title: Automated method for identification of patients with Alzheimer's disease based on three-dimensional MR images.
abstract: OBJECTIVE
  An automated method for identification of patients with cerebral atrophy due to Alzheimer's disease (AD) was developed based on three-dimensional (3D) T1-weighted magnetic resonance (MR) images.
  
  
  METHODS
  Our proposed method consisted of determination of atrophic image features and identification of AD patients. The atrophic image features included white matter and gray matter volumes, cerebrospinal fluid (CSF) volume, and cerebral cortical thickness determined based on a level set method. The cortical thickness was measured with normal vectors on a voxel-by-voxel basis, which were determined by differentiating a level set function. The CSF spaces within cerebral sulci and lateral ventricles (LVs) were extracted by wrapping the brain tightly in a propagating surface determined with a level set method. Identification of AD cases was performed using a support vector machine (SVM) classifier, which was trained by the atrophic image features of AD and non-AD cases, and then an unknown case was classified into either AD or non-AD group based on an SVM model. We applied our proposed method to MR images of the whole brains obtained from 54 cases, including 29 clinically diagnosed AD cases (age range, 52-82 years; mean age, 70 years) and 25 non-AD cases (age range, 49-78 years; mean age, 62 years).
  
  
  RESULTS
  As a result, the area under a receiver operating characteristic (ROC) curve (Az value) obtained by our computerized method was 0.909 based on a leave-one-out test in identification of AD cases among 54 cases.
  
  
  CONCLUSIONS
  This preliminary result showed that our method may be promising for detecting AD patients.
authors.affiliation: Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Fukuoka 812-8582, Japan. arimura@shs.kyushu-u.ac.jp
authors.forename: Hidetaka
authors.initials: H
authors.lastname: Arimura
authors.forename: Takashi
authors.initials: T
authors.lastname: Yoshiura
authors.forename: Seiji
authors.initials: S
authors.lastname: Kumazawa
authors.forename: Kazuhiro
authors.initials: K
authors.lastname: Tanaka
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Koga
authors.forename: Futoshi
authors.initials: F
authors.lastname: Mihara
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Honda
authors.forename: Shuji
authors.initials: S
authors.lastname: Sakai
authors.forename: Fukai
authors.initials: F
authors.lastname: Toyofuku
authors.forename: Yoshiharu
authors.initials: Y
authors.lastname: Higashida
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000544:Alzheimer Disease / Q000134:cerebrospinal fluid / Q000175:diagnosis* / Q000473:pathology; D019540:Area Under Curve; D001284:Atrophy; D001921:Brain / Q000473:pathology*; D016022:Case-Control Studies; D002540:Cerebral Cortex / Q000473:pathology; D005103:Expert Systems; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D020547:Lateral Ventricles / Q000473:pathology; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D012372:ROC Curve