A Hybrid Diffusion Imaging Atlas in Q-space
暂无分享,去创建一个
Introduction A recent acquisition and diffusion encoding strategy, called hybrid diffusion imaging (HYDI) [1], consists of acquiring multiple shells of constant diffusion weighting. In the context of diffusion weighted imaging (DWI) in general (and HYDI in particular), the number of methods for atlas construction (and registration) is at least equal to the number of possible models which can be reconstructed from the original data in q-space. Therefore, we aim at constructing an atlas before the reconstruction of any of these models: a HYDI atlas containing signal functions for multiple shells of q-space. From this generalized atlas, any model can still be reconstructed to the fullest possible extent.
[1] F. Maes,et al. Spatial Transformations of High Angular Resolution Diffusion Imaging Data in Q-space , 2010 .
[2] Andrew L. Alexander,et al. Hybrid diffusion imaging , 2007, NeuroImage.
[3] Tom Vercauteren,et al. Diffeomorphic demons: Efficient non-parametric image registration , 2009, NeuroImage.