Inproceedings: An article in a conference proceedings.
Efficient total variation algorithm for fetal MRI reconstruction
Title of the conference
17th International Conference on Medical Image Computing and Computer Assisted Intervention
Massachusetts Inst Technol, Boston, MA, Sep 14-18, 2014
Lecture Notes in Computer Science
Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy , Total Variation (TV)based energies [2,3] and more recently non-local means . Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.
fetal imaging, magnetic resonance, image reconstruction, super-resolution, total-variation, optimisation
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