Publications

2017

Papers in international journals

  1. 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.
    Abstract DOI PMID Cited by ~75
  2. 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.
    Abstract DOI PMID Cited by ~791
  3. 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.
    Abstract DOI PMID Cited by ~7
  4. 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.
    Abstract DOI PMID Cited by ~13
  5. 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.
    Abstract DOI PMID Cited by ~19
  6. 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", Nature Scientific Reports, 2017;7.
    Abstract DOI PMID
  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.
    Abstract DOI PMID Cited by ~18
  8. T. Kooi and N. Karssemeijer, "Classifying Symmetrical Differences and Temporal Change in Mammography Using Deep Neural Networks", Journal of Medical Imaging, 2017;4(4):International Society for Optics and Photonics.
    Abstract DOI PMID Cited by ~6
  9. 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", Nature Scientific Reports, 2017(46479).
    Abstract DOI PMID arXiv Cited by ~171
  10. 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.
    Abstract DOI PMID Cited by ~18
  11. 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.
    Abstract DOI PMID Cited by ~48
  12. 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.
    Abstract DOI PMID Cited by ~10
  13. 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.
    Abstract DOI PMID arXiv Cited by ~3681
  14. 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.
    Abstract DOI PMID Cited by ~7
  15. 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.
    Abstract DOI PMID arXiv Cited by ~291
  16. 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.
    Abstract DOI PMID Cited by ~59
  17. 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.
    Abstract DOI PMID
  18. 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", Nature Scientific Reports, 2017;7(1):5110.
    Abstract DOI PMID arXiv Cited by ~117
  19. 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.
    Abstract DOI PMID Cited by ~32
  20. 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.
    Abstract DOI PMID Cited by ~28
  21. 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.
    Abstract DOI PMID Cited by ~9
  22. 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.
    Abstract DOI PMID Cited by ~8
  23. 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.
    Abstract DOI PMID Cited by ~5
  24. 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.
    Abstract DOI PMID Cited by ~21
  25. 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.
    Abstract DOI PMID Cited by ~8
  26. 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.
    Abstract DOI PMID Cited by ~37
  27. 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.
    Abstract DOI PMID Cited by ~10
  28. 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.
    Abstract DOI PMID Cited by ~2
  29. 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.
    Abstract DOI PMID
  30. 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.
    Abstract DOI PMID Cited by ~32
  31. 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.
    Abstract DOI PMID Cited by ~28
  32. 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", Nature Scientific Reports, 2017;7(119).
    Abstract DOI PMID Cited by ~17
  33. 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.
    Abstract DOI PMID Cited by ~85
  34. 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.
    Abstract DOI PMID Cited by ~6
  35. 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.
    Abstract DOI PMID Cited by ~76
  36. 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.
    Abstract DOI PMID Cited by ~5
  37. 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.
    Abstract DOI PMID Cited by ~21
  38. 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.
    Abstract DOI PMID Cited by ~17
  39. 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.
    Abstract DOI PMID Cited by ~4
  40. S. Steens, E. Bekers, W. Weijs, G. Litjens, A. Veltien, A. Maat, G. van den Broek, J. van der Laak, J. Fütterer, 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.
    Abstract DOI PMID
  41. 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.
    Abstract DOI PMID Cited by ~63
  42. 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.
    Abstract DOI PMID Cited by ~11
  43. 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.
    Abstract DOI PMID Cited by ~14
  44. 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.
    Abstract DOI PMID Cited by ~113
  45. 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.
    Abstract DOI PMID Cited by ~57
  46. 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.
    Abstract DOI PMID Cited by ~23
  47. 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.
    Abstract DOI PMID Cited by ~49
  48. 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.
    Abstract DOI PMID Cited by ~7
  49. 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.
    Abstract DOI PMID Cited by ~10
  50. 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.
    Abstract DOI PMID Cited by ~432
  51. 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.
    Abstract DOI PMID Cited by ~15
  52. N. Moriakov, "On Effective Birkhoff's Ergodic Theorem for Computable Actions of Amenable Groups", Theory of Computing Systems, 2017.
    Abstract DOI

Papers in conference proceedings

  1. 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.
    Abstract DOI PMID arXiv Cited by ~38
  2. 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.
    Abstract DOI arXiv Cited by ~124
  3. 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.
    Abstract DOI Cited by ~6
  4. T. Kooi, J. Mordang and N. Karssemeijer, "Conditional Random Field Modelling of Interactions Between Findings in Mammography", Medical Imaging, 2017;10133:101341E.
    Abstract DOI Cited by ~2
  5. 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.
    Abstract DOI arXiv Cited by ~75
  6. 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.
    Abstract DOI Cited by ~10
  7. T. Kooi and N. Karssemeijer, "Deep learning of symmetrical discrepancies for computer-aided detection of mammographic masses", Medical Imaging, 2017;10133:101341J.
    Abstract DOI Cited by ~7
  8. 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.
    Abstract DOI Cited by ~1
  9. 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.
    Abstract DOI arXiv Cited by ~14
  10. 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.
    Abstract DOI Cited by ~4
  11. 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.
    Abstract DOI Cited by ~4

Abstracts

  1. 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.
    Abstract
  2. 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.
    Abstract
  3. 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.
    Abstract
  4. 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.
    Abstract
  5. 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.
    Abstract
  6. 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.
    Abstract
  7. 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.
    Abstract
  8. 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.
    Abstract
  9. 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.
    Abstract
  10. N. Lessmann, B. van Ginneken, P. de Jong, W. Veldhuis, M. Viergever and I. Išgum, "Deep learning analysis for automatic calcium scoring in routine chest CT", Annual Meeting of the Radiological Society of North America, 2017.
    Abstract
  11. 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.
    Abstract
  12. M. Zreik, N. Lessmann, R. van Hamersvelt, J. Wolterink, M. Voskuil, M. Viergever, T. Leiner and I. Išgum, "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.
    Abstract
  13. 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.
    Abstract
  14. 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.
    Abstract
  15. 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.
    Abstract
  16. R. van Hamersvelt, M. Zreik, N. Lessmann, J. Wolterink, M. Voskuil, M. Viergever, T. Leiner and I. Išgum, "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.
    Abstract
  17. 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.
    Abstract
  18. B. de Vos, N. Lessmann, P. de Jong, M. Viergever and I. Išgum, "Direct coronary artery calcium scoring in low-dose chest CT using deep learning analysis", Annual Meeting of the Radiological Society of North America, 2017.
    Abstract
  19. 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.
    Abstract Cited by ~2
  20. L. Stoilescu and H. Huisman, "Feasibility of multireferencetissue normalization of T2weighted prostate MRI", Annual Meeting of the Radiological Society of North America, 2017.
    Abstract

PhD theses

  1. T. Kockelkorn, "Interactive texture analysis in chest CT Scans", 2017.
    Abstract Url
  2. J. Charbonnier, "Segmentation & quantification of airways and blood vessels in chest CT", 2017.
    Abstract Url
  3. K. Holland, "Breast density measurement for personalised screening", 2017.
    Abstract Url
  4. B. Bejnordi, "Histopathological diagnosis of breast cancer using machine learning", 2017.
    Abstract Url