Publications of Jonas Teuwen

2019

Papers in international journals

1. G. Litjens, F. Ciompi, J. Wolterink, B. de Vos, T. Leiner, J. Teuwen and I. Isgum, "State-of-the-Art Deep Learning in Cardiovascular Image Analysis", JACC Cardiovascular Imaging, 2019;12(8 Pt 1):1549-1565.
   Abstract DOI PMID Download Cited by ~246
2. A. Rodriguez-Ruiz, K. Lang, A. Gubern-Merida, J. Teuwen, M. Broeders, G. Gennaro, P. Clauser, T. Helbich, M. Chevalier, T. Mertelmeier, M. Wallis, I. Andersson, S. Zackrisson, I. Sechopoulos and R. 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.
   Abstract DOI PMID Cited by ~137
3. M. Dalmis, A. Gubern-Mérida, 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(6):325-332.
   Abstract DOI PMID Cited by ~74
4. S. van de Leemput, J. Teuwen, B. van Ginneken and R. Manniesing, "MemCNN: A Python/PyTorch package for creating memory-efficient invertible neural networks", Journal of Open Source Software, 2019;4(39):1576.
   Abstract DOI Code Cited by ~13

Preprints

1. R. Dilz, L. Schröder, N. Moriakov, J. Sonke and J. Teuwen, "Learned SIRT for Cone Beam Computed Tomography Reconstruction", arXiv:1908.10715, 2019.
   Abstract arXiv Cited by ~1
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 arXiv Cited by ~29

Papers in conference proceedings

1. N. Moriakov, K. Michielsen, R. Mann, J. Adler, I. Sechopolous and J. Teuwen, "Deep learning framework for digital breast tomosynthesis reconstruction", Medical Imaging, 2019.
   Abstract DOI arXiv Cited by ~10
2. 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", Medical Imaging, 2019.
   Abstract DOI
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", Medical Imaging meets NeurIPS, 2019.
   Abstract
4. 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", Medical Imaging, 2019.
   Abstract DOI Cited by ~5

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", Annual Meeting of the International Society for Magnetic Resonance in Medicine, 2019.
   Abstract

PhD theses

1. M. Dalmis, "Automated Analysis of Breast MRI From traditional methods into deep learning", PhD thesis, 2019.
   Abstract Url