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Browsing by Author "Van Nieuwenhove, Vincent"

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    A Deep Convolutional Framelet Network based on Tight steerable Wavelet: application to sparse-view medical tomosynthesis

    Pereira, Luis F. Alves
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    Van Nieuwenhove, Vincent
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    De Beenhouwer, Jan  
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    Sijbers, Jan  
    Proceedings paper
    2021-10, Proceedings of the 16th Virtual International Meeting on Fully 3D Image Reconstruction in Radiology and Nuclear Medicine, 19/07/2021, p.399-402
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    Data-driven affine deformation estimation and correction in cone beam computed tomography

    Van Nieuwenhove, Vincent
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    De Beenhouwer, Jan  
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    De Schryver, Thomas
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    Van Hoorebeke, Luc
    Journal article
    2017-01, IEEE Transactions on Image Processing, (2017) 26, p.1441-1451
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    Joint reconstruction and flat-field estimation using support estimation

    Six, Nathanaël
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    De Beenhouwer, Jan  
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    Van Nieuwenhove, Vincent
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    Vanroose, Wim
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    Sijbers, Jan  
    Proceedings paper
    2018-11, 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC), 10/11/2018, p.1-4
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    Model-based reconstruction algorithms for dynamic X-ray CT

    Van Nieuwenhove, Vincent
    PHD thesis
    2017
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    MoVIT: a tomographic reconstruction framework for 4D-CT

    Van Nieuwenhove, Vincent
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    De Beenhouwer, Jan  
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    Vlassenbroeck, Jelle
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    Brennan, Mark
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    Sijbers, Jan  
    Journal article
    2017-01, Optics Express, (25) 16, p.19236-19250
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    Performance and memory use trade-off in CPU and GPU implementations of a deformation operator for 4D-CT

    Manhaeve, Stijn
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    Van Nieuwenhove, Vincent
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    Sijbers, Jan  
    Meeting abstract
    2018, 8th Conference on Industrial Computed Tomography, 6/02/2018
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    Ringing artefact removal from sparse view tomosynthesis using deep neural networks

    Bazrafkan, Shabab  
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    Van Nieuwenhove, Vincent
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    Soons, Joris
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    De Beenhouwer, Jan  
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    Sijbers, Jan  
    Proceedings paper
    2020, 6th International Conference on Image Formation in X-Ray Computed Tomography, 3/08/2020, p.380-383
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    To recurse or not to recurse: a low-dose CT study

    Bazrafkan, Shabab  
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    Van Nieuwenhove, Vincent
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    Soons, Joris
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    De Beenhouwer, Jan  
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    Sijbers, Jan  
    Journal article
    2021, PROGRESS IN ARTIFICIAL INTELLIGENCE, (10) 1, p.65-81

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