9 March 2010 Computer-aided classification of patients with dementia of Alzheimer's type based on cerebral blood flow determined with arterial spin labeling technique
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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 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.
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Yasuo Yamashita, Yasuo Yamashita, Hidetaka Arimura, Hidetaka Arimura, Takashi Yoshiura, Takashi Yoshiura, Chiaki Tokunaga, Chiaki Tokunaga, Taiki Magome, Taiki Magome, Akira Monji, Akira Monji, Tomoyuki Noguchi, Tomoyuki Noguchi, Fukai Toyofuku, Fukai Toyofuku, Masafumi Oki, Masafumi Oki, Yasuhiko Nakamura, Yasuhiko Nakamura, Hiroshi Honda, Hiroshi Honda, } "Computer-aided classification of patients with dementia of Alzheimer's type based on cerebral blood flow determined with arterial spin labeling technique", Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 76241J (9 March 2010); doi: 10.1117/12.845530; https://doi.org/10.1117/12.845530
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