1. R. J. Dilz, L. Schröder, N. Moriakov, J. Sonke, J. Teuwen, "Learned SIRT for Cone Beam Computed Tomography Reconstruction", 2019
  2. M. U. Dalmiş, A. Gubern-Mérida, S. Vreemann, P. Bult, N. Karssemeijer, R. Mann, J. Teuwen, "Artificial Intelligence–Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI", Investigative Radiology, 2019, 54;(6):325-332
  3. G. Litjens, F. Ciompi, J. M. Wolterink, B. D. De Vos, T. Leiner, J. Teuwen, I. Išgum, "State-of-the-Art Deep Learning in Cardiovascular Image Analysis", JACC: Cardiovascular Imaging, 2019, 12;(8):1549-1565
  4. 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, "Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study", European Radiology, 2019, 29;(9):4825-4832
  5. S. C. Van De Leemput, J. Teuwen, B. Van Ginneken, R. Manniesing, "MemCNN: A Python/PyTorch package for creating memory-efficient invertible neural networks", Journal of Open Source Software, 2019, 4;(39):1576
  6. M. Caballo, J. Teuwen, R. Mann, I. Sechopoulos, "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, 2019
  7. F. Ayatollahi, S. B. Shokouhi, J. Teuwen, "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, 2019, 15;(2):297-307
  8. J. Teuwen, N. Moriakov, R. Mann, E. Marchiori, J. Van Vugt, A. Gubern-Mérida, "Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation", Medical Imaging 2019: Computer-Aided Diagnosis, 2019
  9. E. Marcus, S. Vandoren, "A new class of SYK-like models with maximal chaos", Journal of High Energy Physics, 2019, 2019;(1)


  1. Y. B. Hagos, A. G. Merida, J. Teuwen, "Improving Breast Cancer Detection using Symmetry Information with Deep Learning", 2018
  2. J. v. Vugt, E. Marchiori, R. Mann, A. Gubern-Mérida, N. Moriakov, J. Teuwen, "Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation", 2018
  3. N. Moriakov, K. Michielsen, J. Adler, R. Mann, I. Sechopoulos, J. Teuwen, "Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction", 2018
  4. T. d. Moor, A. Rodriguez-Ruiz, A. G. Mérida, R. Mann, J. Teuwen, "Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network", 2018
  5. M. Ghafoorian, J. Teuwen, R. Manniesing, F. d. Leeuw, B. v. Ginneken, N. Karssemeijer, B. Platel, "Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR", 2018
  6. J. Teuwen, P. Urbach, "On Maximum Focused Electric Energy in Bounded Regions", 2018
  7. A. Rodriguez-Ruiz, J. Teuwen, K. Chung, N. Karssemeijer, M. Chevalier, A. Gubern-Mérida, I. Sechopoulos, "Pectoral muscle segmentation in breast tomosynthesis with deep learning", Medical Imaging 2018: Computer-Aided Diagnosis, 2018
  8. T. De Moor, A. Rodriguez-Ruiz, R. Mann, A. Gubern Mérida, J. Teuwen, "Automated lesion detection and segmentation in digital mammography using a u-net deep learning network", 14th International Workshop on Breast Imaging (IWBI 2018), 2018
  9. U. Gürsoy, D. Kharzeev, E. Marcus, K. Rajagopal, C. Shen, "Charge-dependent flow induced by magnetic and electric fields in heavy ion collisions", Physical Review C, 2018, 98;(5)
  10. N. Moriakov, "Fluctuations of ergodic averages for actions of groups of polynomial growth", Studia Mathematica, 2018, 240;(3):255-273
  11. M. Haase, N. Moriakov, "On systems with quasi-discrete spectrum", Studia Mathematica, 2018, 241;(2):173-199


  1. A. Amenta, J. Teuwen, "$L^p-L^q$- off-diagonal estimates for the Ornstein-Uhlenbeck semigroup: Some positive and negative results", Bulletin of the Australian Mathematical Society, 2017, 96;(1):154-161
  2. A. Rodriguez-Ruiz, J. Teuwen, S. Vreemann, R. W. Bouwman, R. E. Van Engen, N. Karssemeijer, R. M. Mann, A. Gubern-Merida, I. Sechopoulos, "New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers", Acta Radiologica, 2017, 59;(9):1051-1059
  3. 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, "Endothelial progenitor cells and plaque burden in stented coronary artery segments: an optical coherence tomography study six months after elective PCI", BMC Cardiovascular Disorders, 2017, 17;(1)
  4. N. Moriakov, "On Effective Birkhoff’s Ergodic Theorem for Computable Actions of Amenable Groups", Theory of Computing Systems, 2017, 62;(5):1269-1287
  5. Y. Jiang, J. Brunekreef, "On the semi-classical limit of scalar products of the XXZ spin chain", Journal of High Energy Physics, 2017, 2017;(3)


  1. A. Amenta, J. Teuwen, "$L^p$-$L^q$ off-diagonal estimates for the Ornstein–Uhlenbeck semigroup: some positive and negative results", 2016
  2. J. Teuwen, "Shedding new light on Gaussian harmonic analysis", 2016
  3. U. Gürsoy, D. Kharzeev, E. Marcus, K. Rajagopal, "Magnetohydrodynamics and charged flow in heavy ion collisions", Nuclear Physics A, 2016, 956


  1. J. Teuwen, "On the integral kernels of derivatives of the Ornstein-Uhlenbeck semigroup", 2015
  2. J. Teuwen, "A note on Gaussian maximal functions", Indagationes Mathematicae, 2015, 26;(1):106-112


  1. J. Teuwen, "A note on the Gaussian maximal functions", 2013