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Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction
Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction
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Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction

Qin, Chen ; Schlemper, Jo ; Caballero, Jose ; Price, Anthony N. ; Hajnal, Joseph V. ; Rueckert, Daniel

IEEE transactions on medical imaging, 2019-01, Vol.38 (1), p.280-290

United States: IEEE

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Assessment of the generalization of learned image reconstruction and the potential for transfer learning
Assessment of the generalization of learned image reconstruction and the potential for transfer learning
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Assessment of the generalization of learned image reconstruction and the potential for transfer learning

Knoll, Florian ; Hammernik, Kerstin ; Kobler, Erich ; Pock, Thomas ; Recht, Michael P ; Sodickson, Daniel K

Magnetic resonance in medicine, 2019-01, Vol.81 (1), p.116-128 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography. Part 1: Scatter compensation approaches
A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography. Part 1: Scatter compensation approaches
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A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography. Part 1: Scatter compensation approaches

Rührnschopf, Ernst-Peter ; Klingenbeck, Klaus

Medical Physics, 2011-07, Vol.38 (7), p.4296-4311 [Periódico revisado por pares]

United States: American Association of Physicists in Medicine

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A three-dimensional statistical approach to improved image quality for multislice helical CT
A three-dimensional statistical approach to improved image quality for multislice helical CT
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A three-dimensional statistical approach to improved image quality for multislice helical CT

Thibault, Jean-Baptiste ; Sauer, Ken D. ; Bouman, Charles A. ; Hsieh, Jiang

Medical physics (Lancaster), 2007-11, Vol.34 (11), p.4526-4544 [Periódico revisado por pares]

United States: American Association of Physicists in Medicine

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5
PWLS-ULTRA: An Efficient Clustering and Learning-Based Approach for Low-Dose 3D CT Image Reconstruction
PWLS-ULTRA: An Efficient Clustering and Learning-Based Approach for Low-Dose 3D CT Image Reconstruction
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PWLS-ULTRA: An Efficient Clustering and Learning-Based Approach for Low-Dose 3D CT Image Reconstruction

Zheng, Xuehang ; Ravishankar, Saiprasad ; Long, Yong ; Fessler, Jeffrey A.

IEEE transactions on medical imaging, 2018-06, Vol.37 (6), p.1498-1510

United States: IEEE

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Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer
Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer
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Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer

Knoll, Florian ; Holler, Martin ; Koesters, Thomas ; Otazo, Ricardo ; Bredies, Kristian ; Sodickson, Daniel K

IEEE transactions on medical imaging, 2017-01, Vol.36 (1), p.1-16

United States: IEEE

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7
Segmented simultaneous multi‐slice diffusion‐weighted imaging with navigated 3D rigid motion correction
Segmented simultaneous multi‐slice diffusion‐weighted imaging with navigated 3D rigid motion correction
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Segmented simultaneous multi‐slice diffusion‐weighted imaging with navigated 3D rigid motion correction

Riedel (né Steinhoff), Malte ; Setsompop, Kawin ; Mertins, Alfred ; Börnert, Peter

Magnetic resonance in medicine, 2021-09, Vol.86 (3), p.1701-1717 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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8
Free‐breathing high isotropic resolution quantitative susceptibility mapping (QSM) of liver using 3D multi‐echo UTE cones acquisition and respiratory motion‐resolved image reconstruction
Free‐breathing high isotropic resolution quantitative susceptibility mapping (QSM) of liver using 3D multi‐echo UTE cones acquisition and respiratory motion‐resolved image reconstruction
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Free‐breathing high isotropic resolution quantitative susceptibility mapping (QSM) of liver using 3D multi‐echo UTE cones acquisition and respiratory motion‐resolved image reconstruction

Kang, MungSoo ; Behr, Gerald G. ; Jafari, Ramin ; Gambarin, Maya ; Otazo, Ricardo ; Kee, Youngwook

Magnetic resonance in medicine, 2023-11, Vol.90 (5), p.1844-1858 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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9
MAIR-Net: a sparse-view CT reconstruction network based on a combination of mixed attention and iterative optimization learning
MAIR-Net: a sparse-view CT reconstruction network based on a combination of mixed attention and iterative optimization learning
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MAIR-Net: a sparse-view CT reconstruction network based on a combination of mixed attention and iterative optimization learning

Guo, Tong ; Liu, Yi ; Zhang, Pengcheng ; Liu, Yu ; Gui, Zhiguo

Journal of instrumentation, 2024-08, Vol.19 (8), p.P08029 [Periódico revisado por pares]

Bristol: IOP Publishing

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10
Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance
Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance
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Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

Li, Ke ; Tang, Jie ; Chen, Guang-Hong

Medical physics (Lancaster), 2014-04, Vol.41 (4), p.041906-n/a [Periódico revisado por pares]

United States: American Association of Physicists in Medicine

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