B. Bejnordi, G. Zuidhof, M. Balkenhol, M. Hermsen, P. Bult, B. van Ginneken, N. Karssemeijer, G. Litjens and J. van der Laak, "Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images",
Journal of Medical Imaging,
2017;4(4):044504.
B. Ehteshami Bejnordi, M. Veta, P. van Diest, B. van Ginneken, N. Karssemeijer, G. Litjens, J. van der Laak, T. Consortium, M. Hermsen, Q. Manson, M. Balkenhol, O. Geessink, N. Stathonikos, M. van Dijk, P. Bult, F. Beca, A. Beck, D. Wang, A. Khosla, R. Gargeya, H. Irshad, A. Zhong, Q. Dou, Q. Li, H. Chen, H. Lin, P. Heng, C. Haß, E. Bruni, Q. Wong, U. Halici, M. Öner, R. Cetin-Atalay, M. Berseth, V. Khvatkov, A. Vylegzhanin, O. Kraus, M. Shaban, N. Rajpoot, R. Awan, K. Sirinukunwattana, T. Qaiser, Y. Tsang, D. Tellez, J. Annuscheit, P. Hufnagl, M. Valkonen, K. Kartasalo, L. Latonen, P. Ruusuvuori, K. Liimatainen, S. Albarqouni, B. Mungal, A. George, S. Demirci, N. Navab, S. Watanabe, S. Seno, Y. Takenaka, H. Matsuda, H. Ahmady Phoulady, V. Kovalev, A. Kalinovsky, V. Liauchuk, G. Bueno, M. Fernandez-Carrobles, I. Serrano, O. Deniz, D. Racoceanu and R. Venâncio, "Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer",
Journal of the American Medical Association,
2017;318(22):2199-2210.
L. Gallardo-Estrella, E. Pompe, P. de Jong, C. Jacobs, E. van Rikxoort, M. Prokop, C. Sánchez and B. van Ginneken, "Normalized emphysema scores on low dose CT: Validation as an imaging biomarker for mortality",
PLoS One,
2017;12(12):e0188902.
B. Liefers, F. Venhuizen, V. Schreur, B. van Ginneken, C. Hoyng, S. Fauser, T. Theelen and C. Sánchez, "Automatic detection of the foveal center in optical coherence tomography",
Biomedical Optics Express,
2017;8(11):5160-5178.
K. Holland, I. Sechopoulos, R. Mann, G. den Heeten, C. van Gils and N. Karssemeijer, "Influence of breast compression pressure on the performance of population-based mammography screening",
Breast Cancer Research,
2017;19(1):126.
M. Meijs, A. Patel, S. van de Leemput, M. Prokop, E. van Dijk, F. de Leeuw, F. Meijer, B. van Ginneken and R. Manniesing, "Robust Segmentation of the Full Cerebral Vasculature in 4D CT Images of Suspected Stroke Patients",
Scientific Reports,
2017;7.
S. van Riel, F. Ciompi, M. Winkler Wille, A. Dirksen, S. Lam, E. Scholten, S. Rossi, N. Sverzellati, M. Naqibullah, R. Wittenberg, M. Hovinga-de Boer, M. Snoeren, L. Peters-Bax, O. Mets, M. Brink, M. Prokop, C. Schaefer-Prokop and B. van Ginneken, "Malignancy risk estimation of pulmonary nodules in screening CTs: Comparison between a computer model and human observers",
PLoS One,
2017;12(11):e0185032.
T. Kooi and N. Karssemeijer, "Classifying symmetrical differences and temporal change for the detection of malignant masses in mammography using deep neural networks",
Journal of Medical Imaging,
2017;4(4):International Society for Optics and Photonics.
E. Gray, A. Donten, N. Karssemeijer, C. van Gils, D. Evans, S. Astley and K. Payne, "Evaluation of a Stratified National Breast Screening Program in the United Kingdom: An Early Model-Based Cost-Effectiveness Analysis",
Value in Health,
2017;20:1100-1109.
F. Ciompi, K. Chung, S. van Riel, A. Setio, P. Gerke, C. Jacobs, E. Scholten, C. Schaefer-Prokop, M. Wille, A. Marchiano, U. Pastorino, M. Prokop and B. van Ginneken, "Towards automatic pulmonary nodule management in lung cancer screening with deep learning",
Scientific Reports,
2017(46479).
E. van Leijsen, I. van Uden, M. Ghafoorian, M. Bergkamp, V. Lohner, E. Kooijmans, H. van der Holst, A. Tuladhar, D. Norris, E. van Dijk, L. Rutten-Jacobs, B. Platel, C. Klijn and F. de Leeuw, "Nonlinear temporal dynamics of cerebral small vessel disease The RUN DMC study",
Neurology,
2017;89(15):1569-1577.
W. Venderink, M. van der Leest, A. van Luijtelaar, W. van de Ven, J. Futterer, J. Sedelaar and H. Huisman, "Retrospective comparison of direct in-bore magnetic resonance imaging (MRI) guided biopsy and fusion guided biopsy in patients with MRI lesions which are likely or highly likely to be clinically significant prostate cancer",
World Journal of Urology,
2017;35(12):1849-1855.
A. Devaraj, B. van Ginneken, A. Nair and D. Baldwin, "Use of Volumetry for Lung Nodule Management: Theory and Practice",
Radiology,
2017;284(3):630-644.
J. Melendez, R. Philipsen, P. Chanda-Kapata, V. Sunkutu, N. Kapata and B. van Ginneken, "Automatic versus human reading of chest X-rays in the Zambia National Tuberculosis Prevalence Survey",
International Journal of Tuberculosis and Lung Disease,
2017;21(8):880-886.
G. Litjens, T. Kooi, B. Ehteshami Bejnordi, A. Setio, F. Ciompi, M. Ghafoorian, J. van der Laak, B. van Ginneken and C. Sánchez, "A Survey on Deep Learning in Medical Image Analysis",
Medical Image Analysis,
2017;42:60-88.
E. Gibson, Y. Hu, H. Huisman and D. Barratt, "Designing image segmentation studies: statistical power, sample size and reference standard quality",
Medical Image Analysis,
2017;42:44-59.
A. Setio, A. Traverso, T. de Bel, M. Berens, C. Bogaard, P. Cerello, H. Chen, Q. Dou, M. Fantacci, B. Geurts, R. Gugten, P. Heng, B. Jansen, M. de Kaste, V. Kotov, J. Lin, J. Manders, A. Sonora-Mengana, J. Garcia-Naranjo, E. Papavasileiou, M. Prokop, M. Saletta, C. Schaefer-Prokop, E. Scholten, L. Scholten, M. Snoeren, E. Torres, J. Vandemeulebroucke, N. Walasek, G. Zuidhof, B. Ginneken and C. Jacobs, "Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge",
Medical Image Analysis,
2017;42:1-13.
F. Venhuizen, B. van Ginneken, B. Liefers, Schreur, M. van Grinsven, S. Fauser, C. Hoyng, T. Theelen and C. Sánchez, "Robust Total Retina Thickness Segmentation in Optical Coherence Tomography Images using Convolutional Neural Networks",
Biomedical Optics Express,
2017;8(7):3292-3316.
T. van den Heuvel, D. Graham, K. Smith, C. de Korte and J. Neasham, "Development of a Low-Cost Medical Ultrasound Scanner Using a Monostatic Synthetic Aperture",
IEEE Transactions on Biomedical Circuits and Systems,
2017;11(4):849-857.
M. Ghafoorian, N. Karssemeijer, T. Heskes, I. van Uden, C. Sánchez, G. Litjens, F. de Leeuw, B. van Ginneken, E. Marchiori and B. Platel, "Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities",
Scientific Reports,
2017;7(1):5110.
A. Bankier, H. MacMahon, J. Goo, G. Rubin, C. Schaefer-Prokop and D. Naidich, "Recommendations for Measuring Pulmonary Nodules at CT: A Statement from the Fleischner Society",
Radiology,
2017;285:584-600.
J. Milenković, M. Dalmış, J. Zgajnar and B. Platel, "Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol",
Medical Physics,
2017;44:4652-4664.
J. van Zelst, R. Mus, G. Woldringh, M. Rutten, P. Bult, S. Vreemann, M. de Jong, N. Karssemeijer, N. Hoogerbrugge and R. Mann, "Surveillance of Women with the BRCA1 or BRCA2 Mutation by Using Biannual Automated Breast US, MR Imaging, and Mammography",
Radiology,
2017;285(2):376-388.
J. Wanders, K. Holland, N. Karssemeijer, P. Peeters, W. Veldhuis, R. Mann and C. van Gils, "The effect of volumetric breast density on the risk of screen-detected and interval breast cancers: a cohort study",
Breast Cancer Research,
2017;19(1):67.
J. van Zelst, M. Balkenhol, T. Tan, M. Rutten, M. Imhof-Tas, P. Bult, N. Karssemeijer and R. Mann, "Sonographic Phenotypes of Molecular Subtypes of Invasive Ductal Cancer in Automated 3-D Breast Ultrasound",
Ultrasound in Medicine and Biology,
2017;43(9):1820-1828.
B. Lassen-Schmidt, J. Kuhnigk, O. Konrad, B. van Ginneken and E. van Rikxoort, "Fast interactive segmentation of the pulmonary lobes from thoracic computed tomography data",
Physics in Medicine and Biology,
2017;62(16):6649-6665.
A. Castells-Nobau, B. Nijhof, I. Eidhof, L. Wolf, J. Scheffer-de Gooyert, I. Monedero, L. Torroja, J. van der Laak and A. Schenck, "Two Algorithms for High-throughput and Multi-parametric Quantification of Drosophila Neuromuscular Junction Morphology",
JoVE,
2017;123(e55395):1-13.
S. Vreemann, A. Rodriguez-Ruiz, D. Nickel, L. Heacock, L. Appelman, J. van Zelst, N. Karssemeijer, E. Weiland, M. Maas, L. Moy, B. Kiefer and R. Mann, "Compressed Sensing for Breast MRI: Resolving the Trade-Off Between Spatial and Temporal Resolution",
Investigative Radiology,
2017;52(10):574-582.
K. Chung, C. Jacobs, E. Scholten, O. Mets, I. Dekker, M. Prokop, B. van Ginneken and C. Schaefer-Prokop, "Malignancy estimation of Lung-RADS criteria for subsolid nodules on CT: accuracy of low and high risk spectrum when using NLST nodules",
European Radiology,
2017;27:4672-4679.
F. Venhuizen, B. van Ginneken, F. van Asten, M. van Grinsven, S. Fauser, C. Hoyng, T. Theelen and C. Sánchez, "Automated Staging of Age-Related Macular Degeneration Using Optical Coherence Tomography",
Investigative Ophthalmology and Visual Science,
2017;58(4):2318-2328.
E. Pompe, P. de Jong, D. Lynch, N. Lessmann, I. Išgum, B. van Ginneken, J. Lammers and F. Mohamed Hoesein, "Computed tomographic findings in subjects who died from respiratory disease in the National Lung Screening Trial",
European Respiratory Journal,
2017;49(4):1601814.
L. Gallardo Estrella, E. Pompe, J. Kuhnigk, D. Lynch, S. Bhatt, B. van Ginneken and E. van Rikxoort, "Computed tomography quantification of tracheal abnormalities in COPD and their influence on airflow limitation",
Medical Physics,
2017;44(7):3594-3603.
U. Yousaf-Khan, C. van der Aalst, P. de Jong, M. Heuvelmans, E. Scholten, J. Walter, K. Nackaerts, H. Groen, R. Vliegenthart, K. Ten Haaf, M. Oudkerk and H. de Koning, "Risk stratification based on screening history: the NELSON lung cancer screening study",
Thorax,
2017;72(9):819-824.
K. Chung, C. Jacobs, E. Scholten, J. Goo, H. Prosch, N. Sverzellati, F. Ciompi, O. Mets, P. Gerke, M. Prokop, B. van Ginneken and C. Schaefer-Prokop, "Lung-RADS Category 4X: Does It Improve Prediction of Malignancy in Subsolid Nodules?",
Radiology,
2017;284(1):264-271.
Y. Suzuki, N. Fujima, T. Ogino, J. Meakin, A. Suwa, H. Sugimori, M. Van Cauteren and M. van Osch, "Acceleration of ASL-based time-resolved MR angiography by acquisition of control and labeled images in the same shot (ACTRESS)",
Magnetic Resonance in Medicine,
2017;79:224-233.
S. van Riel, F. Ciompi, C. Jacobs, M. Winkler Wille, E. Scholten, M. Naqibullah, S. Lam, M. Prokop, C. Schaefer-Prokop and B. van Ginneken, "Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines",
European Radiology,
2017;27(10):4019-4029.
R. Manniesing, M. Oei, L. Oostveen, J. Melendez, E. Smit, B. Platel, C. Sánchez, F. Meijer, M. Prokop and B. van Ginneken, "White Matter and Gray Matter Segmentation in 4D Computed Tomography",
Scientific Reports,
2017;7(119).
M. Ghafoorian, N. Karssemeijer, T. Heskes, M. Bergkamp, J. Wissink, J. Obels, K. Keizer, F. de Leeuw, B. Ginneken, E. Marchiori and B. Platel, "Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin",
NeuroImage: Clinical,
2017;14:391-399.
R. Mus, C. Borelli, P. Bult, E. Weiland, N. Karssemeijer, J. Barentsz, A. Gubern-Mérida, B. Platel and R. Mann, "Time to enhancement derived from ultrafast breast MRI as a novel parameter to discriminate benign from malignant breast lesions",
European Journal of Radiology,
2017;89:90-96.
J. van Zelst, T. Tan, B. Platel, M. de Jong, A. Steenbakkers, M. Mourits, A. Grivegnee, C. Borelli, N. Karssemeijer and R. Mann, "Improved cancer detection in automated breast ultrasound by radiologists using Computer Aided Detection",
European Journal of Radiology,
2017;89:54-59.
K. Holland, A. Gubern-Mérida, R. Mann and N. Karssemeijer, "Optimization of volumetric breast density estimation in digital mammograms",
Physics in Medicine and Biology,
2017;62(9):3779-3797.
B. van Ginneken, "Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning",
Radiological Physics and Technology,
2017;10(1):23-32.
J. Mordang, A. Gubern-Merida, A. Bria, F. Tortorella, G. den Heeten and N. Karssemeijer, "Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings",
Medical Physics,
2017;44(4):1390-1401.
K. Holland, C. van Gils, R. Mann and N. Karssemeijer, "Quantification of masking risk in screening mammography with volumetric breast density maps",
Breast Cancer Research and Treatment,
2017;162(3):541-548.
S. Laban, G. Giebel, N. Klümper, A. Schröck, J. Doescher, G. Spagnoli, J. Thierauf, M. Theodoraki, R. Remark, S. Gnjatic, R. Krupar, A. Sikora, G. Litjens, N. Grabe, G. Kristiansen, F. Bootz, P. Schuler, C. Brunner, J. Brägelmann, T. Hoffmann and S. Perner, "MAGE expression in head and neck squamous cell carcinoma primary tumors, lymph node metastases and respective recurrences: implications for immunotherapy",
Oncotarget,
2017;8:14719-14735.
L. Hogeweg, C. Sánchez, P. Maduskar, R. Philipsen and B. van Ginneken, "Fast and effective quantification of symmetry in medical images for pathology detection: application to chest radiography",
Medical Physics,
2017;44(6):2242-2256.
S. Steens, E. Bekers, W. Weijs, G. Litjens, A. Veltien, A. Maat, G. van den Broek, J. van der Laak, J. Futterer, C. van der Kaa, M. Merkx and R. Takes, "Evaluation of tongue squamous cell carcinoma resection margins using ex-vivo MR.",
International Journal of Computer Assisted Radiology and Surgery,
2017;12(5):821-828.
T. Kooi, B. van Ginneken, N. Karssemeijer and A. den Heeten, "Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network",
Medical Physics,
2017;44(3):1017-1027.
T. Mertzanidou, J. Hipwell, S. Reis, D. Hawkes, B. Bejnordi, M. Dalmis, S. Vreemann, B. Platel, J. van der Laak, N. Karssemeijer, M. Hermsen, P. Bult and R. Mann, "3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imaging",
Medical Physics,
2017;44(3):935-948.
G. Bozovic, C. Adlercreutz, P. Höglund, I. Björkman-Burtscher, P. Reinstrup, R. Ingemansson, C. Schaefer-Prokop, R. Siemund and M. Geijer, "Imaging of the Lungs in Organ Donors and its Clinical Relevance",
Journal of Thoracic Imaging,
2017;32:107-114.
J. Cohen, H. Kim, S. Park, B. van Ginneken, G. Ferretti, C. Lee, J. Goo and C. Park, "Comparison of the effects of model-based iterative reconstruction and filtered back projection algorithms on software measurements in pulmonary subsolid nodules",
European Radiology,
2017;27:3266-3274.
M. Dalmis, G. Litjens, K. Holland, A. Setio, R. Mann, N. Karssemeijer and A. Gubern-Mérida, "Using deep learning to segment breast and fibroglandular tissue in MRI volumes",
Medical Physics,
2017;44(2):533-546.
J. Wanders, K. Holland, W. Veldhuis, R. Mann, R. Pijnappel, P. Peeters, C. van Gils and N. Karssemeijer, "Volumetric breast density affects performance of digital screening mammography",
Breast Cancer Research and Treatment,
2017;162(1):95-103.
A. Patel, B. van Ginneken, F. Meijer, E. van Dijk, M. Prokop and R. Manniesing, "Robust Cranial Cavity Segmentation in CT and CT Perfusion Images of Trauma and Suspected Stroke Patients",
Medical Image Analysis,
2017;36:216-228.
J. Charbonnier, E. van Rikxoort, A. Setio, C. Schaefer-Prokop, B. van Ginneken and F. Ciompi, "Improving Airway Segmentation in Computed Tomography using Leak Detection with Convolutional Networks",
Medical Image Analysis,
2017;36:52-60.
M. Oei, F. Meijer, W. van der Woude, E. Smit, B. van Ginneken, M. Prokop and R. Manniesing, "Interleaving cerebral CT perfusion with neck CT angiography part I. Proof of concept and accuracy of cerebral perfusion values",
European Radiology,
2017;27(6):2649-2656.
M. Oei, F. Meijer, W. van der Woude, E. Smit, B. van Ginneken, R. Manniesing and M. Prokop, "Interleaving cerebral CT perfusion with neck CT angiography. Part II: clinical implementation and image quality",
European Radiology,
2017;27(6):2411-2418.
T. Kooi, G. Litjens, B. van Ginneken, A. Gubern-Mérida, C. Sánchez, R. Mann, A. den Heeten and N. Karssemeijer, "Large scale deep learning for computer aided detection of mammographic lesions",
Medical Image Analysis,
2017;35:303-312.
O. Mets, P. de Jong, E. Scholten, K. Chung, B. van Ginneken and C. Schaefer-Prokop, "Subsolid pulmonary nodule morphology and associated patient characteristics in a routine clinical population",
European Radiology,
2017;27(2):689-696.
W. Mesker, G. van Pelt, A. Huijbers, J. van der Laak, E. Dequeker, J. Fléjou, R. Al Dieri, D. Kerr, J. Van Krieken and R. Tollenaar, "Improving treatment decisions in colon cancer: The tumor-stroma ratio (TSR) additional to the TNM classification",
Annals of Oncology,
2017;28:v190-v191.
T. Kooi and N. Karssemeijer, "Classifying Symmetrical Differences and Temporal Change in Mammography Using Deep Neural Networks",
arXiv:1703.07715,
2017.
B. Bejnordi, J. Lin, B. Glass, M. Mullooly, G. Gierach, M. Sherman, N. Karssemeijer, J. van der Laak and A. Beck, "Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images",
IEEE International Symposium on Biomedical Imaging,
2017:929-932.
T. Kooi and N. Karssemeijer, "Deep learning of symmetrical discrepancies for computer-aided detection of mammographic masses",
Medical Imaging,
2017;10133:101341J.
A. Mehrtash, A. Sedghi, M. Ghafoorian, M. Taghipour, C. Tempany, W. Wells, T. Kapur, P. Mousavi, P. Abolmaesumi and A. Fedorov, "Classification of clinical significance of MRI prostate findings using 3D convolutional neural networks",
Medical Imaging,
2017;10134:101342A-101342A-4.
F. Ciompi, O. Geessink, B. Bejnordi, G. de Souza, A. Baidoshvili, G. Litjens, B. van Ginneken, I. Nagtegaal and J. van der Laak, "The importance of stain normalization in colorectal tissue classification with convolutional networks",
IEEE International Symposium on Biomedical Imaging,
2017:160-163.
G. Humpire Mamani, A. Setio, B. van Ginneken and C. Jacobs, "Organ detection in thorax abdomen CT using multi-label convolutional neural networks",
Medical Imaging,
2017;10134.
T. van den Heuvel, H. Petros, S. Santini, C. de Korte and B. van Ginneken, "A step towards measuring the fetal head circumference with the use of obstetric ultrasound in a low resource setting",
Medical Imaging,
2017;10139:101390V.
M. Ghafoorian, A. Mehrtash, T. Kapur, N. Karssemeijer, E. Marchiori, M. Pesteie, C. Guttmann, F. de Leeuw, C. Tempany, B. van Ginneken, A. Fedorov, P. Abolmaesumi, B. Platel and W. Wells, "Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation",
Medical Image Computing and Computer-Assisted Intervention,
2017;10435:516-524.
T. Kooi, J. Mordang and N. Karssemeijer, "Conditional Random Field Modelling of Interactions Between Findings in Mammography",
Medical Imaging,
2017;10133:101341E.
C. Balta, R. Bouwman, I. Sechopoulos, M. Broeders, N. Karssemeijer, R. van Engen and W. Veldkamp, "Signal template generation from acquired mammographic images for the non-prewhitening model observer with eye-filter",
Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment,
2017.
T. van den Heuvel, H. Petros, S. Santini, C. de Korte and B. van Ginneken, "Combining Automated Image Analysis with Obstetric Sweeps for Prenatal Ultrasound Imaging in Developing Countries",
MICCAI} Workshop: Point-of-Care Ultrasound,
2017;10549:105-112.
A. Marchesi, A. Bria, C. Marrocco, M. Molinara, J. Mordang, F. Tortorella and N. Karssemeijer, "The Effect of Mammogram Preprocessing on Microcalcification Detection with Convolutional Neural Networks",
2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS),
2017.
P. Bándi, R. van de Loo, M. Intezar, D. Geijs, F. Ciompi, B. van Ginneken, J. van der Laak and G. Litjens, "Comparison of Different Methods for Tissue Segmentation In Histopathological Whole-Slide Images",
IEEE International Symposium on Biomedical Imaging,
2017:591-595.
A. Patel, S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Automatic Cerebrospinal Fluid Segmentation in Non-Contrast CT Images Using a 3D Convolutional Network",
Medical Imaging,
2017;10134.
B. Liefers, F. Venhuizen, T. Theelen, C. Hoyng, B. van Ginneken and C. Sánchez, "Fovea Detection in Optical Coherence Tomography using Convolutional Neural Networks",
Medical Imaging,
2017;10133:1013302.
B. de Vos, N. Lessmann, P. de Jong, M. Viergever and I. Isgum, "Direct coronary artery calcium scoring in low-dose chest CT using deep learning analysis",
Annual Meeting of the Radiological Society of North America,
2017.
T. van den Heuvel, C. de Korte and B. van Ginneken, "Automated Measurement of Fetal Head Circumference in Ultrasound Images",
Dutch Bio-Medical Engineering Conference,
2017.
A. Patel, F. Meijer, M. Prokop, B. van Ginneken and R. Manniesing, "Robust segmentation of the cranial cavity in non-contrast CT and CT perfusion of the brain",
European Congress of Radiology,
2017.
R. van Hamersvelt, M. Zreik, N. Lessmann, J. Wolterink, M. Voskuil, M. Viergever, T. Leiner and I. Isgum, "Improving Specificity of Coronary CT Angiography for the Detection of Functionally Significant Coronary Artery Disease: A Deep Learning Approach",
Annual Meeting of the Radiological Society of North America,
2017.
S. van de Leemput, F. Meijer, M. Prokop and R. Manniesing, "Cerebral white matter, gray matter and cerebrospinal fluid segmentation in CT using VCAST: a volumetric cluster annotation and segmentation tool",
European Congress of Radiology,
2017.
M. Zreik, N. Lessmann, R. van Hamersvelt, J. Wolterink, M. Voskuil, M. Viergever, T. Leiner and I. Isgum, "Deep learning analysis of the left ventricular myocardium in cardiac CT images enables detection of functionally significant coronary artery stenosis regardless of coronary anatomy",
Annual Meeting of the Radiological Society of North America,
2017.
N. Lessmann, B. van Ginneken, P. de Jong, W. Veldhuis, M. Viergever and I. Isgum, "Deep learning analysis for automatic calcium scoring in routine chest CT",
Annual Meeting of the Radiological Society of North America,
2017.
M. Silva, G. Capretti, N. Sverzellati, C. Jacobs, F. Ciompi, B. van Ginneken, C. Schaefer-Prokop, A. Marchianò and U. Pastorino, "Subsolid and part-solid nodules in lung cancer screening: comparison between visual and computer-aided detection",
European Congress of Radiology,
2017.
J. Gomez, C. Sánchez, B. Liefers, F. Venhuizen, G. Fatti, A. Morilla-Grasa, Y. Cartagena, A. Cabarcos, A. Santos, M. Ledesma-Carbayo and A. Anton-Lopez, "Automated Analysis of Retinal Images for detection of Glaucoma based on Convolutional Neural Networks",
Association for Research in Vision and Ophthalmology,
2017.
S. Pegge, M. Meijs, M. Prokop, R. Manniesing and F. Meijer, "Color-mapping of 4D-CTA for the detection and classification of cranial arteriovenous fistulas",
European Society of Neuroradiology,
2017.
M. Meijs, S. Pegge, M. Prokop, B. van Ginneken, F. Meijer and R. Manniesing, "Detection of vessel occlusion in acute stroke is facilitated by color-coded 4D-CTA",
European Congress of Radiology,
2017.
F. Venhuizen, S. Schaffhauser, V. Schreur, B. Liefers, B. van Ginneken, C. Hoyng, T. Theelen, E. de Jong and C. Sánchez, "Fully automated detection of hyperreflective foci in optical coherence tomography",
Association for Research in Vision and Ophthalmology,
2017.
L. Stoilescu and H. Huisman, "Feasibility of multireferencetissue normalization of T2weighted prostate MRI",
Annual Meeting of the Radiological Society of North America,
2017.
B. Liefers, F. Venhuizen, V. Schreur, B. van Ginneken, C. Hoyng, T. Theelen and C. Sánchez, "Automatic detection of the foveal center in optical coherence tomography",
Association for Research in Vision and Ophthalmology,
2017.
M. Hermsen, T. de Bel, M. van de Warenburg, J. Knuiman, E. Steenbergen, G. Litjens, B. Smeets, L. Hilbrands and J. van der Laak, "Automatic segmentation of histopathological slides from renal allograft biopsies using artificial intelligence",
Dutch Federation of Nephrology (NfN) Fall Symposium,
2017.
J. Teuwen, M. Kallenberg, A. Gubern-Merida, A. Rodriguez-Ruiz, N. Karssemeijer and R. Mann, "Automated pre-selection of mammograms without abnormalities using deep learning",
Annual Meeting of the Radiological Society of North America,
2017.
J. Bukala, G. Humpire Mamani, E. Scholten, M. Prokop, B. van Ginneken and C. Jacobs, "Fully Automatic Measurement of the Splenic Volume in CT with U-Net Convolutional Neural Networks",
Annual Meeting of the Radiological Society of North America,
2017.
M. Silva, G. Capretti, N. Sverzellati, C. Jacobs, F. Ciompi, B. van Ginneken, C. Schaefer-Prokop, M. Prokop, A. Marchiano and U. Pastorino, "Non-solid and Part-solid Nodules: Comparison Between Visual and Computer Aided Detection",
World Congress of Thoracic Imaging,
2017.
A. Schreuder, C. Schaefer-Prokop, E. Scholten, C. Jacobs, M. Prokop and B. van Ginneken, "Use of a risk model combining clinical information and CT findings to customize follow-up intervals in lung cancer screening",
Annual Meeting of the Radiological Society of North America,
2017.
L. Stoilescu, M. Maas and H. Huisman, "Feasibility of multireference tissue normalization of T2-weighted prostate MRI",
European Society for Magnetic Resonance in Medicine and Biology,
2017.
A. Bria, C. Marrocco, A. Galdran, A. Campilho, A. Marchesi, J. Mordang, N. Karssemeijer, M. Molinara and F. Tortorella, "Spatial Enhancement by Dehazing for Detection of Microcalcifications with Convolutional Nets",
Image Analysis and Processing - ICIAP 2017,
2017:288-298.
S. Balocco, F. Ciompi, J. Rigla, X. Carrillo, J. Mauri and P. Radeva, "Intra-coronary Stent Localization in Intravascular Ultrasound Sequences, A Preliminary Study",
Lecture Notes in Computer Science,
2017:12-19.