Diagnostic Features of Alzheimer's Disease Extracted From FDG Pet Images

Abstract

FDG-PET images of patients suffering from Alzheimers disease (AD) were obtained from Paul Scherre Institute, Villingen, Switzerland. The data were from a CTI/Siemens ECAT 933/04-16 scanner, comprising of 7 image slices 128 x 128 pixels. The study included 48 Clinically diagnosed AD patients and 73 normal controls. Using an invariant feature extraction method features were extracted. The features are invariant to translation and rotation of object(s) within the image. The patients are separated into two groups one for training (24 AD and 37 normal controls) and one cross validation testing (24 AD and 36 normal controls). Discriminant function analysis yielded a classification accuracy of 88% sensitivity and 86% specificity, when these features were used.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412377

Entities

People

  • A. Sayeed
  • M. Petrou
  • R. Maguire

Organizations

  • University of Surrey

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Alzheimer Disease
  • Classification
  • Computations
  • Diseases And Disorders
  • Electrical Engineering
  • Engineering
  • Feature Extraction
  • Gray Scale
  • Mathematics
  • Military Research
  • Translations

Fields of Study

  • Medicine

Readers

  • Computer Vision.
  • Medical Imaging.
  • Psychometric Testing or Psychological Assessment.

Technology Areas

  • AI & ML