Publications of Jonas Teuwen

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2018

Papers in international journals

  1. A. Rodriguez-Ruiz, J. Teuwen, S. Vreemann, R. Bouwman, R. van Engen, N. Karssemeijer, R. Mann, A. Gubern-Merida and I. Sechopoulos, "New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers", Acta Radiologica, 2018;59(9):1051-1059.
    Abstract DOI PMID Cited by ~33

Preprints

  1. J. Teuwen and P. Urbach, "On Maximum Focused Electric Energy in Bounded Regions", arXiv:1801.02450, 2018.
    Abstract arXiv
  2. T. de Moor, A. Rodriguez-Ruiz, R. Mann and J. Teuwen, "Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network", arXiv:1802.06865, 2018.
    Abstract arXiv

Papers in conference proceedings

  1. T. de Moor, A. Rodriguez-Ruiz, R. Mann and J. Teuwen, "Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network", International Workshop on Breast Imaging, 2018.
    Abstract arXiv Cited by ~32
  2. M. Ghafoorian, J. Teuwen, R. Manniesing, F. de Leeuw, B. van Ginneken, N. Karssemeijer and B. Platel, "Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR", Medical Imaging, 2018;10574:105742U.
    Abstract DOI arXiv Cited by ~18
  3. S. van de Leemput, J. Teuwen and R. Manniesing, "MemCNN: a Framework for Developing Memory Efficient Deep Invertible Networks", International Conference on Learning Representations, 2018.
    Abstract Url Cited by ~11
  4. A. Rodriguez-Ruiz, J. Teuwen, K. Chung, N. Karssemeijer, M. Chevalier, A. Gubern-Merida and I. Sechopoulos, "Pectoral muscle segmentation in breast tomosynthesis with deep learning", Medical Imaging, 2018.
    Abstract DOI Cited by ~21
  5. Y. Hagos, A. Gubern-Mérida and J. Teuwen, "Improving Breast Cancer Detection using Symmetry Information with Deep Learning", Breast Image Analysis (BIA), 2018.
    Abstract DOI Cited by ~25

Abstracts

  1. E. Smeets, J. Teuwen, J. van der Laak, M. Gotthardt, F. Ciompi and E. Aarntzen, "Tumor heterogeneity as a PET-biomarker predicts overall survival of pancreatic cancer patients", European Society for Molecular Imaging, 2018.
    Abstract