Publications
2020
- N. Moriakov, A. Samudre, M. Negro, F. Gieseke, S. Otten, L. Hendriks, "Inferring astrophysical X-ray polarization with deep learning", arXiv:2005.08126 [astro-ph], 2020-05-16
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T. Driever, A. Van der Horst, J. Teuwen, M. Fast, J. Sonke, "Quantifying intra-fractional gastric wall motion for MR-guided radiotherapy", ESTRO 2020, 2020
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M. Fernandes, J. Teuwen, R. Wijsman, S. Barbara, N. Moriakov, J. Bussink, R. Monshouwer, "Segmentation of the heart using a Residual U-net model", ESTOR 2020, 2020
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C. Linthorst, R. Wijsman, M. Fernandes, B. Stam, J. Teuwen, D. Bosboom, R. Monshouwer, J. Bussink, "Pericardial effusion after radiotherapy for Non-Small Cell Lung Cancer", ESTRO 2020, 2020
- A. Tiwari, A. Pai, D. Joshi, "A shoe-mounted infrared sensor-based instrumentation for locomotion identification using machine learning methods", Measurement, 10/09/2020, 168;(108458)
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C. Rao, S. Pai, I. Hadzic, I. Zhovannik, D. Bontempi, A. Dekker, J. Teuwen, A. Traverso, "Oropharyngeal Tumour Segmentation using Ensemble 3D PET-CT Fusion Networks for the HECKTOR Challenge", Head and Neck Tumor Segmentation: First Challenge, HECKTOR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings, 2020
- I. Olaciregui-Ruiz, I. Torres-Xirau, J. Teuwen, U. A. van der Heide, A. Mans, "A Deep Learning-based correction to EPID dosimetry for attenuation and scatter in the Unity MR-Linac system", Physica Medica, 03/2020, 71
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T. Kootstra, J. Teuwen, J. Goudsmit, T. Nijboer, M. Dodd, S. Van der Stigchel, "Machine learning-based classification of viewing behavior using a wide range of statistical oculomotor features", Journal of Vision, 2020, 20;(9):1-1
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K. Michielsen, N. Moriakov, J. Teuwen, I. Sechopoulos, "Deep Learning-based Initialization of Iterative Reconstruction for Breast Tomosynthesis", arXiv preprint arXiv:2009.01538, 2020
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J. Goudsmit, J. Teuwen, "Tussen data en theorie: Het venijn zit in de aard", Tijdschrift voor Toezicht, 2020
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N. Moriakov, J. Adler, J. Teuwen, "Kernel of CycleGAN as a Principle homogeneous space", arXiv preprint arXiv:2001.09061, 2020
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N. Lessmann, C. I. Sánchez, L. Beenen, L. H. Boulogne, M. Brink, E. Calli, J. Charbonnier, T. Dofferhoff, W. M. van Everdingen, P. K. Gerke, "Automated assessment of CO-RADS and chest CT severity scores in patients with suspected COVID-19 using artificial intelligence", Radiology, 2020
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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, 2020, 15;(2):297-307
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J. Teuwen, N. Moriakov, "Convolutional neural networks", Handbook of Medical Image Computing and Computer Assisted Intervention, 2020
2019
- E. Marcus, S. Vandoren, "A new class of SYK-like models with maximal chaos", Journal of High Energy Physics, 2019-01-22, 2019;(1):166
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J. Teuwen, A. Hauptmann, M. Kachelriess, "Deep Learning for Image Reconstruction and Processing", MEDICAL PHYSICS, 2019, 46
- M. U. Dalmis, 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, June 2019, 54;(6):325–332
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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 Part 1):1549-1565
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W. Sanderink, J. Teuwen, L. Appelman, I. Sechopoulos, R. Mann, "Simultaneous multi-slice single-shot DWI compared to routine read-out-segmented DWI for evaluation of breast lesions", ISMRM, 2019
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A. Rodriguez-Ruiz, K. Lång, A. Gubern-Merida, J. Teuwen, M. Broeders, G. Gennaro, P. Clauser, T. H. Helbich, M. Chevalier, T. Mertelmeier, "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
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P. Putzky, D. Karkalousos, J. Teuwen, N. Miriakov, B. Bakker, M. Caan, M. Welling, "i-RIM applied to the fastMRI challenge", arXiv preprint arXiv:1910.08952, 2019
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R. J. Dilz, L. Schröder, N. Moriakov, J. Sonke, J. Teuwen, "Learned SIRT for Cone Beam Computed Tomography Reconstruction", arXiv preprint arXiv:1908.10715, 2019
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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, 10950
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J. van 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", Medical Imaging 2019: Computer-Aided Diagnosis, 2019, 10950
2018
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S. C. van de Leemput, J. Teuwen, R. Manniesing, "Memcnn: a framework for developing memory efficient deep invertible networks", ICLR 2018 Workshop Submission, 2018
- 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, November 15, 2018, 98;(5):055201
- R. S. Sheombarsing, "Validated Chebyshev-based Computations for Ordinary and Partial Differential Equations", PhD thesis, 2018
- N. Moriakov, "On Effective Birkhoff’s Ergodic Theorem for Computable Actions of Amenable Groups", Theory of Computing Systems, 7/2018, 62;(5):1269-1287
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E. Smeets, B. Feuerecker, J. Teuwen, J. van der Laak, M. Gotthardt, J. Siveke, R. Braren, F. Ciompi, E. Aarntzen, "Tumor heterogeneity as a PET-biomarker predicts overall survival of pancreatic cancer patients", European Society for Molecular Imaging 2018, 2018
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N. Antropova, A. L. Beam, B. K. Beaulieu-Jones, I. Chen, C. Chivers, A. Dalca, S. Finlayson, M. Fiterau, J. A. Fries, M. Ghassemi, "Machine learning for health (ML4H) workshop at NeurIPS 2018", arXiv preprint arXiv:1811.07216, 2018
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J. Teuwen, "[I253] Basics of deep learning", Physica Medica, 2018, 52
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A. Rodriguez-Ruiz, J. Teuwen, K. Chung, N. Karssemeijer, M. Chevalier, A. Gubern-Merida, I. Sechopoulos, "Pectoral muscle segmentation in breast tomosynthesis with deep learning", Medical Imaging 2018: Computer-Aided Diagnosis, 2018, 10575
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Y. B. Hagos, A. G. Mérida, J. Teuwen, "Improving breast cancer detection using symmetry information with deep learning", Image Analysis for Moving Organ, Breast, and Thoracic Images, 2018
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T. de Moor, A. Rodriguez-Ruiz, A. G. Mérida, R. Mann, 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, 10718
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M. Ghafoorian, J. Teuwen, R. Manniesing, F. de Leeuw, B. van Ginneken, N. Karssemeijer, B. Platel, "Student beats the teacher: deep neural networks for lateral ventricles segmentation in brain MR", Medical Imaging 2018: Image Processing, 2018, 10574
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J. Teuwen, P. Urbach, "On Maximum Focused Electric Energy in Bounded Regions", arXiv preprint arXiv:1801.02450, 2018
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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, 2018, 59;(9):1051-1059
2017
- 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, 2017-04-26, 17;(1):103
- L. Gong, H. Wang, C. Peng, Y. Dai, M. Ding, Y. Sun, X. Yang, J. Zheng, "Non-rigid MR-TRUS image registration for image-guided prostate biopsy using correlation ratio-based mutual information", BioMedical Engineering OnLine, January 10, 2017, 16;(1):8
- 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, 08/2017, 96;(1):154-161