Publications of Bram van Ginneken

2019

Papers in international journals

1. P. Bándi, M. Balkenhol, B. van Ginneken, J. van der Laak and G. Litjens, "Resolution-agnostic tissue segmentation in whole-slide histopathology images with convolutional neural networks", PeerJ, 2019;7:e8242.
   Abstract DOI PMID Cited by ~44
2. A. Patel, F. Schreuder, C. Klijn, M. Prokop, B. van Ginneken, H. Marquering, Y. Roos, M. Baharoglu, F. Meijer and R. Manniesing, "Intracerebral haemorrhage segmentation in non-contrast CT", Scientific Reports, 2019;9(1):17858.
   Abstract DOI PMID Cited by ~38
3. R. Philipsen, C. Sánchez, J. Melendez, W. Lew and B. van Ginneken, "Automated chest X-ray reading for tuberculosis in the Philippines to improve case detection: a cohort study", International Journal of Tuberculosis and Lung Disease, 2019;23(7):805-810.
   Abstract DOI PMID Download Cited by ~11
4. G. Aresta, C. Jacobs, T. Araujo, A. Cunha, I. Ramos, B. van Ginneken and A. Campilho, "iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network", Scientific Reports, 2019;9(1):11591.
   Abstract DOI PMID Download Cited by ~66
5. C. Jacobs and B. van Ginneken, "Google's lung cancer AI: a promising tool that needs further validation", Nature Reviews Clinical Oncology, 2019;16(9):532-533.
   Abstract DOI PMID Download Cited by ~27
6. G. Chlebus, H. Meine, S. Thoduka, N. Abolmaali, B. van Ginneken, H. Hahn and A. Schenk, "Reducing inter-observer variability and interaction time of MR liver volumetry by combining automatic CNN-based liver segmentation and manual corrections", PLoS One, 2019;14(5):e0217228.
   Abstract DOI PMID Cited by ~41
7. A. Schreuder, C. Jacobs, L. Gallardo-Estrella, M. Prokop, C. Schaefer-Prokop and B. van Ginneken, "Predicting all-cause and lung cancer mortality using emphysema score progression rate between baseline and follow-up chest CT images: A comparison of risk model performances", PLoS One, 2019;14(2):e0212756.
   Abstract DOI PMID Download Cited by ~3
8. N. Lessmann, B. van Ginneken, P. de Jong and I. Išgum, "Iterative fully convolutional neural networks for automatic vertebra segmentation and identification", Medical Image Analysis, 2019;53:142-155.
   Abstract DOI PMID arXiv Download Cited by ~182
9. 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", Scientific Reports, 2019;9(1).
   Abstract DOI PMID arXiv Cited by ~128
10. J. Charbonnier, E. Pompe, C. Moore, S. Humphries, B. van Ginneken, B. Make, E. Regan, J. Crapo, E. van Rikxoort and D. Lynch, "Airway wall thickening on CT: Relation to smoking status and severity of COPD", Respiratory Medicine, 2019;146:36-41.
    Abstract DOI PMID Download Cited by ~49
11. N. Lessmann, P. de Jong, C. Celeng, R. Takx, M. 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, 2019;12:1808-1817.
    Abstract DOI PMID Download Cited by ~22
12. T. van den Heuvel, H. Petros, S. Santini, C. 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 DOI PMID Download Cited by ~68
13. B. van Ginneken, "Deep Learning for Triage of Chest Radiographs: Should Every Institution Train Its Own System?", Radiology, 2019;290:545-546.
    Abstract DOI PMID Cited by ~10
14. M. Tammemagi, A. Ritchie, S. Atkar-Khattra, B. Dougherty, C. Sanghera, J. Mayo, R. Yuan, D. Manos, A. 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. 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(2):203-211.
    Abstract DOI PMID Cited by ~35
15. S. van Riel, C. Jacobs, E. Scholten, R. Wittenberg, M. Winkler Wille, B. de Hoop, R. Sprengers, O. 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 DOI PMID Download Cited by ~44
16. A. Patel, S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Image Level Training and Prediction: Intracranial Hemorrhage Identification in 3D Non-Contrast CT", IEEE Access, 2019;7(1):92355-92364.
    Abstract DOI Cited by ~45
17. 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
18. S. van de Leemput, M. Meijs, A. Patel, F. Meijer, B. van Ginneken and R. Manniesing, "Multiclass Brain Tissue Segmentation in 4D CT using Convolutional Neural Networks", IEEE Access, 2019;7(1):51557-51569.
    Abstract DOI Cited by ~13

Preprints

1. P. Bilic, P. Christ, E. Vorontsov, G. Chlebus, H. Chen, Q. Dou, C. Fu, X. Han, P. Heng, J. Hesser, S. Kadoury, T. Konopczynski, M. Le, C. Li, X. Li, J. Lipkova, J. Lowengrub, H. Meine, J. Moltz, C. Pal, M. Piraud, X. Qi, J. Qi, M. Rempfler, K. Roth, A. Schenk, A. Sekuboyina, E. Vorontsov, P. Zhou, C. Hulsemeyer, M. Beetz, F. Ettlinger, F. Gruen, G. Kaissis, F. Lohofer, R. Braren, J. Holch, F. Hofmann, W. Sommer, V. Heinemann, C. Jacobs, G. Humpire Mamani, B. van Ginneken, G. Chartrand, A. Tang, M. Drozdzal, A. Ben-Cohen, E. Klang, 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. Menze, "The Liver Tumor Segmentation Benchmark (LiTS)", arXiv:1901.04056, 2019.
   Abstract arXiv Cited by ~627
2. M. Argus, C. Schaefer-Prokop, D. Lynch and B. van Ginneken, "Function Follows Form: Regression from Complete Thoracic Computed Tomography Scans", arXiv:1909.12047, 2019.
   Abstract arXiv
3. A. Simpson, M. Antonelli, S. Bakas, M. Bilello, K. Farahani, B. van Ginneken, A. Kopp-Schneider, B. Landman, G. Litjens, B. Menze, O. Ronneberger, R. Summers, P. Bilic, P. Christ, R. Do, M. Gollub, J. Golia-Pernicka, S. Heckers, W. Jarnagin, M. McHugo, S. Napel, E. Vorontsov, L. Maier-Hein and M. Cardoso, "A large annotated medical image dataset for the development and evaluation of segmentation algorithms", arXiv:1902.09063, 2019.
   Abstract arXiv Cited by ~665
4. B. Liefers, J. Colijn, C. González-Gonzalo, T. Verzijden, P. Mitchell, C. Hoyng, B. van Ginneken, C. Klaver and C. Sánchez, "A deep learning model for segmentation of geographic atrophy to study its long-term natural history", arXiv:1908.05621, 2019.
   Abstract arXiv Cited by ~36
5. C. González-Gonzalo, B. Liefers, B. van Ginneken and C. Sánchez, "Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks", arXiv:1910.07373, 2019.
   Abstract arXiv
6. K. Murphy, S. Habib, S. Zaidi, S. Khowaja, A. Khan, J. Melendez, E. Scholten, F. Amad, S. Schalekamp, M. Verhagen, R. Philipsen, A. Meijers and B. van Ginneken, "Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system", arXiv:1903.03349, 2019.
   Abstract arXiv Cited by ~113
7. L. Maier-Hein, A. Reinke, M. Kozubek, A. L. Martel, T. Arbel, M. Eisenmann, A. Hanbuary, P. Jannin, H. Muller, S. Onogur, J. Saez-Rodriguez, B. van Ginneken, A. Kopp-Schneider and B. Landman, "BIAS: Transparent reporting of biomedical image analysis challenges", arXiv:1910.04071, 2019.
   Abstract arXiv Cited by ~84

Papers in conference proceedings

1. E. Calli, K. Murphy, E. Sogancioglu and B. van Ginneken, "FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis", Medical Imaging with Deep Learning, 2019.
   Abstract Url Cited by ~15
2. B. Liefers, C. González-Gonzalo, C. Klaver, B. van Ginneken and C. Sánchez, "Dense Segmentation in Selected Dimensions: Application to Retinal Optical Coherence Tomography", Medical Imaging with Deep Learning, 2019;102:337-346.
   Abstract Url Cited by ~11
3. A. Hering, B. van Ginneken and S. Heldmann, "mlVIRNET: Multilevel Variational Image Registration Network", Medical Image Computing and Computer-Assisted Intervention, 2019;11769:257-265.
   Abstract DOI arXiv Cited by ~54
4. T. van der Ouderaa, D. Worrall and B. van Ginneken, "Chest CT Super-resolution and Domain-adaptation using Memory-efficient 3D Reversible GANs", Medical Imaging with Deep Learning, 2019.
   Abstract Url Cited by ~5
5. T. van den Heuvel, C. de Korte and B. van Ginneken, "Automated interpretation of prenatal ultrasound using a predefined acquisition protocol in resource-limited countries", Medical Imaging with Deep Learning, 2019.
   Abstract Url Cited by ~4
6. N. Lessmann, J. Wolterink, M. Zreik, M. Viergever, B. van Ginneken and I. Isgum, "Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network", Medical Imaging with Deep Learning, 2019.
   Abstract arXiv Cited by ~1
7. E. Calli, E. Sogancioglu, E. Scholten, K. Murphy and B. van Ginneken, "Handling label noise through model confidence and uncertainty: application to chest radiograph classification", Medical Imaging, 2019(1).
   Abstract DOI Cited by ~17

Abstracts

1. T. van den Heuvel, B. van Ginneken and C. de Korte, "Improving Maternal Care In Resource-Limited Settings Using A Low-Cost Ultrasound Device And Machine Learning", Dutch Bio-Medical Engineering Conference, 2019.
   Abstract
2. C. Jacobs, E. Scholten, A. Schreuder, M. Prokop and B. van Ginneken, "An observer study comparing radiologists with the prize-winning lung cancer detection algorithms from the 2017 Kaggle Data Science Bowl", Annual Meeting of the Radiological Society of North America, 2019.
   Abstract
3. C. Jacobs and B. van Ginneken, "Deep learning for detection and characterization of lung nodules", Annual Meeting of the European Society of Thoracic Imaging, 2019.
   Abstract
4. G. Chlebus, G. Humpire Mamani, A. Schenk, B. van Ginneken and H. Meine, "Mimicking radiologists to improve the robustness of deep-learning based automatic liver segmentation", Annual Meeting of the Radiological Society of North America, 2019.
   Abstract
5. M. Silva, G. Milanese, F. Sabia, C. Jacobs, B. van Ginneken, M. Prokop, C. Schaefer-Prokop, A. Marchiano, N. Sverzellati and U. Pastorino, "Lung cancer risk after baseline round of screening: Only 20% of NLST eligibles require annual round", Annual Meeting of the European Society of Thoracic Imaging, 2019.
   Abstract
6. M. Silva, G. Milanese, F. Sabia, C. Jacobs, B. van Ginneken, M. Prokop, C. Schaefer-Prokop, S. Sestini, A. Marchiano, N. Sverzellati and U. Pastorino, "Lung Cancer Screening in NLST Eligibles: Tailoring Annual Low-Dose Computed Tomography by Post-Test Risk Stratification", Annual Meeting of the Radiological Society of North America, 2019.
   Abstract
7. H. van Zeeland, J. Meakin, B. Liefers, C. González-Gonzalo, A. Vaidyanathan, B. van Ginneken, C. Klaver and C. Sánchez, "EyeNED workstation: Development of a multi-modal vendor-independent application for annotation, spatial alignment and analysis of retinal images", Association for Research in Vision and Ophthalmology, 2019.
   Abstract Cited by ~1

PhD theses

1. N. Lessmann, "Machine Learning based quantification of extrapulmonary diseases in chest CT", PhD thesis, 2019.
   Abstract Url
2. E. Smit, "Feasibility of a single-acquisition CT stroke protocol", PhD thesis, 2019.
   Abstract
3. T. van den Heuvel, "Automated low-cost ultrasound: improving antenatal care in resource-limited settings", PhD thesis, 2019.
   Abstract Url
4. L. Estrella, "Quantification of COPD biomarkers in thoracic CT scans", PhD thesis, 2019.
   Abstract Url
5. R. Philipsen, "Automated chest radiography reading. Improvements, validation, and cost-effectiveness analysis", PhD thesis, 2019.
   Abstract Url
6. F. Venhuizen, "Machine Learning for Quantification of Age-Related Macular Degeneration Imaging Biomarkers in Optical Coherence Tomography", PhD thesis, 2019.
   Abstract Url