Luke Bloy1, Madhura Ingalhalikar2, Robert T. Schultz3, Timothy P.L. Roberts4, Ragini Verma2
1Section of Biomedical Imaging, University of Pennsylvania, Philadelphia, PA, United States; 2Section of Biomedical Imaging, Univeristy of Pennsylvania, Philadelphia, PA, United States; 3Center for Autism Research, Children's Hospital of Philadelphia, Philadelphia, PA, United States; 4Lurie Family Foundation's MEG Imaging Center, Children's Hospital of Philadelphia, Philadelphia, PA, United States
We create and compare an automated atlas creation method applied to DTI and HARDI data. The method works by generating a population average DTI dataset which is then parcellated using a normalized cuts segmentation algorithm. The framework is demonstration through its application to a population of adolescent subjects. The resultant atlas is compared to one created using HARDI datasets acquired on the same subjects. The HARDI atlas is better able to capture regions of cortical WM and those of complex WM such as fiber crossings. Additionally, these two atlases can be used in a population for comparative analysis between modalities.