Abstract
AbstractNonlinear registration plays a central role in most neuroimage analysis methods and pipelines, such as in tractography-based individual and group-level analysis methods. However, nonlinear registration is a non-trivial task, especially when dealing with tractography data that digitally represent the underlying anatomy of the brain’s white matter. Furthermore, such process often changes the structure of the data, causing artifacts that can suppress the underlying anatomical and structural details. In this paper, we introduce BundleWarp, a novel and robust streamline-based nonlinear registration method for the registration of white matter tracts. BundleWarp intelligently warps two bundles while preserving the bundles’ crucial topological features. BundleWarp has two main steps. The first step involves the solution of an assignment problem that matches corresponding streamlines from the two bundles (iterLAP step). The second step introduces streamline-specific point-based deformations while keeping the topology of the bundle intact (mlCPD step).We provide comparisons against streamline-based linear registration and image-based nonlinear registration methods. BundleWarp quantitatively and qualitatively outperforms both, and we show that Bundle-Warp can deform and, at the same time, preserve important characteristics of the original anatomical shape of the bundles. Results are shown on 1,728 pairs of bundle registrations across 27 different bundle types. In addition, we present an application of BundleWarp for quantifying bundle shape differences using the generated deformation fields.
Publisher
Cold Spring Harbor Laboratory
Reference69 articles.
1. Diffusion tensor imaging of the brain
2. Non-linear registration, aka spatial normalisation fmrib technical report tr07ja2;FMRIB Analysis Group of the University of Oxford,2007
3. A fast and log-euclidean polyaffine framework for locally linear registration;Journal of Mathematical Imaging and Vision,2009
4. Advanced normalization tools (ANTS);Insight J,2009
5. Methodological considerations on tract-based spatial statistics (TBSS)
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