MR images were processed using our locally developed BRAINS2 (Brain Research: Analysis of Images, Networks, and Systems, Version 2) software package (Magnotta et al., 2002). Detailed descriptions of image analysis methods have been provided elsewhere (Andreasen et al., 1993; Andreasen et al., 1994; Andreasen et al., 1996; Harris et al., 1999). In brief, the T1-weighted images were spatially normalized and re-sampled so that the anterior-posterior axis of the brain was realigned parallel to the anterior-posterior commissure line, and the interhemispheric fissure was aligned on the other two axes. The T2-weighted images were aligned to the spatially normalized T1-weighted image using an automated image registration program (Woods, Cherry, & Mazziotta, 1992). These images were then subjected to a linear transformation into standardized stereotaxic Talairach atlas space (Talairach & Tournoux, 1988) to generate automated measurements of frontal, temporal, parietal and occipital lobes (Andreasen et al., 1996). To further classify tissue volumes into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), we employed a discriminant analysis method of tissue segmentation based on automated training class selection that utilized data from the
