FOD-Based registration for susceptibility distortion correction in connectome imaging

Abstract

Multi-shell, high resolution diffusion MRI (dMRI) data from the Human Connectome Project (HCP) provides an unprecedented opportunity for the in vivo mapping of human brain pathways. It was recently noted, however, that significant distortions remain present in the data of most subjects preprocessed by the HCP-Pipeline, which have been widely distributed and used extensively in connectomics research. Fundamentally this is caused by the reliance of the HCP tools on the B0 images for registering data from different phase encodings (PEs). In this work, we develop an improved framework to remove the residual distortion in data generated by the HCP-Pipeline. Our method is based on more advanced registration of fiber orientation distribution (FOD) images, which represent information of dMRI scans from all gradient directions and thus provide more reliable contrast to align data from different PEs. In our experiments, we focus on the brainstem area and compare our method with the preprocessing steps in the HCP-Pipeline. We show that our method can provide much improved distortion correction and generate FOD images with more faithful representation of brain pathways.