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Computed tomography (CT) is critical for various clinical applications, e.g., radiotherapy treatment planning and also PET attenuation correction.
Attenuation correction for a combined 3d pet/ct scanner
PE Kinahan et al · 1998
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Gradient-based learning applied to document recognition
Yann LeCun et al · 1998
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Habib Zaidi et al · 2003
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Computed tomography¡ªan increasing source of radiation exposure
David J Brenner and Eric J Hall · 2007
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Diffeomorphic demons: Efficient non-parametric image registration
Tom Vercauteren et al · 2009
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Toward implementing an mri-based pet attenuation-correction method for neurologic studies on the mr-pet brain prototype
Ciprian Catana et al · 2010
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Auto-context and its application to high-level vision tasks and 3d brain image segmentation
Zhuowen Tu and Xiang Bai · 2010
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Mri-based attenuation correction for hybrid pet/mri systems: a 4-class tissue segmentation technique using a combined ultrashort-echo-time/dixon mri sequence
Yannick Berker et al · 2012
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3d convolutional neural networks for human action recognition
Shuiwang Ji et al · 2013
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Learning a deep convolutional network for image super-resolution
Chao Dong et al · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Cited alongside, same era.
Improving magnetic resonance resolution with supervised learning
Learning spatiotemporal features with 3d convolutional networks
Du Tran et al · 2014
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Estimating CT Image from MRI Data Using Structured Random Forest and Auto-context Model
Tri Huynh et al · 2015
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Deep learning
Y. LeCun et al · 2015
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Deep multi-scale video prediction beyond mean square error
Michael Mathieu, Camille Couprie, and Yann LeCun · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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Amod Jog et al · 2014
Cited alongside, same era.
Deep learning based imaging data completion for improved brain disease diagnosis
Rongjian Li et al · 2014
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Links: Learning-based multi-source integration framework for segmentation of infant brain images
Li Wang, Yaozong Gao, Feng Shi, Gang Li, John H Gilmore, Weili Lin, and Dinggang Shen · 2015
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