On the generalized inverse for MRI reconstruction

Tzu Hsueh Tsai, Hsin Chia Chen, Hao Chiao Yang, Yu Chieh Chao, Jyh Miin Lin, Chih Ching Chen, Hing Chiu Chang, Chin Kuo Chang, Wei Hsuan Yu, Feng Nan Hwang, Martin Graves

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

Recent studies have suggested that the boundary between data-driven deep-learning non-Cartesian magnetic resonance imaging (MRI) reconstruction methods and conventional optimization-based, iterative reconstruction methods is becoming blurred. For instance, the unrolled iterative reconstruction method can be regarded as a trainable neural network. Another example is that the Moore-Penrose pseudoinverse plays a central role in finding the predefined solution to many imaging processes. However, the application of pseudoinverse in MRI reconstruction was obstructed in clinical imaging, mostly due to the excessive storage required for singular vectors. Since the spatial encoding of MRI is fully determined by the known k-space trajectory, the generalized inverse can be 'iteratively learning in a data-free fashion', which leads to surprising but realizable properties. To compare our method with other conventional methods, numerical simulations were performed using in vivo MRI. The proposed method leads to nearly equivalent image quality with a much shorter run-time (only 0.68%) than the conjugate gradient (CG) method. We discuss the potential impact of the generalized inverse as a feasible reconstruction method for non-Cartesian MRI.

原文???core.languages.en_GB???
主出版物標題BMEiCON 2022 - 14th Biomedical Engineering International Conference
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781665489034
DOIs
出版狀態已出版 - 2022
事件14th Biomedical Engineering International Conference, BMEiCON 2022 - Virtual, Online, Thailand
持續時間: 10 11月 202213 11月 2022

出版系列

名字BMEiCON 2022 - 14th Biomedical Engineering International Conference

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???event.eventtypes.event.conference???14th Biomedical Engineering International Conference, BMEiCON 2022
國家/地區Thailand
城市Virtual, Online
期間10/11/2213/11/22

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