Magnetic resonance image reconstruction by nullspace based finite rate of innovation framework

Mapping Intimacies ◽

10.1145/3490035.3490294 ◽

2021 ◽

Author(s):

P Sudhakar Reddy ◽

B S Raghavendra ◽

A V Narasimhadhan

Keyword(s):

Magnetic Resonance ◽

Image Reconstruction ◽

Magnetic Resonance Image ◽

Finite Rate ◽

Finite Rate Of Innovation

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Deep learning in magnetic resonance image reconstruction

Journal of Medical Imaging and Radiation Oncology ◽

10.1111/1754-9485.13276 ◽

2021 ◽

Author(s):

Shekhar S Chandra ◽

Marlon Bran Lorenzana ◽

Xinwen Liu ◽

Siyu Liu ◽

Steffen Bollmann ◽

...

Keyword(s):

Deep Learning ◽

Magnetic Resonance ◽

Image Reconstruction ◽

Magnetic Resonance Image

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Detecting spontaneous brain activity in functional magnetic resonance imaging using finite rate of innovation

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) ◽

10.1109/isbi.2014.6868053 ◽

2014 ◽

Author(s):

Zafer Dogan ◽

Thierry Blu ◽

Dimitri Van De Ville

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Functional Magnetic Resonance Imaging ◽

Brain Activity ◽

Functional Magnetic Resonance ◽

Resonance Imaging ◽

Finite Rate ◽

Spontaneous Brain Activity ◽

Finite Rate Of Innovation

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Multi-contrast magnetic resonance image reconstruction

10.1117/12.2082136 ◽

2015 ◽

Author(s):

Meng Liu ◽

Yunmei Chen ◽

Hao Zhang ◽

Feng Huang

Keyword(s):

Magnetic Resonance ◽

Image Reconstruction ◽

Magnetic Resonance Image ◽

Contrast Magnetic Resonance

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Enhanced Deep-Learning-Based Magnetic Resonance Image Reconstruction by Leveraging Prior Subject-Specific Brain Imaging: Proof-of-Concept Using a Cohort of Presumed Normal Subjects

IEEE Journal of Selected Topics in Signal Processing ◽

10.1109/jstsp.2020.3001525 ◽

2020 ◽

Vol 14 (6) ◽

pp. 1126-1136

Author(s):

Roberto Souza ◽

Youssef Beauferris ◽

Wallace Loos ◽

Robert Marc Lebel ◽

Richard Frayne

Keyword(s):

Deep Learning ◽

Magnetic Resonance ◽

Image Reconstruction ◽

Brain Imaging ◽

Magnetic Resonance Image ◽

Normal Subjects ◽

Proof Of Concept ◽

Subject Specific

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IKWI-net: A cross-domain convolutional neural network for undersampled magnetic resonance image reconstruction

Magnetic Resonance Imaging ◽

10.1016/j.mri.2020.06.015 ◽

2020 ◽

Vol 73 ◽

pp. 1-10

Author(s):

Zhilun Wang ◽

Haitao Jiang ◽

Hongwei Du ◽

Jinzhang Xu ◽

Bensheng Qiu

Keyword(s):

Neural Network ◽

Magnetic Resonance ◽

Image Reconstruction ◽

Convolutional Neural Network ◽

Magnetic Resonance Image ◽

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Adaptive Transform Learning and Joint Sparsity Based PLORAKS Parallel Magnetic Resonance Image Reconstruction

IEEE Access ◽

10.1109/access.2020.3039527 ◽

2020 ◽

Vol 8 ◽

pp. 212315-212326

Author(s):

Jizhong Duan ◽

Chang Liu ◽

Yu Liu ◽

Zhenhong Shang

Keyword(s):

Magnetic Resonance ◽

Image Reconstruction ◽

Magnetic Resonance Image ◽

Joint Sparsity ◽

Adaptive Transform

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Accelerating Parallel Magnetic Resonance Image Reconstruction on Graphics Processing Units Using CUDA

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) ◽

10.1109/infoct.2019.8710946 ◽

2019 ◽

Author(s):

Omair Inam ◽

Mahmood Qureshi ◽

Hamza Akram ◽

Hammad Omer ◽

Zoia Laraib

Keyword(s):

Magnetic Resonance ◽

Image Reconstruction ◽

Magnetic Resonance Image ◽

Graphics Processing Units ◽

Graphics Processing

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Magnetic resonance image reconstruction from non-equidistantly sampled data

1997 IEEE International Conference on Acoustics, Speech, and Signal Processing ◽

10.1109/icassp.1997.595378 ◽

2002 ◽

Author(s):

Ning Li ◽

T. Adali ◽

M. NessAiver

Keyword(s):

Magnetic Resonance ◽

Image Reconstruction ◽

Magnetic Resonance Image ◽

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Magnetic resonance image reconstruction via L0-norm minimization

2015 IET International Conference on Biomedical Image and Signal Processing (ICBISP 2015) ◽

10.1049/cp.2015.0780 ◽

2015 ◽

Author(s):

H. Chen ◽

Y. Sun ◽

J. Tao ◽

B. Qiu ◽

Z. Ye

Keyword(s):

Magnetic Resonance ◽

Image Reconstruction ◽

Magnetic Resonance Image ◽

Norm Minimization

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Ultrasound image reconstruction using the finite-rate-of-innovation principle

2014 IEEE International Conference on Image Processing (ICIP) ◽

10.1109/icip.2014.7025346 ◽

2014 ◽

Author(s):

Satish Mulleti ◽

Sudarshan Nagesh ◽

Rajesh Langoju ◽

Abhijit Patil ◽

Chandra Sekhar Seelamantula

Keyword(s):

Image Reconstruction ◽

Ultrasound Image ◽

Finite Rate ◽

Finite Rate Of Innovation

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