Title
Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging Based on a Riemannian Manifold Approach.
Abstract
In this paper, we consider combined TV denoising and diffusion tensor fitting in DTI using the affine-invariant Riemannian metric on the space of diffusion tensors. Instead of first fitting the diffusion tensors, and then denoising them, we define a suitable TV type energy functional which incorporates the measured DWIs (using an inverse problem setup) and which measures the nearness of neighboring tensors in the manifold. To approach this functional, we propose generalized forwardbackward splitting algorithms which combine an explicit and several implicit steps performed on a decomposition of the functional.We validate the performance of the derived algorithms on synthetic and real DTI data. In particular, we work on real 3D data. To our knowledge, the present paper describes the first approach to TV regularization in a combined manifold and inverse problem setup.
Year
DOI
Venue
2016
10.1109/TMI.2016.2528820
IEEE Trans. Med. Imaging
Keywords
Field
DocType
Combined denoising and diffusion tensor fitting,diffusion tensor imaging,generalized forward-backward algorithm,manifold-valued data,total variation minimization
Mathematical optimization,Tensor (intrinsic definition),Tensor,Riemannian manifold,Symmetric tensor,Inverse problem,Energy functional,Tensor contraction,Manifold,Mathematics
Journal
Volume
Issue
ISSN
35
8
0278-0062
Citations 
PageRank 
References 
2
0.35
39
Authors
6
Name
Order
Citations
PageRank
Maximilian Baust115519.15
andreas weinmann213812.81
Matthias Wieczorek3183.28
Tobias Lasser49716.81
Martin Storath513812.69
Nassir Navab66594578.60