Abstract

Recently, 3-D imaging and computer-intensive analysis have revolutionized the study of normal human neuroanatomy and information processing. 3-D images of anatomy (MRI) and function (PET, MRI) are resampled into a standardized coordinate space which allows quantitative cross-subject comparison. Coordinate transformation may be linear or employ image-warping algorithms to overcome residual anatomical differences evident in the MRI data. Within the standardized space, image segmentation algorithms label voxels according to tissue type (e.g. gray or white matter), anatomical region (e.g. thalamus) or cortical feature (e.g. pre-central sulcus). Population analysis then generates probabilistic atlases for each sub-class.

© 1993 Optical Society of America