Accelerated Computing in Magnetic Resonance Imaging: Real-Time Imaging Using Nonlinear Inverse Reconstruction
Joint Authors
Frahm, Jens
Voit, Dirk
Schaetz, Sebastian
Uecker, Martin
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-31
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Purpose.
To develop generic optimization strategies for image reconstruction using graphical processing units (GPUs) in magnetic resonance imaging (MRI) and to exemplarily report on our experience with a highly accelerated implementation of the nonlinear inversion (NLINV) algorithm for dynamic MRI with high frame rates.
Methods.
The NLINV algorithm is optimized and ported to run on a multi-GPU single-node server.
The algorithm is mapped to multiple GPUs by decomposing the data domain along the channel dimension.
Furthermore, the algorithm is decomposed along the temporal domain by relaxing a temporal regularization constraint, allowing the algorithm to work on multiple frames in parallel.
Finally, an autotuning method is presented that is capable of combining different decomposition variants to achieve optimal algorithm performance in different imaging scenarios.
Results.
The algorithm is successfully ported to a multi-GPU system and allows online image reconstruction with high frame rates.
Real-time reconstruction with low latency and frame rates up to 30 frames per second is demonstrated.
Conclusion.
Novel parallel decomposition methods are presented which are applicable to many iterative algorithms for dynamic MRI.
Using these methods to parallelize the NLINV algorithm on multiple GPUs, it is possible to achieve online image reconstruction with high frame rates.
American Psychological Association (APA)
Schaetz, Sebastian& Voit, Dirk& Frahm, Jens& Uecker, Martin. 2017. Accelerated Computing in Magnetic Resonance Imaging: Real-Time Imaging Using Nonlinear Inverse Reconstruction. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1142068
Modern Language Association (MLA)
Schaetz, Sebastian…[et al.]. Accelerated Computing in Magnetic Resonance Imaging: Real-Time Imaging Using Nonlinear Inverse Reconstruction. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1142068
American Medical Association (AMA)
Schaetz, Sebastian& Voit, Dirk& Frahm, Jens& Uecker, Martin. Accelerated Computing in Magnetic Resonance Imaging: Real-Time Imaging Using Nonlinear Inverse Reconstruction. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1142068
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142068