Slab boundary artifact correction in multislab imaging using convolutional‐neural‐network–enabled inversion for slab profile encoding

Purpose This study aims to propose a novel algorithm for slab boundary artifact correction in both single‐band multislab imaging and simultaneous multislab (SMSlab) imaging. Theory and Methods In image domain, the formation of slab boundary artifacts can be regarded as modulating the artifact‐free i...

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Veröffentlicht in:	Magnetic resonance in medicine 2022-03, Vol.87 (3), p.1546-1560
Hauptverfasser:	Zhang, Jieying, Liu, Simin, Dai, Erpeng, Ye, Xinyu, Shi, Diwei, Wu, Yuhsuan, Lu, Jie, Guo, Hua
Format:	Artikel
Sprache:	eng
Schlagworte:	3D multislab Algorithms Artificial neural networks Brain - diagnostic imaging deep learning Functional magnetic resonance imaging Humans Image acquisition Image Processing, Computer-Assisted Inverse problems Inversion Iterative algorithms Iterative methods Magnetic Resonance Imaging model‐based CNN Neural networks Neural Networks, Computer Robustness (mathematics) simultaneous multislab slab boundary artifacts
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