regions. Each voxel contains texture information from its local neighborhood and is used as a feature in the classification of normal controls and Mild Cognitive Impairment patients. The proposed approach obtained an accuracy of 87% (sensitivity 85%, specificity 95%) with Support Vector Machines, outperforming the 63% achieved by the local gray matter density feature.
Starting Page	153
Ending Page	156
File Size	165306
Page Count	4
File Format	PDF
ISBN	9781467322164
ISSN	10514651
e-ISBN	9784990644109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-11
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	ICPR Org Committee
Subject Keyword	Alzheimer's disease Magnetic resonance imaging Accuracy Support vector machines Correlation
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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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