Accurate and reliable labeling of regions of interest (ROIs) within structural magnetic resonance images (MRIs) is an important step in group analysis. Group registration does not always yield accurate alignment of homologous regions. We present an approach that distinguishes itself from other algorithms by being concerned with a label which is of the highest fidelity, while leaving ambiguous regions unlabeled. Regions that are not deemed to be reliably labeled are not included in group statistics. We will present results showing that our method is an improvement over traditional multi-atlas voting schemes. We conclude with a pilot study of longitudinal trends of cortical thickness in normal aging.
['Jing Wan', 'Aaron Carass', 'Susan M. Resnick', 'Jerry L. Prince']
Automated reliable labeling of the cortical surface