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PROMISE: Parallel‐imaging and compressed‐sensing reconstruction of multicontrast imaging using SharablE information
Author(s) -
Gong Enhao,
Huang Feng,
Ying Kui,
Wu Wenchuan,
Wang Shi,
Yuan Chun
Publication year - 2015
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.25142
Subject(s) - computer science , artificial intelligence , compressed sensing , computer vision , pattern recognition (psychology) , sensitivity (control systems) , iterative reconstruction , robustness (evolution) , electronic engineering , engineering , biochemistry , chemistry , gene
Purpose A typical clinical MR examination includes multiple scans to acquire images with different contrasts for complementary diagnostic information. The multicontrast scheme requires long scanning time. The combination of partially parallel imaging and compressed sensing (CS‐PPI) has been used to reconstruct accelerated scans. However, there are several unsolved problems in existing methods. The target of this work is to improve existing CS‐PPI methods for multicontrast imaging, especially for two‐dimensional imaging. Theory and Methods If the same field of view is scanned in multicontrast imaging, there is significant amount of sharable information. It is proposed in this study to use manifold sharable information among multicontrast images to enhance CS‐PPI in a sequential way. Coil sensitivity information and structure based adaptive regularization, which were extracted from previously reconstructed images, were applied to enhance the following reconstructions. The proposed method is called Parallel‐imaging and compressed‐sensing Reconstruction Of Multicontrast Imaging using SharablE information (PROMISE). Results Using L 1 ‐SPIRiT as a CS‐PPI example, results on multicontrast brain and carotid scans demonstrated that lower error level and better detail preservation can be achieved by exploiting manifold sharable information. Besides, the privilege of PROMISE still exists while there is interscan motion. Conclusion Using the sharable information among multicontrast images can enhance CS‐PPI with tolerance to motions. Magn Reson Med 73:523–535, 2015. © 2014 Wiley Periodicals, Inc.