By Topic

Graph Based Classification of MRI Data Based on the Ventricular System

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Long, S.S. ; Washington State Univ., Pullman, WA, USA ; Holder, L.B.

The ventricular system inside the brain is known to enlarge and change shape given conditions such as Alzheimer's disease. This change in shape may provide a way to assess the level of cognitive impairment of a patient, as well as other intellectual characteristics. This paper describes the use of trees to represent the 3D space containing the third and lateral ventricles, and classification of these trees using frequent sub graph mining and support vector machines. Level of cognitive impairment and years of education are shown to be predictable given a tree representation of the shape of the third and lateral ventricles, demonstrating that the shape of the ventricular system correlates with these attributes. These results were generated using a cross-sectional collection of 416 MR images of subjects ranging in age from 18 to 96 years, including 100 subjects diagnosed with Alzheimer's disease.

Published in:

Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on

Date of Conference:

11-11 Dec. 2011