Publications

Accepted or to appear

Papers in international journals

  1. N. Lessmann, P.A. de Jong, C. Celeng, R.A.P. Takx, M.A. Viergever, B. van Ginneken and I. Išgum. "Sex Differences in Coronary Artery and Thoracic Aorta Calcification and Their Association With Cardiovascular Mortality in Heavy Smokers", JACC Cardiovascular Imaging. Abstract/PDF DOI PMID 30660540

  2. M.U. Dalmış, 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. Abstract/PDF DOI PMID 30652985

  3. O. Geessink, A. Baidoshvili, J. Klaase, B. Ehteshami Bejnordi, G. Litjens, G. van Pelt, W. Mesker, I. Nagtegaal, F. Ciompi and J. van der Laak. "Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer", Cellular Oncology.


Papers in conference proceedings

  1. E. Calli, E. Sogancioglu, E.T. Scholten, K. Murphy and B. van Ginneken. "Handling label noise through model confidence and uncertainty: application to chest radiograph classification", in: Medical Imaging of Proceedings of the SPIE.

  2. 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 SPIE.

  3. 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 SPIE.

  4. H. Pinckaers, W. Bulten and G. Litjens. "High resolution whole prostate biopsy classification using streaming stochastic gradient descent", in: Medical Imaging of Proceedings of the SPIE. Abstract/PDF

  5. J. van Vugt, E. Marchiori, R. Mann, A. Gubern-Mérida, N. Moriakov and J. Teuwen. "Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation", in: Medical Imaging of SPIE.


2019

Papers in international journals

  1. N. Lessmann, B. van Ginneken, P.A. de Jong and I. Išgum. "Iterative fully convolutional neural networks for automatic vertebra segmentation and identification", Medical Image Analysis 2019;53:142-155. Abstract/PDF DOI arXiv PMID 30771712

  2. B. van Ginneken. "Deep Learning for Triage of Chest Radiographs: Should Every Institution Train Its Own System?", Radiology 2019;290:545-546. PDF DOI PMID 30422089

  3. M. Tammemagi, A.J. Ritchie, S. Atkar-Khattra, B. Dougherty, C. Sanghera, J.R. Mayo, R. Yuan, D. Manos, A.M. McWilliams, H. Schmidt, M. Gingras, S. Pasian, L. Stewart, S. Tsai, J.M.Seely, P. Burrowes, R. Bhatia, E.A.Haider, C. Boylan, C. Jacobs, B. van Ginneken, M.-S. Tsao, S. Lam and the Pan-Canadian Early Detection of Lung Cancer Study Group. "Predicting Malignancy Risk of Screen Detected Lung Nodules – Mean Diameter or Volume", Journal of Thoracic Oncology 2019;14:203-211. Abstract/PDF DOI PMID 30368011

  4. S. Balocco, F. Ciompi, J. Rigla, X. Carrillo, J. Mauri and P. Radeva. "Assessment Of Intra-coronary Stent Location And Extension In Intravascular Ultrasound Sequences", Medical Physics 2019;46(2):484-493. Abstract/PDF DOI PMID 30383304

  5. W. Bulten, P. Bándi, J. Hoven, R. van de Loo, J. Lotz, N. Weiss, J. van der Laak, B. van Ginneken, C. Hulsbergen-van de Kaa and G. Litjens. "Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard", Nature Scientific Reports 2019;9(864). Abstract/PDF DOI

  6. J.-P. Charbonnier, E. Pompe, C. Moore, S. Humphries, B. van Ginneken, B. Make, E. Regan, J.D. Crapo, E.M. van Rikxoort and D.A. Lynch. "Airway wall thickening on CT: Relation to smoking status and severity of COPD", Respiratory Medicine 2019;146:36-41. Abstract/PDF DOI

  7. T.L.A. van den Heuvel, H. Petros, S. Santini, C.L. de Korte and B. van Ginneken. "Automated Fetal Head Detection and Circumference Estimation from Free-Hand Ultrasound Sweeps Using Deep Learning in Resource-Limited Countries", Ultrasound in Medicine and Biology 2019;45(3):773-785. Abstract/PDF DOI PMID 30573305

  8. L. Maier-Hein, M. Eisenmann, A. Reinke, S. Onogur, M. Stankovic, P. Scholz, T. Arbel, H. Bogunovic, A.P. Bradley, A. Carass, C. Feldmann, A.F. Frangi, P.M. Full, B. van Ginneken, A. Hanbury, K. Honauer, M. Kozubek, B.A. Landman, K. März, O. Maier, K. Maier-Hein, B.H. Menze, H. Müller, P.F. Neher, W. Niessen, N. Rajpoot, G.C. Sharp, K. Sirinukunwattana, S. Speidel, C. Stock, D. Stoyanov, A.A. Taha, F. van der Sommen, C.-W. Wang, M.-A. Weber, G. Zheng, P. Jannin and A. Kopp-Schneider. "Author Correction: Why rankings of biomedical image analysis competitions should be interpreted with care.", Nature communications 2019;10:588. Abstract DOI PMID 30700735

  9. S.J. van Riel, C. Jacobs, E.T. Scholten, R. Wittenberg, M.M. Winkler Wille, B. de Hoop, R. Sprengers, O.M. Mets, B. Geurts, M. Prokop, C. Schaefer-Prokop and B. van Ginneken. "Observer variability for Lung-RADS categorisation of lung cancer screening CTs: impact on patient management", European Radiology 2019;29(2):924-931. Abstract/PDF DOI PMID 30066248


Preprints

  1. P. Bilic, P.F. Christ, E. Vorontsov, G. Chlebus, H. Chen, Q. Dou, C.-W. Fu, X. Han, P.-A. Heng, J. Hesser, S. Kadoury, T. Konopczynski, M. Le, C. Li, X. Li, J. Lipkovà, J. Lowengrub, H. Meine, J.H. Moltz, C. Pal, M. Piraud, X. Qi, J. Qi, M. Rempfler, K. Roth, A. Schenk, A. Sekuboyina, E. Vorontsov, P. Zhou, C. Hülsemeyer, M. Beetz, F. Ettlinger, F. Gruen, G. Kaissis, F. Lohöfer, R. Braren, J. Holch, F. Hofmann, W. Sommer, V. Heinemann, C. Jacobs, G.E.H. Mamani, B. van Ginneken, G. Chartrand, A. Tang, M. Drozdzal, A. Ben-Cohen, E. Klang, M.M. Amitai, E. Konen, H. Greenspan, J. Moreau, A. Hostettler, L. Soler, R. Vivanti, A. Szeskin, N. Lev-Cohain, J. Sosna, L. Joskowicz and B.H. Menze. "The Liver Tumor Segmentation Benchmark (LiTS)", arXiv:1901.04056 2019. Abstract


Abstracts

  1. T.L.A. van den Heuvel, B. van Ginneken and C.L. de Korte. "Improving Maternal Care In Resource-Limited Settings Using A Low-Cost Ultrasound Device And Machine Learning", in: Dutch Bio-Medical Engineering Conference, 2019. PDF


Theses

  1. T. van der Ouderaa. "Reversible Networks for Memory-efficient Image-to-Image Translation in 3D Medical Imaging", Masters thesis, University of Amsterdam, 2019. Abstract/PDF

  2. T.L.A. van den Heuvel. "Automated low-cost ultrasound: improving antenatal care in resource-limited settings", PhD thesis, Radboud University, Nijmegen, The Netherlands, 2019. Abstract/PDF

  3. R. Philipsen. "Automated chest radiography reading. Improvements, validation, and cost-effectiveness analysis.", PhD thesis, 2019. Abstract/PDF