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Combined tensor fitting and TV regularization in diffusion tensor imaging based on a Riemannian manifold approach.
IEEE Trans. Med. Imaging 35, 1972-1989 (2016)
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.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Combined Denoising And Diffusion Tensor Fitting; Magnetic-resonance Images; Log-euclidean Metrics; Corpus-callosum; Valued Images; Dt-mri; Dissimilarity Measure; Bounded Variation; Least-squares; Weighted Mri; Segmentation
ISSN (print) / ISBN
0278-0062
e-ISSN
1558-254X
Quellenangaben
Volume: 35,
Issue: 8,
Pages: 1972-1989
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publishing Place
New York, NY [u.a.]
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)