Large Deformation Diffeomorphic Registration of Diffusion-Weighted Imaging Data

TitleLarge Deformation Diffeomorphic Registration of Diffusion-Weighted Imaging Data
Publication TypeJournal Article
Year of Publication2014
AuthorsZhang P, Niethammer M, Shen D, Yap P-T
JournalMedical Image Analysis

Registration plays an important role in group analysis of diffusion-weighted imaging (DWI) data. It helps build a white matter anatomy that is crucial for investigating variation or tracking changes in white matter within a population. Unlike traditional scalar image registration where spatial alignment is the only focus, registration of DWI data requires both spatial alignment of structures and reorientation of local diffusivity profiles. As such, DWI registration is much more complex and challenging than scalar image registration. Although a variety of algorithms has been proposed to tackle the problem, most of them are restricted by the diffusion model used for registration, making it difficult to fit to the registered data a different model. In this paper we describe a method that allows any diffusion model to be fitted after registration for subsequent multifaceted analysis. This is achieved by directly aligning DWI data using a large deformation diffeomorphic registration framework. Our algorithm seeks the optimal coordinate mapping by simultaneously considering structural alignment, local diffusivity profile reorientation, and deformation regularization. Our algorithm also incorporates a multikernel strategy to concurrently register anatomical structures of different scales. We demonstrate the efficacy of our approach using in vivo data and report detailed qualitative and quantitative results in comparison with several different registration strategies.

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