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Compressed multi-contrast magnetic resonance image reconstruction using augmented lagrangian method

Gungor, Alper, Kopanoglu, Emre, Cukur, Tolga and Guven, H. Emre 2016. Compressed multi-contrast magnetic resonance image reconstruction using augmented lagrangian method. Presented at: 2016 24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Turkey, 16-19 May 2016. 2016 24th Signal Processing and Communication Application Conference (SIU). IEEE, 10.1109/SIU.2016.7496157

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Abstract

In this paper, a Multi-Channel/Multi-Contrast image reconstruction algorithm is proposed. The method, which is based on the Augmented Lagrangian Method uses joint convex objective functions to utilize the mutual information in the data from multiple channels to improve reconstruction quality. For this purpose, color total variation and group sparsity are used. To evaluate the performance of the method, the algorithm is compared in terms of convergence speed and image quality using Magnetic Resonance Imaging data to FCSA-MT [1], an alternative approach on reconstructing multi-contrast MRI data.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Cardiff University Brain Research Imaging Centre (CUBRIC)
Psychology
Language other than English: Turkish
Publisher: IEEE
ISBN: 978-1-5090-1679-2
Last Modified: 08 Jul 2019 08:47
URI: http://orca.cf.ac.uk/id/eprint/101052

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