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More IMPATIENT: A gridding-accelerated Toeplitz-based strategy for non-Cartesian high-resolution 3D MRI on GPUs
Open accessAbstract
Several recent methods have been proposed to obtain significant speed-ups in MRI image reconstruction by leveraging the computational power of GPUs. Previously, we implemented a GPU-based image reconstruction technique called the Illinois Massively Parallel Acquisition Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI) for reconstructing data collected along arbitrary 3D trajectories. In this paper, we improve IMPATIENT by removing computational bottlenecks by using a gridding approach to accelerate the computation of various data structures needed by the previous routine. Further, we enhance the routine with capabilities for off-resonance correction and multi-sensor parallel imaging reconstruction. Through implementation of optimized gridding into our iterative reconstruction scheme, speed-ups of more than a factor of 200 are provided in the improved GPU implementation compared to the previous accelerated GPU code.
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“Monte ve diğerleri [41] Monte Karlo yöntemini GPU paralel programlama teknikleri kullanarak uygulamakta ve seri algoritma ile paralel algoritmanın işlem sürelerini karşılaştırmaktadırlar.”
From GPU Programlamada CUDA Platformu Kullanılan Paralel Görüntü İşleme Çalışmalarının İncelenmesi (2020) · cites this paper as [41]
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GPU Programlamada CUDA Platformu Kullanılan Paralel Görüntü İşleme Çalışmalarının İncelenmesi
AYDIN, S., SAMET, R., & BAY, Ö. F. (2020) · Politeknik Dergisi · doi:10.2339/politeknik.563767 · Cited by 3
“Environment”, Procedia Computer Science, 18: 1402– 1411, (2013) [42] Gai J.”
Metadata
- Authors
- Gai, J., Obeid, N., Holtrop, J. L., Wu, X.-L., Lam, F., Fu, M., Haldar, J. P., Hwu, W.-M. W., Liang, Z.-P., & Sutton, B. P.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- University of Southern California (US)
- Corresponding author
- Sutton, Bradley P.
- Venue
- Journal of Parallel and Distributed Computing
- Publisher
- Elsevier BV
- Published
- 2013-05
- Volume
- 73
- Issue
- 5
- Pages
- 686-697
- ISSN
- 0743-7315 (ISSN-L)
- PMC
- PMC3652469
- OpenAlex
- W2080236984
- Cited by
- 43
- References
- 38
- Citations by year
- 2026: 2 · 2025: 2 · 2022: 1 · 2021: 3 · 2020: 3 · 2019: 1 · 2018: 5 · 2017: 8 · 2016: 6 · 2015: 7 · 2014: 3 · 2013: 2
- FWCI
- 4.66
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Journal of Parallel and Distributed Computing (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Biomedical Imaging and Bioengineering (R21EB009768, R21EB010095)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Keywords
- Toeplitz matrices, 3D MRI reconstruction, iterative reconstruction, off-resonance correction
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- Gai, J., Obeid, N., Holtrop, J. L., Wu, X.-L., Lam, F., Fu, M., Haldar, J. P., Hwu, W.-M. W., Liang, Z.-P., & Sutton, B. P. (2013). More IMPATIENT: A gridding-accelerated Toeplitz-based strategy for non-Cartesian high-resolution 3D MRI on GPUs. Journal of Parallel and Distributed Computing. https://doi.org/10.1016/j.jpdc.2013.01.001
