Publications

2018

Papers in international journals

  1. 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;22:567-571. Abstract/PDF DOI PMID Cited by ~10
  2. 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;63:085003. Abstract/PDF DOI PMID Cited by ~11
  3. 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/PDF DOI PMID Cited by ~12
  4. 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/PDF DOI PMID Cited by ~5
  5. 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;53:579-586. Abstract/PDF DOI PMID Cited by ~22
  6. 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/PDF DOI PMID Cited by ~25
  7. 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;37:2126 - 2136. Abstract/PDF DOI PMID Cited by ~45
  8. 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;73:759e1-759e9. Abstract/PDF DOI PMID Cited by ~7
  9. 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;53:441-449. Abstract/PDF DOI PMID Cited by ~13
  10. 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. Abstract/PDF DOI PMID Cited by ~26
  11. 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/PDF DOI PMID
  12. 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;37:1857-1864. Abstract/PDF DOI PMID Cited by ~3
  13. 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/PDF DOI PMID Cited by ~14
  14. 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/PDF DOI PMID Cited by ~9
  15. 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/PDF DOI PMID
  16. 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/PDF DOI PMID Cited by ~12
  17. 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;73:857-863. Abstract/PDF DOI PMID Cited by ~18
  18. 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;37:615-625. Abstract/PDF DOI PMID arXiv Cited by ~72
  19. 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/PDF DOI PMID Cited by ~23
  20. 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/PDF DOI PMID Cited by ~5
  21. 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/PDF DOI PMID Cited by ~14
  22. 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/PDF DOI PMID Cited by ~1
  23. 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/PDF DOI PMID Cited by ~11
  24. 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/PDF DOI PMID Cited by ~16
  25. 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/PDF DOI PMID Cited by ~20
  26. 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/PDF DOI PMID Cited by ~21
  27. 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;288:867-875. Abstract/PDF DOI PMID Cited by ~14
  28. 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/PDF DOI PMID Cited by ~4
  29. 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/PDF DOI PMID Cited by ~5
  30. 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/PDF DOI PMID Cited by ~3
  31. 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/PDF DOI PMID Cited by ~15
  32. 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;46:484-493. Abstract/PDF DOI PMID Cited by ~1
  33. 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/PDF DOI PMID Cited by ~5
  34. 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;5:044501. Abstract/PDF DOI PMID
  35. 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;9:1545-1569. Abstract/PDF DOI PMID
  36. 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/PDF DOI PMID Cited by ~15
  37. 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/PDF DOI PMID Cited by ~54
  38. 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", Nature Scientific Reports, 2018;8(1):15497. Abstract/PDF DOI PMID Cited by ~46
  39. 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;73:626-633. Abstract/PDF DOI PMID Cited by ~13
  40. 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", Nature Scientific Reports, 2018;8(1):646. Abstract/PDF DOI PMID Cited by ~9
  41. 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/PDF DOI PMID Cited by ~56
  42. 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;44:2250-2260. Abstract/PDF DOI PMID Cited by ~2
  43. 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/PDF DOI PMID Cited by ~6
  44. 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", Nature Scientific Reports, 2018;8(1):12339. Abstract/PDF DOI PMID Cited by ~15
  45. G. Litjens, P. Bandi, 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;7:1-8. Abstract/PDF DOI PMID Cited by ~48
  46. 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;31:1502-1512. Abstract/PDF DOI PMID Cited by ~52

Preprints

  1. 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
  2. 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", arXiv:1812.01859, 2018. Abstract/PDF arXiv
  3. G. Mooij, I. Bagulho and H. Huisman, "Automatic segmentation of prostate zones", arXiv:1806.07146, 2018. Abstract arXiv Cited by ~10
  4. 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
  5. 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 ~4
  6. 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
  7. A. de Gelder and H. Huisman, "Autoencoders for Multi-Label Prostate MR Segmentation", arXiv:1806.08216, 2018. Abstract arXiv Cited by ~3
  8. J. Teuwen and P. Urbach, "On Maximum Focused Electric Energy in Bounded Regions", arXiv:1801.02450, 2018. Abstract arXiv
  9. D. Belli, S. Hu, E. Sogancioglu and B. van Ginneken, "Chest X-Rays Image Inpainting with Context Encoders", arXiv:1812.00964, 2018. Abstract arXiv

Papers in conference proceedings

  1. 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 ~10
  2. 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/PDF Cited by ~3
  3. 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/PDF Cited by ~1
  4. 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/PDF DOI Cited by ~3
  5. 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/PDF Cited by ~1
  6. 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/PDF DOI Cited by ~2
  7. 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", International Workshop on Breast Imaging, 2018. Abstract/PDF arXiv
  8. 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/PDF Cited by ~5
  9. 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/PDF DOI Cited by ~21
  10. 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/PDF DOI
  11. 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/PDF DOI arXiv Cited by ~14
  12. A. Patel and R. Manniesing, "A convolutional neural network for intracranial hemorrhage detection in non-contrast CT", Medical Imaging, 2018;10575. Abstract/PDF DOI Cited by ~3
  13. Y. Hagos, A. Gubern-Mérida and J. Teuwen, "Improving Breast Cancer Detection using Symmetry Information with Deep Learning", Breast Image Analysis (BIA), 2018. Abstract/PDF DOI
  14. 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/PDF DOI
  15. 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/PDF Cited by ~2
  16. 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/PDF Cited by ~1
  17. W. Bulten and G. Litjens, "Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders", Medical Imaging with Deep Learning, 2018. Abstract/PDF Cited by ~8
  18. 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/PDF Cited by ~5
  19. 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/PDF DOI Cited by ~7
  20. 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/PDF DOI Cited by ~10
  21. 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/PDF DOI Cited by ~15
  22. 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/PDF
  23. 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/PDF DOI Cited by ~12

Abstracts

  1. 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/PDF
  2. 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
  3. B. van Ginneken, "Deep Machine Learning for Screening LDCT", Journal of Thoracic Oncology, 2018;13:S190. Abstract/PDF
  4. 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/PDF
  5. 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
  6. 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
  7. 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/PDF
  8. 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
  9. 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
  10. 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
  11. F. Meijer, P. Willems, M. Meijs and R. Manniesing, "Color-mapping visualization of 4D-CTA in neurovascular disease", European Society of Neuroradiology, 2018. Abstract/PDF
  12. B. van Ginneken, "Real-Life Artificial Intelligence Applications", Journal of the Belgian Society of Nephrology, 2018. Abstract/PDF DOI Cited by ~1
  13. 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

PhD theses

  1. M. Ghafoorian, "Machine Learning for Quantification of Small Vessel Disease Imaging Biomarkers", 2018. Abstract/PDF
  2. K. Chung, "Malignancy risk estimation of subsolid nodules", 2018. Abstract/PDF
  3. T. Kooi, "Computer aided diagnosis of breast cancer in mammography using deep neural networks", 2018. Abstract/PDF
  4. J. Mordang, "Towards an independent observer of screening mammograms: detection of calcifications", 2018. Abstract/PDF
  5. A. Setio, "Computer-aided diagnosis in thoracic CT scans for lung cancer screening", 2018. Abstract/PDF

Other publications

  1. 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/PDF DOI