Publications

2018

Papers in international journals

1. S. Armato, H. Huisman, K. Drukker, L. Hadjiiski, J. Kirby, N. Petrick, G. Redmond, M. Giger, K. Cha, A. Mamonov, J. Kalpathy-Cramer and K. Farahani, "The PROSTATEx Challenges for Computerized Classification of Prostate Lesions from Multi-Parametric Magnetic Resonance Images", Journal of Medical Imaging, 2018;5(4):044501.
   Abstract DOI PMID Cited by ~112
2. P. Bándi, O. Geessink, Q. Manson, M. van Dijk, M. Balkenhol, M. Hermsen, B. Bejnordi, B. Lee, K. Paeng, A. Zhong, Q. Li, F. Zanjani, S. Zinger, K. Fukuta, D. Komura, V. Ovtcharov, S. Cheng, S. Zeng, J. Thagaard, A. Dahl, H. Lin, H. Chen, L. Jacobsson, M. Hedlund, M. Cetin, E. Halici, H. Jackson, R. Chen, F. Both, J. Franke, H. Kusters-Vandevelde, W. Vreuls, P. Bult, B. van Ginneken, J. van der Laak and G. Litjens, "From detection of individual metastases to classification of lymph node status at the patient level: the CAMELYON17 challenge", IEEE Transactions on Medical Imaging, 2018;38(2):550-560.
   Abstract DOI PMID Cited by ~416
3. O. Mets, C. Schaefer-Prokop and P. de Jong, "Cyst-related primary lung malignancies: an important and relatively unknown imaging appearance of (early) lung cancer", European Respiratory Review, 2018;27:180079.
   Abstract DOI PMID Cited by ~16
4. L. Maier-Hein, M. Eisenmann, A. Reinke, S. Onogur, M. Stankovic, P. Scholz, T. Arbel, H. Bogunovic, A. Bradley, A. Carass, C. Feldmann, A. Frangi, P. Full, B. van Ginneken, A. Hanbury, K. Honauer, M. Kozubek, B. Landman, K. Marz, O. Maier, K. Maier-Hein, B. Menze, H. Muller, P. Neher, W. Niessen, N. Rajpoot, G. Sharp, K. Sirinukunwattana, S. Speidel, C. Stock, D. Stoyanov, A. Taha, F. van der Sommen, C. Wang, M. Weber, G. Zheng, P. Jannin and A. Kopp-Schneider, "Why rankings of biomedical image analysis competitions should be interpreted with care", Nature Communications, 2018;9(1):5217.
   Abstract DOI PMID Cited by ~254
5. C. Reijnen, H. Kusters-Vandevelde, K. Abbink, P. Zusterzeel, A. van Herwaarden, J. van der Laak, L. Massuger, M. Snijders, J. Pijnenborg and J. Bulten, "Quantification of Leydig cells and stromal hyperplasia in the postmenopausal ovary of women with endometrial carcinoma", Human Pathology, 2018.
   Abstract DOI PMID Cited by ~3
6. A. Nair, E. Bartlett, S. Walsh, A. Wells, N. Navani, G. Hardavella, S. Bhalla, L. Calandriello, A. Devaraj, J. Goo, J. Klein, H. MacMahon, C. Schaefer-Prokop, J. Seo, N. Sverzellati and S. Desai, "Variable radiological lung nodule evaluation leads to divergent management recommendations", European Respiratory Journal, 2018;52:1801359.
   Abstract DOI PMID Cited by ~31
7. O. Mets, C. Schaefer-Prokop and P. de Jong, "Primary lung cancer in patients with previous malignancies: a nationwide study", Thorax, 2018;74:492-495.
   Abstract DOI PMID Cited by ~1
8. 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, 2018;46(2):484-493.
   Abstract DOI PMID Cited by ~4
9. M. Bergkamp, J. Wissink, E. van Leijsen, M. Ghafoorian, D. Norris, E. van Dijk, B. Platel, A. Tuladhar and F. de Leeuw, "Risk of Nursing Home Admission in Cerebral Small Vessel Disease", Stroke, 2018;49(11):2659-2665.
   Abstract DOI PMID Cited by ~3
10. G. Chlebus, A. Schenk, J. Moltz, B. van Ginneken, H. Hahn and H. Meine, "Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing", Scientific Reports, 2018;8(1):15497.
    Abstract DOI PMID Cited by ~171
11. E. van Leijsen, J. Tay, I. van Uden, E. Kooijmans, M. Bergkamp, H. van der Holst, M. Ghafoorian, B. Platel, D. Norris, R. Kessels, H. Markus, A. Tuladhar and F. de Leeuw, "Memory decline in elderly with cerebral small vessel disease explained by temporal interactions between white matter hyperintensities and hippocampal atrophy", Hippocampus, 2018;29:500-510.
    Abstract DOI PMID Cited by ~29
12. D. Grob, L. Oostveen, M. Prokop, C. Schaefer-Prokop, I. Sechopoulos and M. Brink, "Imaging of pulmonary perfusion using subtraction CT angiography is feasible in clinical practice", European Radiology, 2018;29:1408-1414.
    Abstract DOI PMID Cited by ~19
13. T. van den Heuvel, D. de Bruijn, C. de Korte and B. van Ginneken, "Automated measurement of fetal head circumference using 2D ultrasound images", PLoS One, 2018;13(8).
    Abstract DOI PMID Cited by ~146
14. S. Zaidi, S. Habib, B. van Ginneken, R. Ferrand, J. Creswell, S. Khowaja and A. Khan, "Evaluation of the diagnostic accuracy of Computer-Aided Detection of tuberculosis on Chest radiography among private sector patients in Pakistan", Scientific Reports, 2018;8(1):12339.
    Abstract DOI PMID Cited by ~48
15. T. van den Heuvel, D. de Bruijn, D. de Moens-van Moesdijk, A. Beverdam, B. van Ginneken and C. de Korte, "Comparison Study of Low-Cost Ultrasound Devices for Estimation of Gestational Age in Resource-Limited Countries", Ultrasound in Medicine and Biology, 2018;44(11):2250-2260.
    Abstract DOI PMID Download Cited by ~11
16. R. Koesoemadinata, K. Kranzer, R. Livia, N. Susilawati, J. Annisa, N. Soetedjo, R. Ruslami, R. Philipsen, B. van Ginneken, R. Soetikno, R. van Crevel, B. Alisjahbana and P. Hill, "Computer-assisted chest radiography reading for tuberculosis screening in people living with diabetes mellitus", International Journal of Tuberculosis and Lung Disease, 2018;22(9):1088-1094.
    Abstract DOI PMID Download Cited by ~21
17. S. Vreemann, J. van Zelst, M. Schlooz-Vries, P. Bult, N. Hoogerbrugge, N. Karssemeijer, A. Gubern-Merida and R. Mann, "The added value of mammography in different age-groups of women with and without BRCA mutation screened with breast MRI", Breast Cancer Research, 2018;20(1):84.
    Abstract DOI PMID Cited by ~35
18. M. Silva, M. Prokop, C. Jacobs, G. Capretti, N. Sverzellati, F. Ciompi, B. van Ginneken, C. Schaefer-Prokop, C. Galeone, A. Marchiano and U. Pastorino, "Long-term Active Surveillance of Screening Detected Subsolid Nodules is a Safe Strategy to Reduce Overtreatment", Journal of Thoracic Oncology, 2018;13:1454-1463.
    Abstract DOI PMID Download Cited by ~55
19. Z. Bian, J. Charbonnier, J. Liu, D. Zhao, D. Lynch and B. van Ginneken, "Small airway segmentation in thoracic computed tomography scans: a machine learning approach", Physics in Medicine and Biology, 2018;63(15):155024.
    Abstract DOI PMID Download Cited by ~15
20. D. Tellez, M. Balkenhol, I. Otte-Holler, R. van de Loo, R. Vogels, P. Bult, C. Wauters, W. Vreuls, S. Mol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks", IEEE Transactions on Medical Imaging, 2018;37(9):2126 - 2136.
    Abstract DOI PMID Cited by ~200
21. A. Bria, C. Marrocco, L. Borges, M. Molinara, A. Marchesi, J. Mordang, N. Karssemeijer and F. Tortorella, "Improving the Automated Detection of Calcifications using Adaptive Variance Stabilization", IEEE Transactions on Medical Imaging, 2018;37(8):1857-1864.
    Abstract DOI PMID Cited by ~10
22. A. Schreuder, B. van Ginneken, E. Scholten, C. Jacobs, M. Prokop, N. Sverzellati, S. Desai, A. Devaraj and C. Schaefer-Prokop, "Classification of CT Pulmonary Opacities as Perifissural Nodules: Reader Variability", Radiology, 2018;288(3):867-875.
    Abstract DOI PMID Cited by ~36
23. J. van Zelst, S. Vreemann, H. Witt, A. Gubern-Merida, M. Dorrius, K. Duvivier, S. Lardenoije-Broker, M. Lobbes, C. Loo, W. Veldhuis, J. Veltman, D. Drieling, N. Karssemeijer and R. Mann, "Multireader Study on the Diagnostic Accuracy of Ultrafast Breast Magnetic Resonance Imaging for Breast Cancer Screening", Investigative Radiology, 2018;53(10):579-586.
    Abstract DOI PMID Cited by ~48
24. A. Baidoshvili, A. Bucur, J. van Leeuwen, J. van der Laak, P. Kluin and P. van Diest, "Evaluating the benefits of digital pathology implementation: time savings in laboratory logistics", Histopathology, 2018;73(5):784-794.
    Abstract DOI PMID Download Cited by ~76
25. B. Ehteshami Bejnordi, M. Mullooly, R. Pfeiffer, S. Fan, P. Vacek, D. Weaver, S. Herschorn, L. Brinton, B. van Ginneken, N. Karssemeijer, A. Beck, G. Gierach, J. van der Laak and M. Sherman, "Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies", Modern Pathology, 2018;31(10):1502-1512.
    Abstract DOI PMID Cited by ~150
26. A. Baidoshvili, N. Stathonikos, G. Freling, J. Bart, N. 't Hart, J. van der Laak, J. Doff, B. van der Vegt, M. Kluin Philip and P. van Dies, "Validation of a whole-slide image-based teleconsultation network", Histopathology, 2018;73:777-783.
    Abstract DOI PMID Cited by ~16
27. G. Litjens, P. Bándi, B. Ehteshami Bejnordi, O. Geessink, M. Balkenhol, P. Bult, A. Halilovic, M. Hermsen, R. van de Loo, R. Vogels, Q. Manson, N. Stathonikos, A. Baidoshvili, P. van Diest, C. Wauters, M. van Dijk and J. van der Laak, "1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset", GigaScience, 2018;7(6):1-8.
    Abstract DOI PMID Cited by ~290
28. K. Chung, O. Mets, P. Gerke, C. Jacobs, A. den Harder, E. Scholten, M. Prokop, P. de Jong, B. van Ginneken and C. Schaefer-Prokop, "Brock malignancy risk calculator for pulmonary nodules: validation outside a lung cancer screening population", Thorax, 2018;73(9):857-863.
    Abstract DOI PMID Cited by ~32
29. S. de Lange, M. Bakker, E. Monninkhof, P. Peeters, P. de Koekkoek-Doll, R. Mann, M. Rutten, R. Bisschops, J. Veltman, K. Duvivier, M. Lobbes, H. de Koning, N. Karssemeijer, R. Pijnappel, W. Veldhuis and C. van Gils, "Reasons for (non)participation in supplemental population-based MRI breast screening for women with extremely dense breasts", Clinical Radiology, 2018;73(8):759e1-759e9.
    Abstract DOI PMID Cited by ~21
30. E. van Leijsen, M. Bergkamp, I. van Uden, M. Ghafoorian, H. van der Holst, D. Norris, B. Platel, A. Tuladhar and F. de Leeuw, "Progression of White Matter Hyperintensities Preceded by Heterogeneous Decline of Microstructural Integrity", Stroke, 2018;49:1386-1393.
    Abstract DOI PMID Cited by ~67
31. J. Wanders, C. van Gils, N. Karssemeijer, K. Holland, M. Kallenberg, P. Peeters, M. Nielsen and M. Lillholm, "The combined effect of mammographic texture and density on breast cancer risk: a cohort study", Breast Cancer Research, 2018;20.
    Abstract DOI PMID Cited by ~28
32. B. Bejnordi, G. Litjens and J. van der Laak, "Machine Learning Compared With Pathologist Assessment-Reply", Journal of the American Medical Association, 2018;319(16):1726.
    Abstract DOI PMID Cited by ~5
33. F. Venhuizen, B. van Ginneken, B. Liefers, F. van Asten, V. Schreur, S. Fauser, C. Hoyng, T. Theelen and C. Sánchez, "A Deep Learning Approach for Detection and Quantification of Intraretinal Cystoid Fluid in Multivendor Optical Coherence Tomography", Biomedical Optics Express, 2018;9(4):1545-1569.
    Abstract DOI PMID Cited by ~117
34. J. Melendez, L. Hogeweg, C. Sánchez, R. Philipsen, R. Aldridge, A. Hayward, I. Abubakar, B. van Ginneken and A. Story, "Accuracy of an automated system for tuberculosis detection on chest radiographs in high-risk screening", International Journal of Tuberculosis and Lung Disease, 2018;22(5):567-571.
    Abstract DOI PMID Cited by ~22
35. O. Mets, K. Chung, P. Zanen, E. Scholten, W. Veldhuis, B. van Ginneken, M. Prokop, C. Schaefer-Prokop and P. de Jong, "In vivo growth of 60 non-screening detected lung cancers: a computed tomography study", European Respiratory Journal, 2018;51:1702183.
    Abstract DOI PMID Download Cited by ~11
36. J. van Zelst and R. Mann, "Automated Three-dimensional Breast US for Screening: Technique, Artifacts, and Lesion Characterization", Radiographics, 2018;38(3):663-683.
    Abstract DOI PMID
37. A. Schreuder, C. Schaefer-Prokop, E. Scholten, C. Jacobs, M. Prokop and B. van Ginneken, "Lung cancer risk to personalise annual and biennial follow-up computed tomography screening", Thorax, 2018;73(7):626-633.
    Abstract DOI PMID Download Cited by ~29
38. M. Oei, F. Meijer, J. Mordang, E. Smit, A. Idema, B. Goraj, H. Laue, M. Prokop and R. Manniesing, "Observer Variability of Reference Tissue Selection for Relative Cerebral Blood Volume Measurements in Glioma Patients", European Radiology, 2018;28(9):3902-3911.
    Abstract DOI PMID Cited by ~11
39. M. Silva, C. Schaefer-Prokop, C. Jacobs, G. Capretti, F. Ciompi, B. van Ginneken, U. Pastorino and N. Sverzellati, "Detection of Subsolid Nodules in Lung Cancer Screening: Complementary Sensitivity of Visual Reading and Computer-Aided Diagnosis", Investigative Radiology, 2018;53(8):441-449.
    Abstract DOI PMID Download Cited by ~30
40. M. Meijs, F. de Leeuw, H. Boogaarts, R. Manniesing and F. Meijer, "Circle of Willis collateral flow in carotid artery occlusion is depicted by 4D-CTA", World Neurosurgery, 2018;114:421-426.
    Abstract DOI PMID Cited by ~5
41. G. Humpire Mamani, A. Setio, B. van Ginneken and C. Jacobs, "Efficient organ localization using multi-label convolutional neural networks in thorax-abdomen CT scans", Physics in Medicine and Biology, 2018;63(8):085003.
    Abstract DOI PMID Cited by ~31
42. J. Larkin, M. Simard, A. Khrapitchev, J. Meakin, T. Okell, M. Craig, K. Ray, P. Jezzard, M. Chappell and N. Sibson, "Quantitative blood flow measurement in rat brain with multiphase arterial spin labelling magnetic resonance imaging", Journal of Cerebral Blood Flow & Metabolism, 2018;39:1557-1569.
    Abstract DOI PMID Cited by ~26
43. M. Verhagen, A. Smets, J. van Schuppen, E. Deurloo and C. Schaefer-Prokop, "The impact of reconstruction techniques on observer performance for the detection and characterization of small pulmonary nodules in chest CT of children under 13 years", European Journal of Radiology, 2018;100:142-146.
    Abstract DOI PMID Cited by ~8
44. K. Chung, F. Ciompi, J. Scholten E. Th. Goo, M. Prokop, C. Jacobs, B. van Ginneken and C. Schaefer-Prokop, "Visual Discrimination of Screen-detected Persistent from Transient Subsolid Nodules: an Observer Study", PLoS One, 2018;13(2):e0191874.
    Abstract DOI PMID Download Cited by ~8
45. J. van Zelst, T. Tan, P. Clauser, A. Domingo, M. Dorrius, D. Drieling, M. Golatta, F. Gras, M. de Jong, R. Pijnappel, M. Rutten, N. Karssemeijer and R. Mann, "Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts", European Radiology, 2018;28(7):2996-3006.
    Abstract DOI PMID Cited by ~52
46. N. Lessmann, B. van Ginneken, M. Zreik, P. de Jong, B. de Vos, M. Viergever and I. Išgum, "Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions", IEEE Transactions on Medical Imaging, 2018;37(2):615-625.
    Abstract DOI PMID arXiv Cited by ~171
47. S. Vreemann, A. Gubern-Merida, S. Lardenoije, P. Bult, N. Karssemeijer, K. Pinker and R. Mann, "The frequency of missed breast cancers in women participating in a high-risk MRI screening program", Breast Cancer Research and Treatment, 2018;169(2):323-331.
    Abstract DOI PMID Cited by ~25
48. S. Vreemann, A. Gubern-Mérida, C. Borelli, P. Bult, N. Karssemeijer and R. Mann, "The correlation of background parenchymal enhancement in the contralateral breast with patient and tumor characteristics of MRI-screen detected breast cancers", PLoS One, 2018;13(1):e0191399.
    Abstract DOI PMID Cited by ~17
49. M. Dalmis, S. Vreemann, T. Kooi, R. Mann, N. Karssemeijer and A. Gubern-Merida, "Fully automated detection of breast cancer in screening MRI using convolutional neural networks", Journal of Medical Imaging, 2018;5(1):014502.
    Abstract DOI PMID Cited by ~54
50. J. Charbonnier, K. Chung, E. Scholten, E. van Rikxoort, C. Jacobs, N. Sverzellati, M. Silva, U. Pastorino, B. van Ginneken and F. Ciompi, "Automatic segmentation of the solid core and enclosed vessels in subsolid pulmonary nodules", Scientific Reports, 2018;8(1):646.
    Abstract DOI PMID Download Cited by ~16
51. H. van der Holst, A. Tuladhar, V. Zerbi, I. van Uden, K. de Laat, E. van Leijsen, M. Ghafoorian, B. Platel, M. Bergkamp, A. van Norden and D. Norris, "White matter changes and gait decline in cerebral small vessel disease", NeuroImage: Clinical, 2018;17:731-738.
    Abstract DOI PMID Cited by ~69
52. A. Rodriguez-Ruiz, J. Teuwen, S. Vreemann, R. Bouwman, R. van Engen, N. Karssemeijer, R. Mann, A. Gubern-Merida and I. Sechopoulos, "New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers", Acta Radiologica, 2018;59(9):1051-1059.
    Abstract DOI PMID Cited by ~33
53. A. Rodriguez-Ruiz, A. Gubern-Merida, M. Imhof-Tas, S. Lardenoije, A. Wanders, I. Andersson, S. Zackrisson, K. Lang, M. Dustler, N. Karssemeijer, R. Mann and I. Sechopoulos, "One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection: do we need more?", European Radiology, 2018;28(5):1938-1948.
    Abstract DOI PMID Cited by ~27
54. C. Balta, R. Bouwman, I. Sechopoulos, M. Broeders, N. Karssemeijer, R. van Engen and W. Veldkamp, "A model observer study using acquired mammographic images of an anthropomorphic breast phantom", Medical Physics, 2018;45(2):655-665.
    Abstract DOI PMID Cited by ~15
55. J. Mordang, A. Gubern-Merida, A. Bria, F. Tortorella, R. Mann, M. Broeders, G. den Heeten and N. Karssemeijer, "The importance of early detection of calcifications associated with breast cancer in screening", Breast Cancer Research and Treatment, 2018;167(2):451-458.
    Abstract DOI PMID Cited by ~12
56. S. Vreemann, A. Gubern-Merida, M. Schlooz-Vries, P. Bult, C. van Gils, N. Hoogerbrugge, N. Karssemeijer and R. Mann, "Influence of Risk Category and Screening Round on the Performance of an MR Imaging and Mammography Screening Program in Carriers of the BRCA Mutation and Other Women at Increased Risk", Radiology, 2018;286(2):443-451.
    Abstract DOI PMID Cited by ~45
57. O. Mets, K. Chung, E. Scholten, W. Veldhuis, M. Prokop, B. van Ginneken, C. Schaefer-Prokop and P. de Jong, "Incidental perifissural nodules on routine chest computed tomography: lung cancer or not?", European Radiology, 2018:1095-1101.
    Abstract DOI PMID Cited by ~28
58. W. Venderink, M. de Rooij, M. Sedelaar, H. Huisman and J. Futterer, "Elastic versus rigid image registration in MRI-TRUS fusion prostate biopsy: a systematic review and meta-analysis", European Urology Focus, 2018;4:219-227.
    Abstract DOI PMID Cited by ~54
59. J. Sprem, B. de Vos, N. Lessmann, P. de Jong, M. Viergever and I. Isgum, "Impact of automatically detected motion artifacts on coronary calcium scoring in chest computed tomography", Journal of Medical Imaging, 2018;5:044007.
    Abstract DOI
60. J. Sprem, B. de Vos, N. Lessmann, R. van Hamersvelt, M. Greuter, P. de Jong, T. Leiner, M. Viergever and I. Isgum, "Coronary calcium scoring with partial volume correction in anthropomorphic thorax phantom and screening chest CT images", PLoS One, 2018;13:e0209318.
    Abstract DOI
61. M. Zreik, N. Lessmann, R. van Hamersvelt, J. Wolterink, M. Voskuil, M. Viergever, T. Leiner and I. Išgum, "Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis", Medical Image Analysis, 2018;44:72-85.
    Abstract DOI
62. S. Gernaat, S. van Velzen, V. Koh, M. Emaus, I. Išgum, N. Lessmann, S. Moes, A. Jacobson, P. Tan, D. Grobbee, D. van den Bongard, J. Tang and H. Verkooijen, "Automatic quantification of calcifications in the coronary arteries and thoracic aorta on radiotherapy planning CT scans of Western and Asian breast cancer patients", Radiotherapy and Oncology, 2018;127:487-492.
    Abstract DOI

Preprints

1. S. Kazeminia, C. Baur, A. Kuijper, B. van Ginneken, N. Navab, S. Albarqouni and A. Mukhopadhyay, "GANs for Medical Image Analysis", arXiv:1809.06222, 2018.
   Abstract arXiv Cited by ~55
2. Z. Li, Z. Hu, J. Xu, T. Tan, H. Chen, Z. Duan, P. Liu, J. Tang, G. Cai, Q. Ouyang, Y. Tang, G. Litjens and Q. Li, "Computer-aided diagnosis of lung carcinoma using deep learning - a pilot study", arXiv:1803.05471, 2018.
   Abstract DOI arXiv Cited by ~30
3. T. de Moor, A. Rodriguez-Ruiz, R. Mann and J. Teuwen, "Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network", arXiv:1802.06865, 2018.
   Abstract arXiv
4. E. Sogancioglu, S. Hu, D. Belli and B. van Ginneken, "Chest X-ray Inpainting with Deep Generative Models", arXiv:1809.01471, 2018.
   Abstract arXiv Cited by ~15
5. J. Teuwen and P. Urbach, "On Maximum Focused Electric Energy in Bounded Regions", arXiv:1801.02450, 2018.
   Abstract arXiv
6. D. Belli, S. Hu, E. Sogancioglu and B. van Ginneken, "Chest X-Rays Image Inpainting with Context Encoders", arXiv:1812.00964, 2018.
   Abstract arXiv
7. D. Belli, S. Hu, E. Sogancioglu and B. van Ginneken, "Context Encoding Chest X-rays", arXiv:1812.00964, 2018.
   Abstract DOI arXiv Cited by ~3
8. A. de Gelder and H. Huisman, "Autoencoders for Multi-Label Prostate MR Segmentation", arXiv:1806.08216, 2018.
   Abstract arXiv Cited by ~6
9. G. Aresta, C. Jacobs, T. Araújo, A. Cunha, I. Ramos, B. van Ginneken and A. Campilho, "iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network", arXiv:1811.12789, 2018.
   Abstract arXiv Cited by ~66
10. G. Mooij, I. Bagulho and H. Huisman, "Automatic segmentation of prostate zones", arXiv:1806.07146, 2018.
    Abstract arXiv Cited by ~15

Papers in conference proceedings

1. W. Bulten, C. de Kaa, J. van der Laak and G. Litjens, "Automated segmentation of epithelial tissue in prostatectomy slides using deep learning", Medical Imaging, 2018;10581:105810S.
   Abstract DOI Cited by ~18
2. T. de Bel, M. Hermsen, J. van der Laak, G. Litjens, B. Smeets and L. Hilbrands, "Automatic segmentation of histopathological slides of renal tissue using deep learning", Medical Imaging 2018: Digital Pathology, 2018.
   Abstract DOI Cited by ~48
3. S. van de Leemput, J. Teuwen and R. Manniesing, "MemCNN: a Framework for Developing Memory Efficient Deep Invertible Networks", International Conference on Learning Representations, 2018.
   Abstract Url Cited by ~11
4. M. van Rijthoven, Z. Swiderska-Chadaj, K. Seeliger, J. van der Laak and F. Ciompi, "You Only Look on Lymphocytes Once", Medical Imaging with Deep Learning, 2018.
   Abstract Url Cited by ~21
5. D. Geijs, M. Intezar, J. van der Laak and G. Litjens, "Automatic color unmixing of IHC stained whole slide images", Medical Imaging, 2018;10581.
   Abstract DOI Cited by ~11
6. E. Gibson, Yipeng, H. Ghavami, H. Ahmed, C. Moore, M. Emberton, H. Huisman and D. Barratt, "Inter-site variability in prostate segmentation accuracy using deep learning", Medical Image Computing and Computer-Assisted Intervention, 2018.
   Abstract DOI Cited by ~48
7. S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Stacked Bidirectional Convolutional LSTMs for 3D Non-contrast CT Reconstruction from Spatiotemporal 4D CT", Medical Imaging with Deep Learning, 2018.
   Abstract Url Cited by ~2
8. A. Patel and R. Manniesing, "A convolutional neural network for intracranial hemorrhage detection in non-contrast CT", Medical Imaging, 2018;10575.
   Abstract DOI Cited by ~4
9. N. Lessmann, B. van Ginneken, P. de Jong and I. Išgum, "Iterative fully convolutional neural networks for automatic vertebra segmentation", Medical Imaging with Deep Learning, 2018.
   Abstract Url Cited by ~190
10. M. Ghafoorian, J. Teuwen, R. Manniesing, F. de Leeuw, B. van Ginneken, N. Karssemeijer and B. Platel, "Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR", Medical Imaging, 2018;10574:105742U.
    Abstract DOI arXiv Cited by ~18
11. J. Bokhorst, L. Rijstenberg, D. Goudkade, I. Nagtegaal, J. van der Laak and F. Ciompi, "Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep Learning", Computational Pathology and Ophthalmic Medical Image Analysis, 2018.
    Abstract DOI Cited by ~11
12. W. Bulten and G. Litjens, "Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders", Medical Imaging with Deep Learning, 2018.
    Abstract Url Cited by ~24
13. M. Meijs and R. Manniesing, "Artery and Vein Segmentation of the Cerebral Vasculature in 4D CT using a 3D Fully Convolutional Neural Network", Medical Imaging, 2018;10575:105751Q.
    Abstract DOI Cited by ~13
14. D. Tellez, J. van der Laak and F. Ciompi, "Gigapixel Whole-Slide Image Classification Using Unsupervised Image Compression And Contrastive Training", Medical Imaging with Deep Learning, 2018.
    Abstract Url Cited by ~10
15. A. Rodriguez-Ruiz, R. van Engen, K. Michielsen, R. Bouwman, S. Vreemann, N. Karssemeijer, R. Mann and I. Sechopoulos, "How does wide-angle breast tomosynthesis depict calcifications in comparison to digital mammography? A retrospective observer study", 14th International Workshop on Breast Imaging (IWBI 2018), 2018.
    Abstract DOI Cited by ~2
16. T. de Moor, A. Rodriguez-Ruiz, R. Mann, A. Gubern Mérida and J. Teuwen, "Automated lesion detection and segmentation in digital mammography using a u-net deep learning network", 14th International Workshop on Breast Imaging (IWBI 2018), 2018.
    Abstract DOI
17. G. Aresta, T. Araújo, C. Jacobs, B. van Ginneken, A. Cunha, I. Ramos and A. Campilho, "Towards an automatic lung cancer screening system in low dose computed tomography", MICCAI Workshop: Thoracic Image Analysis, 2018;11040.
    Abstract DOI Cited by ~15
18. S. van de Leemput, A. Patel and R. Manniesing, "Full Volumetric Brain Tissue Segmentation in Non-contrast CT using Memory Efficient Convolutional LSTMs", Medical Imaging meets NeurIPS, 2018.
    Abstract Url Cited by ~1
19. A. Rodriguez-Ruiz, J. Mordang, N. Karssemeijer, I. Sechopoulos and R. Mann, "Can radiologists improve their breast cancer detection in mammography when using a deep learning based computer system as decision support?", 14th International Workshop on Breast Imaging (IWBI 2018), 2018.
    Abstract DOI Cited by ~13
20. A. Bria, B. Savelli, C. Marrocco, J. Mordang, M. Molinara, N. Karssemeijer and F. Tortorella, "Improving the automated detection of calcifications by combining deep cascades and deep convolutional nets", 14th International Workshop on Breast Imaging (IWBI 2018), 2018.
    Abstract DOI Cited by ~6
21. Y. Hagos, A. Gubern-Mérida and J. Teuwen, "Improving Breast Cancer Detection using Symmetry Information with Deep Learning", Breast Image Analysis (BIA), 2018.
    Abstract DOI Cited by ~25
22. K. Standvoss, T. Crijns, L. Goerke, D. Janssen, S. Kern, T. van Niedek, J. van Vugt, N. Burgos, E. Gerritse, J. Mol, D. van de Vooren, M. Ghafoorian, T. van den Heuvel and R. Manniesing, "Cerebral Microbleed Detection in Traumatic Brain Injury Patients using 3D Convolutational Neural Networks", Medical Imaging, 2018;10575.
    Abstract DOI Cited by ~14
23. C. González-Gonzalo, B. Liefers, B. van Ginneken and C. Sánchez, "Improving weakly-supervised lesion localization with iterative saliency map refinement", Medical Imaging with Deep Learning, 2018.
    Abstract Url Cited by ~4
24. N. Lessmann, B. van Ginneken and I. Išgum, "Iterative convolutional neural networks for automatic vertebra identification and segmentation in CT images", Medical Imaging, 2018;10574.
    Abstract DOI Cited by ~32
25. D. Tellez, M. Balkenhol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection", Medical Imaging, 2018;10581.
    Abstract DOI Cited by ~43
26. C. Marrocco, A. Bria, V. Di Sano, L. Borges, B. Savelli, M. Molinara, J. Mordang, N. Karssemeijer and F. Tortorella, "Mammogram denoising to improve the calcification detection performance of convolutional nets", 14th International Workshop on Breast Imaging (IWBI 2018), 2018.
    Abstract DOI Cited by ~6
27. Z. Swiderska-Chadaj, H. Pinckaers, M. van Rijthoven, M. Balkenhol, M. Melnikova, O. Geessink, Q. Manson, G. Litjens, J. van der Laak and F. Ciompi, "Convolutional Neural Networks for Lymphocyte detection in Immunohistochemically Stained Whole-Slide Images", Medical Imaging with Deep Learning, 2018.
    Abstract Url Cited by ~12
28. F. Zanjani, S. Zinger, B. Bejnordi, J. van der Laak and P. de With, "Stain normalization of histopathology images using generative adversarial networks", 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 2018.
    Abstract DOI Cited by ~105
29. A. Rodriguez-Ruiz, J. Teuwen, K. Chung, N. Karssemeijer, M. Chevalier, A. Gubern-Merida and I. Sechopoulos, "Pectoral muscle segmentation in breast tomosynthesis with deep learning", Medical Imaging, 2018.
    Abstract DOI Cited by ~21

Abstracts

1. B. van Ginneken, "Deep Machine Learning for Screening LDCT", Journal of Thoracic Oncology, 2018;13:S190.
   Abstract
2. M. Hermsen, T. de Bel, M. den Boer, E. Steenbergen, J. Kers, S. Florquin, B. Smeets, L. Hilbrands and J. van der Laak, "Glomerular detection, segmentation and counting in PAS-stained histopathological slides using deep learning", Dutch Federation of Nephrology (NfN) Fall Symposium, 2018.
   Abstract
3. A. Schreuder, B. van Ginneken, E. Scholten, C. Jacobs, M. Prokop, N. Sverzellati, S. Desai, A. Devaraj and C. Schaefer-Prokop, "What is a perifissural nodule? Low inter-observer agreement in NLST data", European Societies of Cardiovascular Radiology and Thoracic Imaging joint meeting, 2018.
   Abstract
4. E. Smeets, J. Teuwen, J. van der Laak, M. Gotthardt, F. Ciompi and E. Aarntzen, "Tumor heterogeneity as a PET-biomarker predicts overall survival of pancreatic cancer patients", European Society for Molecular Imaging, 2018.
   Abstract
5. H. Pinckaers and G. Litjens, "Training convolutional neural networks with megapixel images", Medical Imaging with Deep Learning, 2018.
   Abstract arXiv Cited by ~12
6. A. van der Eerden, T. van den Heuvel, B. Geurts, B. Platel, T. Vyveree, L. van den Hauwee, T. Andriessen, B. Goraj and R. Manniesing, "Automatic versus human detection of traumatic cerebral microbleeds on susceptibility weighted imaging", European Congress of Radiology, 2018.
   Abstract
7. F. Zanjani, S. Zinger, B. Bejnordi, J. van der Laak and P. de With, "Histopathology stain-color normalization using deep generative models", Medical Imaging with Deep Learning, 2018.
   Abstract Cited by ~41
8. A. Schreuder, C. Jacobs, N. Lessmann, E. Scholten, I. Isgum, M. Prokop, C. Schaefer-Prokop and B. van Ginneken, "Improved Lung Cancer and Mortality Prediction Accuracy Using Survival Models Based on Semi-Automatic CT Image Measurements", World Conference on Lung Cancer, 2018.
   Abstract
9. F. Meijer, P. Willems, M. Meijs and R. Manniesing, "Color-mapping visualization of 4D-CTA in neurovascular disease", European Society of Neuroradiology, 2018.
   Abstract
10. M. Meijs, A. Patel, S. van de Leemput, B. van Ginneken, M. Prokop and R. Manniesing, "Fast, Robust and Accurate Segmentation of the Complete Cerebral Vasculature in 4D-CTA using Deep Learning", Annual Meeting of the Radiological Society of North America, 2018.
    Abstract
11. A. Schreuder, C. Schaefer-Prokop, E. Scholten, D. Lynch, J. Charbonnier and C. Jacobs, "Perifissural nodule count as a biomarker for COPD GOLD stages and emphysema measurements?", European Societies of Cardiovascular Radiology and Thoracic Imaging Joint Meeting, 2018.
    Abstract
12. M. Hall, A. Setio, S. Sheridan, M. Sproule, M. Williams, E. Scholten, C. Jacobs, B. Van Ginneken and G. Roditi, "Computer aided detection (CAD) and scoring of lung nodules in a Scottish lung cancer screening programme", European Congress of Radiology, 2018.
    Abstract DOI
13. A. Schreuder, C. Jacobs, L. Gallardo-Estrella, C. and Schaefer-Prokop, W. Fukumoto, M. Prokop and B. van Ginneken, "Normalized emphysema score progression: An improved CT biomarker for mortality", Annual Meeting of the Radiological Society of North America, 2018.
    Abstract
14. B. van Ginneken, "Real-Life Artificial Intelligence Applications", Journal of the Belgian Society of Nephrology, 2018.
    Abstract DOI Cited by ~1
15. K. Koschmieder, A. van der Eerden, B. van Ginneken and R. Manniesing, "Brain Extraction in Susceptibility-Weighted MR Images using Deep Learning", Annual Meeting of the Radiological Society of North America, 2018.
    Abstract

PhD theses

1. A. Setio, "Computer-aided diagnosis in thoracic CT scans for lung cancer screening", PhD thesis, 2018.
   Abstract Url
2. K. Chung, "Malignancy risk estimation of subsolid nodules", PhD thesis, 2018.
   Abstract Url
3. J. Mordang, "Towards an independent observer of screening mammograms: detection of calcifications", PhD thesis, 2018.
   Abstract Url
4. S. Vreemann, "Breast MRI for screening: evaluation of clinical practice and future perspectives", PhD thesis, 2018.
   Abstract Url
5. T. Kooi, "Computer aided diagnosis of breast cancer in mammography using deep neural networks", PhD thesis, 2018.
   Abstract Url
6. M. Ghafoorian, "Machine Learning for Quantification of Small Vessel Disease Imaging Biomarkers", PhD thesis, 2018.
   Abstract Url

Master theses

1. T. Ableef, "Malignancy estimation of Pulmonary Nodules using Multi-View Multi-Time Point Convolutional Neural Networks", Master thesis, 2018.
   Abstract
2. I. Bagulho, "Reference Tissue Normalization of Prostate MRI with automatic Multi-Organ Deep Learning Pelvis segmentation", Master thesis, 2018.
   Abstract
3. J. van Kleef, "Robust and accurate cerebral hemisphere segmentation in non-contrast CT using a 2.5D Dense U-Net", Master thesis, 2018.
   Abstract
4. C. Kamphuis, "Automatic Segmentation of Retinal Layers in Optical Coherence Tomography using Deep Learning Techniques", Master thesis, 2018.
   Abstract
5. M. den Boer, "Automated structure segmentation and lymphocyte detection in kidney transplant whole slide images using a convolutional neural network", Master thesis, 2018.
   Abstract

Other publications

1. T. de Bel, M. Hermsen, G. Litjens and J. van der Laak, "Structure Instance Segmentation in Renal Tissue: A Case Study on Tubular Immune Cell Detection", Computational Pathology and Ophthalmic Medical Image Analysis, 2018:112-119.
   Abstract DOI Cited by ~8
2. D. Stoyanov, Z. Taylor, B. Kainz, G. Maicas, R. Beichel, A. Martel, L. Maier-Hein, B. Kanwal, T. Vercauteren, O. Ozan, G. Carneiro, A. Bradley, J. Nascimento, H. Min, M. Brown, C. Jacobs, B. Lassen-Schmidt, K. Mori, J. Petersen, R. Estepar, A. Schmidt-Richberg and C. Veiga, "Image Analysis for Moving Organ, Breast and Thoracic Images", 2018;11040.
   Abstract DOI