Publications of Jonas Teuwen

Accepted or to appear

Papers in international journals

  1. N. Lessmann, C.I. Sanchez, L. Beenen, L.H. Boulogne, M. Brink, E. Calli, J.-P. Charbonnier, T. Dofferhoff, W.M. van Everdingen, P.K. Gerke, B. Geurts, H.A. Gietema, M. Groeneveld, L. van Harten, N. Hendrix, W. Hendrix, H.J. Huisman, I. Isgum, C. Jacobs, R. Kluge, M. Kok, J. Krdzalic, B. Lassen-Schmidt, K. van Leeuwen, J. Meakin, M. Overkamp, T. van Rees Vellinga, E.M. van Rikxoort, R. Samperna, C. Schaefer-Prokop, S. Schalekamp, E.T. Scholten, C. Sital, L. Stöger, J. Teuwen, K. Vaidhya Venkadesh, C. de Vente, M. Vermaat, W. Xie, B. de Wilde, M. Prokop and B. van Ginneken. "Automated Assessment of CO-RADS and Chest CT Severity Scores in Patients with Suspected COVID-19 Using Artificial Intelligence", Radiology. Abstract/PDF DOI PMID

  2. I. Sechopoulos, J. Teuwen and R. Mann. "Artificial Intelligence for Breast Cancer Detection in Mammography: state of the art", Seminars in Cancer Biology. Abstract/PDF DOI PMID


2020

Papers in international journals

  1. F. Ayatollahi, S.B. Shokouhi and 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 2020;15:297-307. Abstract/PDF DOI PMID

  2. J. Goudsmit and J. Teuwen. "Tussen data en theorie", Tijdschrift voor Toezicht 2020;11(1):48-53. PDF DOI

  3. I. Olaciregui-Ruiz, I. Torres-Xirau, J. Teuwen, U.A. van der Heide and A. Mans. "A Deep Learning-based correction to EPID dosimetry for attenuation and scatter in the Unity MR-Linac system", Physica Medica 2020;71:124-131. Abstract/PDF DOI PMID


Papers in conference proceedings

  1. K. Michielsen, N. Moriakov, J. Teuwen and I. Sechopoulos. "Deep Learning-based Initialization of Iterative Reconstruction for Breast Tomosynthesis", in: 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.

  2. N. Moriakov, J. Adler and J. Teuwen. "Kernel of CycleGAN as a principal homogeneous space", in: International Conference on Learning Representations, 2020. Abstract/PDF URL


Abstracts

  1. W. Sanderink, J. Teuwen, L. Appelman, I. Sechopoulos, N. Karssemeijer and R. Mann. "Simultaneous multi-slice single-shot DWI compared to routine read-out-segmented DWI for evaluation of breast lesions", in: ISMRM Benelux, 2020. Abstract


2019

Papers in international journals

  1. M.U. Dalmis, A. Gubern-Merida, S. Vreemann, P. Bult, N. Karssemeijer, R. Mann and J. Teuwen. "Artificial Intelligence Based Classification of Breast Lesions Imaged With a Multi-Parametric Breast MRI Protocol With ultrafast DCE-MRI, T2 and DWI", Investigative Radiology 2019;56:325-332. Abstract/PDF DOI PMID

  2. S.C. van de Leemput, J. Teuwen, B. van Ginneken and R. Manniesing. "MemCNN: A Python/PyTorch package for creating memory-efficient invertible neural networks", #JOSS# 2019;4(39):1576. Abstract/PDF DOI

  3. G. Litjens, F. Ciompi, J.M. Wolterink, B.D. de Vos, T. Leiner, J. Teuwen and I. Isgum. "State-of-the-Art Deep Learning in Cardiovascular Image Analysis", JACC Cardiovascular Imaging 2019;12:1549-1565. Abstract/PDF DOI PMID

  4. A. Rodriguez-Ruiz, K. Lang, 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 and 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;29:4825-4832. Abstract/PDF DOI PMID


Preprints

  1. R. Dilz, L. Schröder, N. Moriakov, J.-J. Sonke and J. Teuwen. "Learned SIRT for Cone Beam Computed Tomography Reconstruction", arXiv:1908.10715 2019. Abstract

  2. P. Putzky, D. Karkalousos, J. Teuwen, N. Moriakov, B. Bakker, M. Caan and M. Welling. "i-RIM applied to the fastMRI challenge", arXiv:1910.08952 2019. Abstract/PDF


Papers in conference proceedings

  1. M. Caballo, J. Teuwen, R. Mann and I. Sechopolous. "Breast parenchyma analysis and classification for breast masses detection using texture feature descriptors and neural networks in dedicated breast CT images", in: Medical Imaging of Proceedings of the SPIE, 2019. Abstract/PDF DOI

  2. N. Moriakov, K. Michielsen, R. Mann, J. Adler, I. Sechopolous and J. Teuwen. "Deep learning framework for digital breast tomosynthesis reconstruction", in: Medical Imaging of Proceedings of the SPIE, 2019. Abstract/PDF DOI arXiv

  3. D. Ruhe, V. Codreanu, C. van Leeuwen, D. Podareanu, V. Saletore and J. Teuwen. "Generating CT-scans with 3D Generative Adversarial Networks Using a Supercomputer", in: Medical Imaging meets NeurIPS, 2019. Abstract

  4. J. van Vugt, E. Marchiori, R. Mann, A. Gubern-Merida, N. Moriakov and J. Teuwen. "Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation", in: Medical Imaging of Proceedings of the SPIE, 2019. Abstract/PDF DOI


Abstracts

  1. W. Sanderink, J. Teuwen, L. Appelman, I. Sechopoulos, N. Karssemeijer and R. Mann. "Simultaneous multi-slice single-shot DWI compared to routine read-out-segmented DWI for evaluation of breast lesions", in: Annual Meeting of the International Society for Magnetic Resonance in Medicine, 2019. Abstract


Theses

  1. M.U. Dalmis. "Automated Analysis of Breast MRI From traditional methods into deep learning", PhD thesis, Radboud University, Nijmegen, 2019. Abstract/PDF URL


2018

Papers in international journals

  1. A. Rodriguez-Ruiz, J. Teuwen, S. Vreemann, R.W. Bouwman, R.E. van Engen, N. Karssemeijer, R.M. Mann, A. Gubern-Merida and I. Sechopoulos. "New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers", Acta Radiologica 2018;59:1051-1059. Abstract/PDF DOI PMID


Preprints

  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", arXiv:1802.06865 2018. Abstract

  2. J. Teuwen and P. Urbach. "On Maximum Focused Electric Energy in Bounded Regions", arXiv:1801.02450 2018. Abstract


Papers in conference proceedings

  1. M. Ghafoorian, J. Teuwen, R. Manniesing, F.-E. de Leeuw, B. van Ginneken, N. Karssemeijer and B. Platel. "Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR", in: Medical Imaging, volume 10574 of Proceedings of the SPIE, 2018, page 105742U. Abstract/PDF DOI arXiv

  2. Y.B. Hagos, A. Gubern-Merida and J. Teuwen. "Improving Breast Cancer Detection using Symmetry Information with Deep Learning", in: Breast Image Analysis (BIA), 2018. Abstract/PDF DOI

  3. S.C. van de Leemput, J. Teuwen and R. Manniesing. "MemCNN: a Framework for Developing Memory Efficient Deep Invertible Networks", in: International Conference on Learning Representations, 2018. Abstract/PDF URL

  4. 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", in: International Workshop on Breast Imaging, 2018. Abstract/PDF arXiv

  5. 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", in: Medical Imaging of Proceedings of the SPIE, 2018. Abstract DOI


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", in: European Society for Molecular Imaging, 2018. Abstract


2017

Abstracts

  1. J. Teuwen, M. Kallenberg, A. Gubern-Merida, A. Rodriguez-Ruiz, N. Karssemeijer and R. Mann. "Automated pre-selection of mammograms without abnormalities using deep learning", in: Annual Meeting of the Radiological Society of North America, 2017. Abstract


2016

Papers in international journals

  1. J. Teuwen. "On the integral kernels of derivatives of the Ornstein-Uhlenbeck semigroup", Infinite Dimensional Analysis, Quantum Probability and Related Topics 2016;19(04):1650030. PDF DOI


Theses

  1. J. Teuwen. "Shedding new light on gaussian harmonic analysis", PhD thesis, Delft University of Technology, 2016. Abstract/PDF DOI


2015

Papers in international journals

  1. J. Teuwen. "A note on Gaussian maximal function", Indagationes Mathematicae 2015;26(1):106-112. Abstract/PDF DOI