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Medical Imaging with Deep Learning,
2019.
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.
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.
K. Dercksen, W. Bulten and G. Litjens, "Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification",
Medical Imaging with Deep Learning,
2019.
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.
J. Bokhorst, H. Pinckaers, P. van Zwam, I. Nagetgaal, J. van der Laak and F. Ciompi, "Learning from sparsely annotated data for semantic segmentation in histopathology images",
Medical Imaging with Deep Learning,
2019;102:81-94.
C. Mercan, M. Balkenhol, J. van der Laak and F. Ciompi, "From Point Annotations to Epithelial Cell Detection in Breast Cancer Histopathology using RetinaNet",
Medical Imaging with Deep Learning,
2019.
T. de Bel, M. Hermsen, J. Kers, J. van der Laak and G. Litjens, "Stain-Transforming Cycle-Consistent Generative Adversarial Networks for Improved Segmentation of Renal Histopathology",
Medical Imaging with Deep Learning,
2019.
H. Pinckaers, W. Bulten and G. Litjens, "High resolution whole prostate biopsy classification using streaming stochastic gradient descent",
Medical Imaging,
2019(1).
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.
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.
S. van Velzen, M. Zreik, N. Lessmann, M. Viergever, P. de Jong, H. Verkooijen and I. Išgum, "Direct prediction of cardiovascular mortality from low-dose chest CT using deep learning",
Medical Imaging,
2019.
M. Kallenberg, D. Vanegas Camargo, M. Birhanu, A. Gubern-Mérida and N. Karssemeijer, "A deep learning method for volumetric breast density estimation from processed full field digital mammograms",
Medical Imaging 2019: Computer-Aided Diagnosis,
2019.
M. Hosseinzadeh, P. Brand and H. Huisman, "Effect of Adding Probabilistic Zonal Prior in Deep Learning-based Prostate Cancer Detection",
Medical Imaging with Deep Learning,
2019.
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).
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.
C. González-Gonzalo, B. Liefers, A. Vaidyanathan, H. van Zeeland, C. Klaver and C. Sánchez, "Opening the "black box" of deep learning in automated screening of eye diseases",
Association for Research in Vision and Ophthalmology,
2019.
S. van Velzen, N. Lessmann, M. Emaus, H. van den Bongard, H. Verkooijen and I. Isgum, "Deep learning for calcium scoring in radiotherapy treatment planning CT scans in breast cancer patients",
Annual Meeting of the Radiological Society of North America,
2019.
J. Bokhorst, H. Dawson, A. Blank, I. Zlobec, A. Lugli, M. Vieth, R. Kirsch, M. Urbanowicz, S. Brockmoeller, J. Flejou, L. Rijstenberg, J. van der Laak, F. Ciompi and I. Nagtegaal, "Assessment of tumor buds in colorectal cancer. A large-scale international digital observer study",
European Congress of Pathology,
2019.
M. Hermsen, T. de Bel, M. den Boer, E. Steenbergen, J. Kers, S. Florquin, J. Roelofs, M. Stegall, M. Alexander, B. Smith, B. Smeets, L. Hilbrands and J. van der Laak, "Deep learning-based histopathological assessment of renal tissue",
American Society of Nephrology Kidney Week 2019,
2019.
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.
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.
D. Grob, L. Oostveen, C. Jacobs, M. Prokop, C. Schaefer-Prokop, I. Sechopoulos and M. Brink, "Intra-patient comparison of pulmonary nodule enhancement in subtraction CT and dual-energy CT",
Annual Meeting of the European Society of Thoracic Imaging,
2019.
W. Aswolinskiy, H. Horlings, L. Mulder, J. van der Laak, J. Wesseling, E. Lips and F. Ciompi, "Potential of an AI-based digital biomarker to predict neoadjuvant chemotherapy response from preoperative biopsies of Luminal-B breast cancer",
European Congress of Pathology,
2019.
B. Liefers, J. Colijn, C. González-Gonzalo, A. Vaidyanathan, H. van Zeeland, P. Mitchell, C. Klaver and C. Sánchez, "Prediction of areas at risk of developing geographic atrophy in color fundus images using deep learning",
Association for Research in Vision and Ophthalmology,
2019.
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.
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.
W. Bulten, H. Pinckaers, C. Hulsbergen-van de Kaa and G. Litjens, "Automated Gleason Grading of Prostate Biopsies Using Deep Learning",
United States and Canadian Academy of Pathology (USCAP) 108th Annual Meeting,
2019.
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.
N. Khalili, N. Lessmann, E. Turk, M. Viergever, M. Benders and I. Isgum, "Brain tissue segmentation in fetal MRI using convolutional neural networks with simulated intensity inhomogeneities",
Annual Meeting of the International Society for Magnetic Resonance in Medicine,
2019.
D. Valkenburg, E. Runhart, B. Liefers, S. Lambertus, C. Sánchez, F. Cremers, B. Nathalie M and C. Hoyng, "Familial discordance in disease phenotype in siblings with Stargardt disease",
Association for Research in Vision and Ophthalmology,
2019.
S. van Velzen, J. Terry, B. de Vos, N. Lessmann, S. Nair, A. Correa, H. Verkooijen, J. Carr and I. Isgum, "Automatic prediction of coronary heart disease events using coronary and thoracic aorta calcium among african americans in the Jackson Heart Study",
Annual Meeting of the Radiological Society of North America,
2019.
J. Engelberts, C. González-Gonzalo, C. Sánchez and M. van Grinsven, "Automatic Segmentation of Drusen and Exudates on Color Fundus Images using Generative Adversarial Networks",
Association for Research in Vision and Ophthalmology,
2019.
C. van 't Klooster, H. Nathoe, J. Hjortnaes, M. Bots, I. Isgum, N. Lessmann, Y. van der Graaf, T. Leiner and F. Visseren, "Prevalence and risk factors of multifocal cardiovascular calcification in patients at high cardiovascular risk",
European Society of Cardiology Congress,
2019.
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.
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.
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.
T. Haddad, N. Farahani, J. Bokhorst, F. Doubrava-Simmer, F. Ciompi, I. Nagtegaal and J. van der Laak, "A Colorectal Carcinoma in 3D: Merging Knife-Edge Scanning Microscopy and Deep Learning",
EACR,
2019.
F. Venhuizen, "Machine Learning for Quantification of Age-Related Macular Degeneration Imaging Biomarkers in Optical Coherence Tomography",
PhD thesis,
2019.
G. Mooij, "Using GANs to synthetically stain histopathological images to generate training data for automatic mitosis detection in breast tissue",
Master thesis,
2019.
S. Hu, D. Worrall, S. Knegt, B. Veeling, H. Huisman and M. Welling, "Supervised Uncertainty Quantification for Segmentation with Multiple Annotations",
Lecture Notes in Computer Science,
2019:137-145.
A. Hering, S. Kuckertz, S. Heldmann and M. Heinrich, "Enhancing Label-Driven Deep Deformable Image Registration with Local Distance Metrics for State-of-the-Art Cardiac Motion Tracking",
Informatik aktuell,
2019:309-314.