Computer-aided classification of patients with dementia of Alzheimer's type based on cerebral blood flow determined with arterial spin labeling technique

Yasuo Yamashita, Hidetaka Arimura, Takashi Yoshiura, Chiaki Tokunaga, Taiki Magome, Akira Monji, Tomoyuki Noguchi, Fukai Toyofuku, Masafumi Oki, Yasuhiko Nakamura, Hiroshi Honda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Arterial spin labeling (ASL) is one of promising non-invasive magnetic resonance (MR) imaging techniques for diagnosis of Alzheimer's disease (AD) by measuring cerebral blood flow (CBF). The aim of this study was to develop a computer-aided classification system for AD patients based on CBFs measured by the ASL technique. The average CBFs in cortical regions were determined as functional image features based on the CBF map image, which was non-linearly transformed to a Talairach brain atlas by using a free-form deformation. An artificial neural network (ANN) was trained with the CBF functional features in 10 cortical regions, and was employed for distinguishing patients with AD from control subjects. For evaluation of the method, we applied the proposed method to 20 cases including ten AD patients and ten control subjects, who were scanned at a 3.0-Tesla MR unit. As a result, the area under the receiver operating characteristic curve obtained by the proposed method was 0.893 based on a leave-one-out-by-case test in identification of AD cases among 20 cases. The proposed method would be feasible for classification of patients with AD.

Original languageEnglish
Title of host publicationMedical Imaging 2010
Subtitle of host publicationComputer-Aided Diagnosis
EditorsRonald M. Summers, Nico Karssemeijer
PublisherSPIE
ISBN (Electronic)9780819480255
DOIs
Publication statusPublished - 2010
EventMedical Imaging 2010: Computer-Aided Diagnosis - San Diego, United States
Duration: Feb 16 2010Feb 18 2010

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7624
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2010: Computer-Aided Diagnosis
CountryUnited States
CitySan Diego
Period2/16/102/18/10

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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