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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


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.

Original languageEnglish
Title of host publicationBMEiCON 2022 - 14th Biomedical Engineering International Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665489034
StatePublished - 2022
Event14th Biomedical Engineering International Conference, BMEiCON 2022 - Virtual, Online, Thailand
Duration: 10 Nov 202213 Nov 2022

Publication series

NameBMEiCON 2022 - 14th Biomedical Engineering International Conference


Conference14th Biomedical Engineering International Conference, BMEiCON 2022
CityVirtual, Online


  • Moore-Penrose pseudoinverse
  • generalized inverse
  • neural network


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