Neural network mapping for nonlinear stereotactic normalization of brain MR images.
We present techniques of automatic nonlinear transformation of MR images (2D or 3D). A neural network automatically finds the corresponding parts between the subject's brain images and the standard images. By iterative operations, the network generates a set of image-shifting vectors to realize a plastic transformation. For precise matching, a set of markers can be placed manually before starting the transformation on landmarks of the images, e.g., on the anterior-posterior commissural line and on the central sulcus.
Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama, Japan.
Y
Y
Kosugi
M
M
Sase
H
H
Kuwatani
N
N
Kinoshita
T
T
Momose
J
J
Nishikawa
T
T
Watanabe
D001931:Brain Mapping; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D016571:Neural Networks, Computer; D013238:Stereotaxic Techniques