Publications

2020

  1. Convolutional neural networks
    Handbook of Medical Image Computing and Computer Assisted Intervention
    J. Teuwen, N. Moriakov, 2020
    Abstract
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  2. Machine learning-based classification of viewing behavior using a wide range of statistical oculomotor features
    Journal of Vision
    T. Kootstra, J. Teuwen, J. Goudsmit, T. Nijboer, M. Dodd, S. Van Der Stigchel, 2020, 20;(9):1
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  3. Tussen data en theorie
    Tijdschrift voor Toezicht
    J. Goudsmit, J. Teuwen, 2020, 11;(1):48-53
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  4. Kernel of cyclegan as a principal homogeneous space
    International Conference on Learning Representations
    N. Moriakov, J. Adler, J. Teuwen, 2020
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  5. Computable Følner monotilings and a theorem of Brudno
    Ergodic Theory and Dynamical Systems
    N. Moriakov, 2020, 41;(11):3389-3416
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  6. Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results
    NeuroImage
    L. Ning, E. Bonet-Carne, F. Grussu, F. Sepehrband, E. Kaden, J. Veraart, S. B. Blumberg, C. S. Khoo, M. Palombo, I. Kokkinos, D. C. Alexander, J. Coll-Font, B. Scherrer, S. K. Warfield, S. C. Karayumak, Y. Rathi, S. Koppers, L. Weninger, J. Ebert, D. Merhof, D. Moyer, M. Pietsch, D. Christiaens, R. A. Gomes Teixeira, J. Tournier, K. G. Schilling, Y. Huo, V. Nath, C. Hansen, J. Blaber, B. A. Landman, A. Zhylka, J. P. Pluim, G. Parker, U. Rudrapatna, J. Evans, C. Charron, D. K. Jones, C. M. Tax, 2020, 221
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2019

  1. A new class of SYK-like models with maximal chaos
    Journal of High Energy Physics
    E. Marcus, S. Vandoren, 2019, 2019;(1)
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  2. i-RIM applied to the fastMRI challenge
    P. Putzky, D. Karkalousos, J. Teuwen, N. Moriakov, B. Bakker, M. Caan, M. Welling, 2019
    Abstract
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  3. Learned SIRT for Cone Beam Computed Tomography Reconstruction
    R. J. Dilz, L. Schröder, N. Moriakov, J. Sonke, J. Teuwen, 2019
    Abstract
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  4. Artificial Intelligence–Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI
    Investigative Radiology
    M. U. Dalmiş, A. Gubern-Mérida, S. Vreemann, P. Bult, N. Karssemeijer, R. Mann, J. Teuwen, 2019, 54;(6):325-332
    Abstract
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  5. State-of-the-Art Deep Learning in Cardiovascular Image Analysis
    JACC: Cardiovascular Imaging
    G. Litjens, F. Ciompi, J. M. Wolterink, B. D. De Vos, T. Leiner, J. Teuwen, I. Išgum, 2019, 12;(8):1549-1565
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  6. Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study
    European Radiology
    A. Rodriguez-Ruiz, K. Lång, A. Gubern-Merida, J. Teuwen, M. Broeders, G. Gennaro, P. Clauser, T. H. Helbich, M. Chevalier, T. Mertelmeier, M. G. Wallis, I. Andersson, S. Zackrisson, I. Sechopoulos, R. M. Mann, 2019, 29;(9):4825-4832
    Abstract
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  7. MemCNN: A Python/PyTorch package for creating memory-efficient invertible neural networks
    Journal of Open Source Software
    S. C. Van De Leemput, J. Teuwen, B. Van Ginneken, R. Manniesing, 2019, 4;(39):1576
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  8. Breast parenchyma analysis and classification for breast masses detection using texture feature descriptors and neural networks in dedicated breast CT images
    Medical Imaging 2019: Computer-Aided Diagnosis
    M. Caballo, J. Teuwen, R. Mann, I. Sechopoulos, 2019
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  9. Differentiating benign and malignant mass and non-mass lesions in breast DCE-MRI using normalized frequency-based features
    International Journal of Computer Assisted Radiology and Surgery
    F. Ayatollahi, S. B. Shokouhi, J. Teuwen, 2019, 15;(2):297-307
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  10. Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation
    Medical Imaging 2019: Computer-Aided Diagnosis
    J. Teuwen, N. Moriakov, R. Mann, E. Marchiori, J. Van Vugt, A. Gubern-Mérida, 2019
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  11. Deep learning framework for digital breast tomosynthesis reconstruction
    Medical Imaging 2019: Physics of Medical Imaging
    N. Moriakov, K. Michielsen, J. Adler, R. Mann, I. Sechopoulos, J. Teuwen, 2019
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2018

  1. Charge-dependent flow induced by magnetic and electric fields in heavy ion collisions
    Physical Review C
    U. Gürsoy, D. Kharzeev, E. Marcus, K. Rajagopal, C. Shen, 2018, 98;(5)
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  2. On Maximum Focused Electric Energy in Bounded Regions
    J. Teuwen, P. Urbach, 2018
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  3. Pectoral muscle segmentation in breast tomosynthesis with deep learning
    Medical Imaging 2018: Computer-Aided Diagnosis
    A. Rodriguez-Ruiz, J. Teuwen, K. Chung, N. Karssemeijer, M. Chevalier, A. Gubern-Mérida, I. Sechopoulos, 2018
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  4. Automated lesion detection and segmentation in digital mammography using a u-net deep learning network
    14th International Workshop on Breast Imaging (IWBI 2018)
    T. De Moor, A. Rodriguez-Ruiz, R. Mann, A. Gubern Mérida, J. Teuwen, 2018
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  5. Student beats the teacher: deep neural networks for lateral ventricles segmentation in brain MR
    Medical Imaging 2018: Image Processing
    J. Teuwen, M. Ghafoorian, R. Manniesing, F. De Leeuw, N. Karssemeijer, B. Van Ginneken, B. Platel, 2018
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  6. Improving Breast Cancer Detection Using Symmetry Information with Deep Learning
    Image Analysis for Moving Organ, Breast, and Thoracic Images
    Y. Brhane Hagos, A. Gubern Mérida, J. Teuwen, 2018
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  7. Fluctuations of ergodic averages for actions of groups of polynomial growth
    Studia Mathematica
    N. Moriakov, 2018, 240;(3):255-273
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  8. On systems with quasi-discrete spectrum
    Studia Mathematica
    M. Haase, N. Moriakov, 2018, 241;(2):173-199
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2017

  1. $L^p-L^q$- off-diagonal estimates for the Ornstein-Uhlenbeck semigroup: Some positive and negative results
    Bulletin of the Australian Mathematical Society
    A. Amenta, J. Teuwen, 2017, 96;(1):154-161
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  2. New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers
    Acta Radiologica
    A. Rodriguez-Ruiz, J. Teuwen, S. Vreemann, R. W. Bouwman, R. E. Van Engen, N. Karssemeijer, R. M. Mann, A. Gubern-Merida, I. Sechopoulos, 2017, 59;(9):1051-1059
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  3. On the semi-classical limit of scalar products of the XXZ spin chain
    Journal of High Energy Physics
    Y. Jiang, J. Brunekreef, 2017, 2017;(3)
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  4. On Effective Birkhoff’s Ergodic Theorem for Computable Actions of Amenable Groups
    Theory of Computing Systems
    N. Moriakov, 2017, 62;(5):1269-1287
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  5. Endothelial progenitor cells and plaque burden in stented coronary artery segments: an optical coherence tomography study six months after elective PCI
    BMC Cardiovascular Disorders
    S. Otto, K. Nitsche, C. Jung, A. Kryvanos, A. Zhylka, K. Heitkamp, J. Gutiérrez-Chico, B. Goebel, P. C. Schulze, H. R. Figulla, T. C. Poerner, 2017, 17;(1)
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2016

  1. Magnetohydrodynamics and charged flow in heavy ion collisions
    Nuclear Physics A
    U. Gürsoy, D. Kharzeev, E. Marcus, K. Rajagopal, 2016, 956
    Abstract
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  2. On the integral kernels of derivatives of the Ornstein–Uhlenbeck semigroup
    Infinite Dimensional Analysis, Quantum Probability and Related Topics
    J. Teuwen, 2016, 19;(04):1650030
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  3. Shedding new light on Gaussian harmonic analysis
    J. Teuwen, 2016
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  4. A Landscape of Pharmacogenomic Interactions in Cancer
    Cell
    F. Iorio, T. A. Knijnenburg, D. J. Vis, G. R. Bignell, M. P. Menden, M. Schubert, N. Aben, E. Gonçalves, S. Barthorpe, H. Lightfoot, T. Cokelaer, P. Greninger, E. Van Dyk, H. Chang, H. De Silva, H. Heyn, X. Deng, R. K. Egan, Q. Liu, T. Mironenko, X. Mitropoulos, L. Richardson, J. Wang, T. Zhang, S. Moran, S. Sayols, M. Soleimani, D. Tamborero, N. Lopez-Bigas, P. Ross-Macdonald, M. Esteller, N. S. Gray, D. A. Haber, M. R. Stratton, C. H. Benes, L. F. Wessels, J. Saez-Rodriguez, U. Mcdermott, M. J. Garnett, 2016, 166;(3):740-754
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2015

  1. A note on Gaussian maximal functions
    Indagationes Mathematicae
    J. Teuwen, 2015, 26;(1):106-112
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2010

  1. Combining regression and classification methods for improving automatic speaker age recognition
    2010 IEEE International Conference on Acoustics, Speech and Signal Processing
    C. Van Heerden, E. Barnard, M. Davel, C. Van Der Walt, E. Van Dyk, M. Feld, C. Muller, 2010
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