Aigerim Djamanakova1, Andreia V. Faria2, Kenichi Oishi2, Xin Li2, Kazi Akhter2, Laurent Younes3,4, Peter van Zijl2,5, Michael Ira Miller3, Susumu Mori2
1Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, United States; 2Radiology, Johns Hopkins University, Baltimore, MD, United States; 3Center for Imaging Science, The Johns Hopkins University, Baltimore, MD, United States; 4Applied Mathematics & Statistics, Johns Hopkins University, Baltimore, MD, United States; 5F.M. Kirby Center for Functional Magnetic Resonance Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
We used Large Deformation Diffeomorphic Metric Mapping in order to improve the registration of brains with enlarged ventricles from patients with Alzheimer's disease . By employing a second channel of information comprised of the lateral ventricle segmentation maps, obtained semi-automatically and automatically, we were able to increase the accuracy of the mappings. The degree of accuracy was calculated by comparing the results of the manual segmentation of lateral ventricles and a neighboring structure, lingual gyrus, with the single and dual-channel registration-based segmentation. This approach can be a powerful tool for improving registration of images.