An Image Analysis and Classification Protocol for Characterization of Normal and Abnormal Memory Loss in Aging from Structural MRI

Author

Sheela, L. Jaba ; Shanthi, V.

Author_Institution

MCA Dept., Panimalar Eng. Coll., Chennai, India

fYear

2009

fDate

15-17 May 2009

Firstpage

639

Lastpage

643

Abstract

In this paper we propose a new CAD (Computer Aided Diagnosis) system to classify patients with Alzheimer disease. Five textural features proposed by Harlick are extracted from the MRI scans which characterize the disease. An enhanced CBA algorithm is used to classify the images as Normal or Abnormal based on the rule set generated during the training phase. The experiments were conducted on OASIS dataset and result show that the proposed system classifies with 98% accuracy, making association rules efficient for the classification task.

Keywords

biomedical MRI; brain; data mining; diseases; image classification; image texture; medical image processing; neurophysiology; Alzheimer disease; abnormal memory loss; aging; association rules; computer aided diagnosis; image analysis; image classification; normal memory loss; structural MRI; textural features; Aging; Alzheimer´s disease; Association rules; Cardiac disease; Data mining; Dementia; Educational institutions; Image analysis; Magnetic resonance imaging; Protocols;

fLanguage

English

Publisher

ieee

Conference_Titel

2009 International Conference on Signal Processing Systems

Conference_Location

Singapore

Print_ISBN

978-0-7695-3654-5

Type

conf

DOI

10.1109/ICSPS.2009.199

Filename

5166865