A synthesis-based approach to compressive multi-contrast magnetic resonance imaging
Date
2017Source Title
Proceedings of the IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017
Print ISSN
1945-7928
Publisher
IEEE
Pages
696 - 699
Language
English
Type
Conference PaperItem Usage Stats
228
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192
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Abstract
In this study, we deal with the problem of image reconstruction from compressive measurements of multi-contrast magnetic resonance imaging (MRI). We propose a synthesis based approach for image reconstruction to better exploit mutual information across contrasts, while retaining individual features of each contrast image. For fast recovery, we propose an augmented Lagrangian based algorithm, using Alternating Direction Method of Multipliers (ADMM). We then compare the proposed algorithm to the state-of-the-art Compressive Sensing-MRI algorithms, and show that the proposed method results in better quality images in shorter computation time.
Keywords
ADMMCompressive sensing
Multi-contrast magnetic resonance imaging
Constrained optimization
Image processing
Image reconstruction
Magnetism
Medical imaging
Optimization
Resonance
Signal reconstruction
Alternating direction method of multipliers
Augmented lagrangians
Compressive measurements
Individual features
Mutual informations
Synthesis-based approaches
Magnetic resonance imaging