Classification of Parkinsonian syndromes from FDG-PET brain data using decision trees with SSM/PCA features.
Medical imaging techniques like fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to aid in the differential diagnosis of neurodegenerative brain diseases. In this study, the objective is to classify FDG-PET brain scans of subjects with Parkinsonian syndromes (Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy) compared to healthy controls. The scaled subprofile model/principal component analysis (SSM/PCA) method was applied to FDG-PET brain image data to obtain covariance patterns and corresponding subject scores. The latter were used as features for supervised classification by the C4.5 decision tree method. Leave-one-out cross validation was applied to determine classifier performance. We carried out a comparison with other types of classifiers. The big advantage of decision tree classification is that the results are easy to understand by humans. A visual representation of decision trees strongly supports the interpretation process, which is very important in the context of medical diagnosis. Further improvements are suggested based on enlarging the number of the training data, enhancing the decision tree method by bagging, and adding additional features based on (f)MRI data.
Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Nijenborgh 9, 9747 AG Groningen, Netherlands.
D
D
Mudali
Department of Neurology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB Groningen, Netherlands.
L K
LK
Teune
Neuroimaging Center, University Medical Center Groningen, University of Groningen, Antonius Deusinglaan 2, 9713 AW Groningen, Netherlands.
R J
RJ
Renken
Department of Neurology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB Groningen, Netherlands.
K L
KL
Leenders
Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Nijenborgh 9, 9747 AG Groningen, Netherlands ; Neuroimaging Center, University Medical Center Groningen, University of Groningen, Antonius Deusinglaan 2, 9713 AW Groningen, Netherlands.
J B T M
JB
Roerdink
D000368:Aged; D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods; D003663:Decision Trees; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000175:diagnosis* / Q000000981:diagnostic imaging; D049268:Positron-Emission Tomography; D025341:Principal Component Analysis; D012044:Regression Analysis
D019788:Fluorodeoxyglucose F18