Abstract：
:This paper presents an algorithm to transform and reconstruct diffusion-weighted imaging (DWI) data for alignment of micro-structures in association with spatial transformations. The key idea is to decompose the diffusion signal profile, a function defined on a unit sphere, into a series of weighted diffusion basis functions (DBFs), reorient these weighted DBFs independently based on the local affine transformation, and then recompose the reoriented weighted DBFs to obtain the final transformed diffusion signal profile. The decomposition is performed in a sparse representation framework in recognition of the fact that each diffusion signal profile is often resulting from a small number of fiber populations. A non-negative constraint is further imposed so that noise-induced negative lobes in the profile can be avoided. The proposed framework also explicitly models the isotropic component of the diffusion signals to avoid undesirable artifacts during transformation. In contrast to existing methods, the current algorithm allows the transformation to be executed directly in the signal space, thus allowing any diffusion models to be fitted to the data after transformation.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Yap PT,Shen Ddoi
10.1109/TMI.2012.2204766subject
Has Abstractpub_date
2012-11-01 00:00:00pages
2035-49issue
11eissn
0278-0062issn
1558-254Xjournal_volume
31pub_type
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