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Self‐supervised learning of physics‐guided reconstruction neural networks without fully sampled reference data
Self‐supervised learning of physics‐guided reconstruction neural networks without fully sampled reference data
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Self‐supervised learning of physics‐guided reconstruction neural networks without fully sampled reference data

Yaman, Burhaneddin ; Hosseini, Seyed Amir Hossein ; Moeller, Steen ; Ellermann, Jutta ; Uğurbil, Kâmil ; Akçakaya, Mehmet

Magnetic resonance in medicine, 2020-12, Vol.84 (6), p.3172-3191 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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A Transfer‐Learning Approach for Accelerated MRI Using Deep Neural Networks
A Transfer‐Learning Approach for Accelerated MRI Using Deep Neural Networks
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A Transfer‐Learning Approach for Accelerated MRI Using Deep Neural Networks

Dar, Salman Ul Hassan ; Özbey, Muzaffer ; Çatlı, Ahmet Burak ; Çukur, Tolga

Magnetic resonance in medicine, 2020-08, Vol.84 (2), p.663-685 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise
Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise
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Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise

Mehranian, Abolfazl ; Wollenweber, Scott D. ; Walker, Matthew D. ; Bradley, Kevin M. ; Fielding, Patrick A. ; Su, Kuan-Hao ; Johnsen, Robert ; Kotasidis, Fotis ; Jansen, Floris P. ; McGowan, Daniel R.

European journal of nuclear medicine and molecular imaging, 2022-01, Vol.49 (2), p.539-549 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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4
Early Detection of Alzheimer’s Disease Using Magnetic Resonance Imaging: A Novel Approach Combining Convolutional Neural Networks and Ensemble Learning
Early Detection of Alzheimer’s Disease Using Magnetic Resonance Imaging: A Novel Approach Combining Convolutional Neural Networks and Ensemble Learning
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Early Detection of Alzheimer’s Disease Using Magnetic Resonance Imaging: A Novel Approach Combining Convolutional Neural Networks and Ensemble Learning

Pan, Dan ; Zeng, An ; Jia, Longfei ; Huang, Yin ; Frizzell, Tory ; Song, Xiaowei

Frontiers in neuroscience, 2020-05, Vol.14, p.259-259 [Periódico revisado por pares]

Lausanne: Frontiers Research Foundation

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Modeling the Influence of Data Structure on Learning in Neural Networks: The Hidden Manifold Model
Modeling the Influence of Data Structure on Learning in Neural Networks: The Hidden Manifold Model
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Modeling the Influence of Data Structure on Learning in Neural Networks: The Hidden Manifold Model

Goldt, Sebastian ; Mézard, Marc ; Krzakala, Florent ; Zdeborová, Lenka

Physical review. X, 2020-12, Vol.10 (4), p.041044, Article 041044 [Periódico revisado por pares]

College Park: American Physical Society

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Analysis of deep complex‐valued convolutional neural networks for MRI reconstruction and phase‐focused applications
Analysis of deep complex‐valued convolutional neural networks for MRI reconstruction and phase‐focused applications
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Analysis of deep complex‐valued convolutional neural networks for MRI reconstruction and phase‐focused applications

Cole, Elizabeth ; Cheng, Joseph ; Pauly, John ; Vasanawala, Shreyas

Magnetic resonance in medicine, 2021-08, Vol.86 (2), p.1093-1109 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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Multi-Classification of Brain Tumor Images Using Deep Neural Network
Multi-Classification of Brain Tumor Images Using Deep Neural Network
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Multi-Classification of Brain Tumor Images Using Deep Neural Network

Sultan, Hossam H. ; Salem, Nancy M. ; Al-Atabany, Walid

IEEE access, 2019, Vol.7, p.69215-69225 [Periódico revisado por pares]

Piscataway: IEEE

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Systematic evaluation of iterative deep neural networks for fast parallel MRI reconstruction with sensitivity‐weighted coil combination
Systematic evaluation of iterative deep neural networks for fast parallel MRI reconstruction with sensitivity‐weighted coil combination
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Systematic evaluation of iterative deep neural networks for fast parallel MRI reconstruction with sensitivity‐weighted coil combination

Hammernik, Kerstin ; Schlemper, Jo ; Qin, Chen ; Duan, Jinming ; Summers, Ronald M. ; Rueckert, Daniel

Magnetic resonance in medicine, 2021-10, Vol.86 (4), p.1859-1872 [Periódico revisado por pares]

Hoboken: Wiley Subscription Services, Inc

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9
A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer’s disease
A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer’s disease
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A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer’s disease

Liu, Manhua ; Li, Fan ; Yan, Hao ; Wang, Kundong ; Ma, Yixin ; Shen, Li ; Xu, Mingqing

NeuroImage (Orlando, Fla.), 2020-03, Vol.208, p.116459-116459, Article 116459 [Periódico revisado por pares]

United States: Elsevier Inc

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IWA: Integrated gradient‐based white‐box attacks for fooling deep neural networks
IWA: Integrated gradient‐based white‐box attacks for fooling deep neural networks
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IWA: Integrated gradient‐based white‐box attacks for fooling deep neural networks

Wang, Yixiang ; Liu, Jiqiang ; Chang, Xiaolin ; Mišić, Jelena ; Mišić, Vojislav B.

International journal of intelligent systems, 2022-07, Vol.37 (7), p.4253-4276 [Periódico revisado por pares]

New York: Hindawi Limited

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