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Cardiac MRI compressed sensing image reconstruction with a graphics processing unit

Majid Sabbagh, Martin Uecker, Andrew J. Powell, Miriam Leeser, Mehdi H. Moghari
2016 2016 10th International Symposium on Medical Information and Communication Technology (ISMICT)  
CPU Central Processing Unit GPU Graphics Processing Unit MIC Many Integrated Core FPGA Field Programmable Gate Array MRI Magnetic Resonance Imaging RF Radio Frequency CS Compressed Sensing  ...  In Chapter 2, we present background on MRI and compressed sensing image reconstruction algorithm as well as related work.  ... 
doi:10.1109/ismict.2016.7498891 dblp:conf/ismict/SabbaghUPLM16 fatcat:gtoybnqx6zc3db7kj5cto3l33q

Fast Cardiac CINE MRI by Iterative Truncation of Small Transformed Coefficients

Jinho Park, Hye-Jin Hong, Young-Joong Yang, Chang-Beom Ahn
2015 Investigative Magnetic Resonance Imaging  
Acknowledgment This work was supported in part by a National Research  ...  The algorithm is adequate for parallel processing, especially with a graphic processing unit (GPU) with massively parallel processors.  ...  Fig. 1 . 1 Test data sets for cardiac CINE MRI for evaluation of the compressed sensing technique with other imaging methods. b a Fast Cardiac CINE MRI by ITSC | Jinho Park, et al.  ... 
doi:10.13104/imri.2015.19.1.19 fatcat:2ageq3dtszbjteux3ly375sk4y

Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning [article]

Joseph Y. Cheng, Feiyu Chen, Christopher Sandino, Morteza Mardani, John M. Pauly, Shreyas S. Vasanawala
2019 arXiv   pre-print
Compressed sensing in MRI enables high subsampling factors while maintaining diagnostic image quality. This technique enables shortened scan durations and/or improved image resolution.  ...  As a result, compressed sensing can have greater clinical impact.  ...  Introduction Compressed sensing is a powerful tool in magnetic resonance imaging (MRI).  ... 
arXiv:1903.07824v1 fatcat:hizgf5xjkjab5ni5thzihr466m

Parallel Computing of Patch-Based Nonlocal Operator and Its Application in Compressed Sensing MRI

Qiyue Li, Xiaobo Qu, Yunsong Liu, Di Guo, Jing Ye, Zhifang Zhan, Zhong Chen
2014 Computational and Mathematical Methods in Medicine  
But the computation time of compressed sensing magnetic resonance imaging (CS-MRI) is relatively long due to its iterative reconstruction process.  ...  Magnetic resonance imaging has been benefited from compressed sensing in improving imaging speed.  ...  Michael Lustig for sharing spare MRI code and Dr. Jong Chul Ye for sharing cardiac data used in Figure 4  ... 
doi:10.1155/2014/257435 pmid:24963335 pmcid:PMC4054895 fatcat:quh6y7yrcrhj3g2tfpjsxtxybu

Assessment of Left Ventricular Function and Mass on Free-Breathing Compressed Sensing Real-Time Cine Imaging

Tomoyuki Kido, Teruhito Kido, Masashi Nakamura, Kouki Watanabe, Michaela Schmidt, Christoph Forman, Teruhito Mochizuki
2017 Circulation Journal  
Compressed sensing (CS) cine magnetic resonance imaging (MRI) has the advantage of being inherently insensitive to respiratory motion.  ...  Conclusions: Despite underestimation of LV mass, FB CS cine MRI is a clinically useful alternative to BH standard cine MRI in patients with impaired BH capacity.  ...  Acknowledgments The authors are grateful to Yoshiaki Komori and Yuta Urushibata (Siemens Healthcare, Tokyo, Japan) for their help with optimization of sequence parameters and image quality.  ... 
doi:10.1253/circj.cj-17-0123 pmid:28515392 fatcat:dicn5dg3tje3lmry57bohrvjwe

Nonlinear inverse reconstruction for real-time MRI of the human heart using undersampled radial FLASH

Martin Uecker, Shuo Zhang, Jens Frahm
2010 Magnetic Resonance in Medicine  
While offline reconstructions required 1-2 sec, real-time applications with modified parameters and slightly lower image quality were achieved within 90 ms per graphical processing unit.  ...  and (iii) the use of a convolution-based iteration, which considerably simplifies the graphical processing unit implementation compared to a gridding technique.  ...  Because such computations are rather slow, one may consider the use of a graphical processing unit (GPU) to achieve reasonable reconstruction times.  ... 
doi:10.1002/mrm.22453 pmid:20512847 fatcat:q4waf5huyzfodlutfjpftuavqa

Whole-Heart Cine MRI in a Single Breath-Hold – A Compressed Sensing Accelerated 3D Acquisition Technique for Assessment of Cardiac Function

T. Wech, W. Pickl, J. Tran-Gia, C. Ritter, M. Beer, D. Hahn, H. Köstler
2013 RöFo. Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren (Print)  
The authors report on implementation of the demanding image reconstruction on a graphics processing unit (GPU) to substantially drive down the post-processing time.  ...  Whole-Heart Cine MRI in a Single Breath-Hold -A Compressed Sensing Accelerated 3D Acquisition Technique for Assessment of Cardiac Function.  ... 
doi:10.1055/s-0033-1350521 pmid:23996623 fatcat:qo5suzsc5bh6jp3r7lbm57gfye

From Compressed-Sensing to Artificial Intelligence-Based Cardiac MRI Reconstruction

Aurélien Bustin, Niccolo Fuin, René M. Botnar, Claudia Prieto
2020 Frontiers in Cardiovascular Medicine  
The underlying assumptions of established techniques such as compressed sensing and low-rank reconstruction are briefly summarized, while a greater focus is given to recent advances in dictionary learning  ...  Parallel imaging and compressed sensing undersampling reconstruction techniques have revolutionized the field, enabling 2- to 3-fold scan time accelerations to become standard in clinical practice.  ...  The overall reconstruction time with the residual 3D U-net implemented on graphics processing unit (GPU) was five times faster than conventional CS techniques implemented on CPU (74) .  ... 
doi:10.3389/fcvm.2020.00017 pmid:32158767 pmcid:PMC7051921 fatcat:xbge626jhzeulfjlssdlqnalze

A survey on deep learning in medical image reconstruction

Emmanuel Ahishakiye, Martin Bastiaan Van Gijzen, Julius Tumwiine, Ruth Wario, Johnes Obungoloch
2021 Intelligent Medicine  
[26] A reconstruction method using severely undersampled dynamic cardiac MRI data. It is 2x faster than compressed sensing-based methods. However, it does not apply to parallel imaging.  ...  [58] A framework based on Tensorflow for iterative reconstructions with data from real CT systems. The limitation is that it requires graphical processing units (GPUs).  ... 
doi:10.1016/j.imed.2021.03.003 fatcat:7orgevbcbvhabnluoforurxvna

High-Speed Compressed Sensing Reconstruction in Dynamic Parallel MRI Using Augmented Lagrangian and Parallel Processing

Çağdaş Bilen, Yao Wang, Ivan W. Selesnick
2012 IEEE Journal on Emerging and Selected Topics in Circuits and Systems  
It is also demonstrated that the proposed algorithm can be accelerated much further than other methods in case of a parallel implementation with graphics processing units (GPUs).  ...  It has been shown that a small fraction of the overall measurements are sufficient to reconstruct images with the combination of compressed sensing and parallel imaging.  ...  Sodickson from NYU Medical Center for their help and support as well as for providing the cardiac MRI dataset. We also thank Yilin Song for his assistance in performing the simulations.  ... 
doi:10.1109/jetcas.2012.2217032 fatcat:33khmke37jbpvozkis2lyagmvy

Block-based compressed sensing of MR images using multi-rate deep learning approach

Ejaz Ul Haq, Huang Jianjun, Xu Huarong, Kang Li
2021 Complex & Intelligent Systems  
In compressive sensing theory, a signal is efficiently reconstructed from very small and limited number of measurements.  ...  In block-based compressive sensing, a number of deep models are needed to train with each corresponding to different sampling rate.  ...  Compressive sensing theory There are two necessary steps involve in compressive sensing process (a) sampling process (2) reconstruction process.  ... 
doi:10.1007/s40747-021-00426-6 fatcat:fe7xvi2hwfaiph26tx4qltjifa

Reconstruction techniques for cardiac cine MRI

Rosa-María Menchón-Lara, Federico Simmross-Wattenberg, Pablo Casaseca-de-la-Higuera, Marcos Martín-Fernández, Carlos Alberola-López
2019 Insights into Imaging  
The present survey describes the state-of-the-art techniques for dynamic cardiac magnetic resonance image reconstruction.  ...  Thus, this paper aims to provide a general vision about cine MRI as the standard procedure in functional evaluation of the heart, focusing on technical methodologies.  ...  Dedicated computing devices, graphics processing units (GPUs) in particular, provide significant efficiency boosts and, therefore, improve the reconstruction speed [49, 50] .  ... 
doi:10.1186/s13244-019-0754-2 pmid:31549235 pmcid:PMC6757088 fatcat:s5574wj5pjadhbq5rah7k3h6lu

From Blackboard to Bedside: High-dimensional Geometry is Transforming the MRI Industry

David Donoho, Karen Saxe
2018 Notices of the American Mathematical Society  
Yet patients with arrhythmias and afib could get better treatment based on dynamic cardiac imaging; patients with aggressive prostate cancer could get much more accurate biopsies under 3-D MRI guidance  ...  Ambitious variations of MR imaging-such as dynamic cardiac imaging and 3-D MRI-require far longer scan times than simple 2-D imaging; such long scan times have typically been awkward or even prohibitive  ...  Improving MRI, by whatever means-mathematical ideas like compressed sensing, or physical ingredients like more powerful magnets-is always a gradual process of getting new equipment into the marketplace  ... 
doi:10.1090/noti1612 fatcat:as6qvti7enhfhhxyiu2kqauuey

Comprehensive Multi-Dimensional MRI for the Simultaneous Assessment of Cardiopulmonary Anatomy and Physiology

Joseph Y. Cheng, Tao Zhang, Marcus T. Alley, Martin Uecker, Michael Lustig, John M. Pauly, Shreyas S. Vasanawala
2017 Scientific Reports  
We constructed a compressive-sensing approach to pseudo-randomly acquire highly subsampled, multi-dimensionallyencoded and time-stamped data from which we reconstruct volumetric cardiac and respiratory  ...  tomography or magnetic resonance imaging (MRI) exam for cardiac evaluation.  ...  Tamir for their assistance in software development for the image reconstruction.  ... 
doi:10.1038/s41598-017-04676-8 pmid:28706270 pmcid:PMC5509743 fatcat:icu6y2de65bedl224h4pvvt63i

CRDN: Cascaded Residual Dense Networks for Dynamic MR Imaging with Edge-enhanced Loss Constraint [article]

Ziwen Ke, Shanshan Wang, Huitao Cheng, Leslie Ying, Qiegen Liu, Hairong Zheng, Dong Liang
2019 arXiv   pre-print
Most existing methods reconstruct Dynamic MR images from incomplete k-space data under the guidance of compressed sensing (CS) or low rank theory, which suffer from long iterative reconstruction time.  ...  Nevertheless, there was still a certain degree of smooth in the reconstructed images at high acceleration factors.  ...  CS-MRI and CNN-MRI According to compressed sensing (CS) [3, 4] , MR images with a sparse representation in some transform domain can be reconstructed from randomly undersampled k-space data.  ... 
arXiv:1901.06111v1 fatcat:3d7dacr2wjbznkkdzucinimjvu
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