TITLE:
Automated measurement of three-dimensional cerebral cortical thickness in Alzheimer’s patients using localized gradient vector trajectory in fuzzy membership maps
AUTHORS:
Chiaki Tokunaga, Hidetaka Arimura, Takashi Yoshiura, Tomoyuki Ohara, Yasuo Yamashita, Kouji Kobayashi, Taiki Magome, Yasuhiko Nakamura, Hiroshi Honda, Hideki Hirata, Masafumi Ohki, Fukai Toyofuku
KEYWORDS:
Alzheimer’s Disease (AD); Fuzzy C-Means Clustering (FCM); Three-Dimensional Cerebral Cortical Thickness; Localized Gradient Vector
JOURNAL NAME:
Journal of Biomedical Science and Engineering,
Vol.6 No.3A,
March
29,
2013
ABSTRACT: Our
purpose in this study was to develop an automated method for measuring
three-dimensional (3D) cerebral cortical thicknesses in patients with Alzheimer’s disease (AD) using magnetic resonance
(MR) images. Our proposed method consists of mainly three steps. First,
a brain parenchymal region was segmented based on brain model matching. Second,
a 3D fuzzy membership map for a cerebral cortical region was created by
applying a fuzzy c-means (FCM) clustering algorithm to T1-weighted MR images.
Third, cerebral cortical thickness was three- dimensionally measured on each
cortical surface voxel by using a localized gradient vector trajectory in a
fuzzy membership map. Spherical models with 3 mm artificial cortical regions,
which were produced using three noise levels of 2%, 5%, and 10%, were employed
to evaluate the proposed method. We also applied the proposed method to
T1-weighted images obtained from 20 cases, i.e.,
10 clinically diagnosed AD cases and 10 clinically normal (CN) subjects. The
thicknesses of the 3 mm artificial cortical regions for spherical models with
noise levels of 2%, 5%, and 10% were measured by the proposed method as 2.953 ±
0.342, 2.953 ± 0.342 and 2.952 ± 0.343 mm, respectively. Thus the mean
thicknesses for the entire cerebral lobar region were 3.1 ± 0.4 mm for AD patients
and 3.3 ± 0.4 mm for CN subjects, respectively (p