Publications

2021

Papers in international journals

  1. C. González-Gonzalo, E. Thee, C. Klaver, A. Lee, R. Schlingemann, A. Tufail, F. Verbraak and C. Sánchez, "Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice", Progress in Retinal and Eye Research, 2021.
    Abstract DOI PMID
  2. L. van Eekelen, H. Pinckaers, M. van den Brand, K. Hebeda and G. Litjens, "Using deep learning for quantification of cellularity and cell lineages in bone marrow biopsies and comparison to normal age-related variation.", 2021.
    Abstract DOI PMID
  3. A. Schreuder, C. Jacobs, N. Lessmann, M. Broeders, M. Silva, I. Išgum, P. de Jong, M. van den Heuvel, N. Sverzellati, M. Prokop, U. Pastorino, C. Schaefer-Prokop and B. van Ginneken, "Scan-based competing death risk model for reevaluating lung cancer computed tomography screening eligibility", European Respiratory Journal, 2021.
    Abstract DOI PMID
  4. C. Jacobs, A. Schreuder, S. van Riel, E. Scholten, R. Wittenberg, M. Winkler Wille, B. de Hoop, R. Sprengers, O. Mets, B. Geurts, M. Prokop, C. Schaefer-Prokop and B. van Ginneken, "Assisted versus Manual Interpretation of Low-Dose CT Scans for Lung Cancer Screening: Impact on Lung-RADS Agreement", Radiology: Imaging Cancer, 2021;3(5):e200160.
    Abstract DOI PMID
  5. M. Dekker, F. Waissi, M. Silvis, J. Bennekom, A. Schoneveld, R. de Winter, I. Isgum, N. Lessmann, B. Velthuis, G. Pasterkamp, A. Mosterd, L. Timmers and D. de Kleijn, "High Levels of Osteoprotegerin Are Associated with Coronary Artery Calcification in Patients Suspected of a Chronic Coronary Syndrome", Nature Scientific Reports, 2021;11(1):18946.
    Abstract DOI PMID Algorithm
  6. K. Kartasalo, W. Bulten, B. Delahunt, P. Chen, H. Pinckaers, H. Olsson, X. Ji, N. Mulliqi, H. Samaratunga, T. Tsuzuki, J. Lindberg, M. Rantalainen, C. Wählby, G. Litjens, P. Ruusuvuori, L. Egevad and M. Eklund, "Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps.", 2021;7(4):687-691.
    Abstract DOI PMID
  7. G. Bortsova, C. González-Gonzalo, S. Wetstein, F. Dubost, I. Katramados, L. Hogeweg, B. Liefers, B. van Ginneken, J. Pluim, M. Veta, C. Sánchez and M. de Bruijne, "Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors", Medical Image Analysis, 2021:102141.
    Abstract DOI PMID arXiv
  8. A. Schreuder, M. Prokop, E. Scholten, O. Mets, K. Chung, F. Mohamed Hoesein, C. Jacobs and C. Schaefer-Prokop, "CT-Detected Subsolid Nodules: A Predictor of Lung Cancer Development at Another Location?", Cancers, 2021;13(11):2812.
    Abstract DOI PMID
  9. E. Çallı, E. Sogancioglu, B. van Ginneken, K. van Leeuwen and K. Murphy, "Deep learning for chest X-ray analysis: A survey", Medical Image Analysis, 2021;72:102125.
    Abstract DOI PMID
  10. A. Schreuder, E. Scholten, B. van Ginneken and C. Jacobs, "Artificial intelligence for detection and characterization of pulmonary nodules in lung cancer CT screening: ready for practice?", Translational Lung Cancer Research, 2021;10(5):2378-2388.
    Abstract DOI PMID
  11. M. Hermsen, V. Volk, J. Bräsen, D. Geijs, W. Gwinner, J. Kers, J. Linmans, N. Schaadt, J. Schmitz, E. Steenbergen, Z. Swiderska-Chadaj, B. Smeets, L. Hilbrands and J. van der Laak, "Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning", Laboratory Investigation, 2021;101(8):970-982.
    Abstract DOI PMID
  12. K. Venkadesh, A. Setio, A. Schreuder, E. Scholten, K. Chung, M. W Wille, Z. Saghir, B. van Ginneken, M. Prokop and C. Jacobs, "Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT.", Radiology, 2021;300(2):438-447.
    Abstract DOI PMID Algorithm
  13. T. Penzkofer, A. Padhani, B. Turkbey, M. Haider, H. Huisman, J. Walz, G. Salomon, I. Schoots, J. Richenberg, G. Villeirs, V. Panebianco, O. Rouviere, V. Logager and J. Barentsz, "ESUR/ESUI position paper: developing artificial intelligence for precision diagnosis of prostate cancer using magnetic resonance imaging.", European Radiology, 2021.
    Abstract DOI PMID
  14. J. van der Laak, G. Litjens and F. Ciompi, "Deep learning in histopathology: the path to the clinic.", Nature Medicine, 2021;27(5):775-784.
    Abstract DOI PMID
  15. B. de Vos, N. Lessmann, P. de Jong and I. Išgum, "Deep Learning–Quantified Calcium Scores for Automatic Cardiovascular Mortality Prediction at Lung Screening Low-Dose CT", Radiology: Cardiothoracic Imaging, 2021;3(2):e190219.
    Abstract DOI PMID
  16. R. Gal, S. van Velzen, M. Hooning, M. Emaus, F. van der Leij, M. Gregorowitsch, E. Blezer, S. Gernaat, N. Lessmann, M. Sattler, T. Leiner, P. de Jong, A. Teske, J. Verloop, J. Penninkhof, I. Vaartjes, H. Meijer, J. van Tol-Geerdink, J. Pignol, D. van den Bongard, I. Išgum and H. Verkooijen, "Identification of Risk of Cardiovascular Disease by Automatic Quantification of Coronary Artery Calcifications on Radiotherapy Planning CT Scans in Patients With Breast Cancer", JAMA Oncology, 2021;7(7):1024-1032.
    Abstract DOI PMID Algorithm
  17. A. Schreuder, O. Mets, C. Schaefer-Prokop, C. Jacobs and M. Prokop, "Microsimulation modeling of extended annual CT screening among lung cancer cases in the National Lung Screening Trial", Lung Cancer, 2021;156:5-11.
    Abstract DOI PMID
  18. K. van Leeuwen, S. Schalekamp, M. Rutten, B. van Ginneken and M. de Rooij, "Artificial intelligence in radiology: 100 commercially available products and their scientific evidence", European Radiology, 2021;31:3797–3804.
    Abstract DOI PMID
  19. F. Faita, T. Oranges, N. Di Lascio, F. Ciompi, S. Vitali, G. Aringhieri, A. Janowska, M. Romanelli and V. Dini, "Ultra-high-frequency ultrasound and machine learning approaches for the differential diagnosis of melanocytic lesions.", Experimental Dermatology, 2021.
    Abstract DOI PMID
  20. H. Pinckaers, W. Bulten, J. der Van Laak and G. Litjens, "Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels.", IEEE Transactions on Medical Imaging, 2021.
    Abstract DOI PMID
  21. M. Velema, L. Canu, T. Dekkers, A. Hermus, H. Timmers, L. Schultze Kool, H. Groenewoud, C. Jacobs, J. Deinum and S. Investigators, "Volumetric evaluation of CT images of adrenal glands in primary aldosteronism.", Journal of endocrinological investigation, 2021;44(11):2359-2366.
    Abstract DOI PMID
  22. T. de Bel, J. Bokhorst, J. van der Laak and G. Litjens, "Residual cyclegan for robust domain transformation of histopathological tissue slides.", Medical Image Analysis, 2021;70:102004.
    Abstract DOI PMID
  23. M. Balkenhol, F. Ciompi, Ż. Świderska-Chadaj, R. van de Loo, M. Intezar, I. Otte-Höller, D. Geijs, J. Lotz, N. Weiss, T. de Bel, G. Litjens, P. Bult and J. van der Laak, "Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics.", BREAST, 2021;56:78-87.
    Abstract DOI PMID
  24. O. Turner, B. Knight, A. Zuraw, G. Litjens and D. Rudmann, "Mini Review: The Last Mile-Opportunities and Challenges for Machine Learning in Digital Toxicologic Pathology.", TP, 2021;49(4):714-719.
    Abstract DOI PMID
  25. A. Schreuder, C. Jacobs, N. Lessmann, M. Broeders, M. Silva, I. Išgum, P. de Jong, N. Sverzellati, M. Prokop, U. Pastorino, C. Schaefer-Prokop and B. van Ginneken, "Combining pulmonary and cardiac computed tomography biomarkers for disease-specific risk modelling in lung cancer screening", European Respiratory Journal, 2021;58(3):2003386.
    Abstract DOI PMID
  26. B. Liefers, P. Taylor, A. Alsaedi, C. Bailey, K. Balaskas, N. Dhingra, C. Egan, F. Rodrigues, C. González-Gonzalo, T. Heeren, A. Lotery, P. Muller, A. Olvera-Barrios, B. Paul, R. Schwartz, D. Thomas, A. Warwick, A. Tufail and C. Sánchez, "Quantification of key retinal features in early and late age-related macular degeneration using deep learning", American Journal of Ophthalmology, 2021;226:1-12.
    Abstract DOI PMID
  27. D. Grob, L. Oostveen, C. Jacobs, E. Scholten, M. Prokop, C. Schaefer-Prokop, I. Sechopoulos and M. Brink, "Pulmonary nodule enhancement in subtraction CT and dual-energy CT: A comparison study", European Journal of Radiology, 2021;134:109443.
    Abstract DOI PMID
  28. M. van Rijthoven, M. Balkenhol, K. Silina, J. van der Laak and F. Ciompi, "HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images", Medical Image Analysis, 2021;68:101890.
    Abstract DOI PMID GitHub Algorithm
  29. J. Bartstra, F. Draaisma, S. Zwakenberg, N. Lessmann, J. Wolterink, Y. van der Schouw, P. de Jong and J. Beulens, "Six months vitamin K treatment does not affect systemic arterial calcification or bone mineral density in diabetes mellitus 2", European Journal of Nutrition, 2021;60:1691-1699.
    Abstract DOI PMID
  30. N. Lessmann, C. Sánchez, L. Beenen, L. Boulogne, M. Brink, E. Calli, J. Charbonnier, T. Dofferhoff, W. van Everdingen, P. Gerke, B. Geurts, H. Gietema, M. Groeneveld, L. van Harten, N. Hendrix, W. Hendrix, H. Huisman, I. Isgum, C. Jacobs, R. Kluge, M. Kok, J. Krdzalic, B. Lassen-Schmidt, K. van Leeuwen, J. Meakin, M. Overkamp, T. van Rees Vellinga, E. van Rikxoort, R. Samperna, C. Schaefer-Prokop, S. Schalekamp, E. Scholten, C. Sital, L. Stöger, J. Teuwen, K. Vaidhya Venkadesh, C. de Vente, M. Vermaat, W. Xie, B. de Wilde, M. Prokop and B. van Ginneken, "Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence", Radiology, 2021;298(1):E18-E28.
    Abstract DOI PMID Algorithm
  31. D. Tellez, G. Litjens, J. van der Laak and F. Ciompi, "Neural Image Compression for Gigapixel Histopathology Image Analysis.", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021;43(2):567-578.
    Abstract DOI PMID
  32. F. Michallek, H. Huisman, B. Hamm, S. Elezkurtaj, A. Maxeiner and M. Dewey, "Prediction of prostate cancer grade using fractal analysis of perfusion MRI: retrospective proof‑of‑principle study", European Radiology, 2021.
    Abstract DOI
  33. A. Sekuboyina, M. Husseini, A. Bayat, M. Löffler, H. Liebl, H. Li, G. Tetteh, J. Kukačka, C. Payer, D. Štern, M. Urschler, M. Chen, D. Cheng, N. Lessmann, Y. Hu, T. Wang, D. Yang, D. Xu, F. Ambellan, T. Amiranashvili, M. Ehlke, H. Lamecker, S. Lehnert, M. Lirio, N. de Olaguer, H. Ramm, M. Sahu, A. Tack, S. Zachow, T. Jiang, X. Ma, C. Angerman, X. Wang, K. Brown, A. Kirszenberg, É. Puybareau, D. Chen, Y. Bai, B. Rapazzo, T. Yeah, A. Zhang, S. Xu, F. Hou, Z. He, C. Zeng, Z. Xiangshang, X. Liming, T. Netherton, R. Mumme, L. Court, Z. Huang, C. He, L. Wang, S. Ling, L. Huỳnh, N. Boutry, R. Jakubicek, J. Chmelik, S. Mulay, M. Sivaprakasam, J. Paetzold, S. Shit, I. Ezhov, B. Wiestler, B. Glocker, A. Valentinitsch, M. Rempfler, B. Menze and J. Kirschke, "VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images", Medical Image Analysis, 2021;73:102166.
    Abstract DOI Cited by ~2
  34. J. Bleker, D. Yakar, B. van Noort, D. Rouw, I. de Jong, R. Dierckx, T. Kwee and H. Huisman, "Single-center versus multi-center biparametric MRI radiomics approach for clinically significant peripheral zone prostate cancer", Insights into Imaging, 2021;12(1).
    Abstract DOI
  35. A. Reinke, M. Eisenmann, M. Tizabi, C. Sudre, T. Rädsch, M. Antonelli, T. Arbel, S. Bakas, M. Cardoso, V. Cheplygina, K. Farahani, B. Glocker, D. Heckmann-Nötzel, F. Isensee, P. Jannin, C. Kahn, J. Kleesiek, T. Kurc, M. Kozubek, B. Landman, G. Litjens, K. Maier-Hein, B. Menze, H. Müller, J. Petersen, M. Reyes, N. Rieke, B. Stieltjes, R. Summers, S. Tsaftaris, B. van Ginneken, A. Kopp-Schneider, P. Jäger and L. Maier-Hein, "Common Limitations of Image Processing Metrics: A Picture Story", 2021.
    Abstract
  36. A. Hering, S. Häger, J. Moltz, N. Lessmann, S. Heldmann and B. van Ginneken, "CNN-based Lung CT Registration with Multiple Anatomical Constraints", Medical Image Analysis, 2021;72:102139.
    Abstract DOI Algorithm
  37. C. de Vente, L. Boulogne, K. Venkadesh, C. Sital, N. Lessmann, C. Jacobs, C. Sánchez and B. van Ginneken, "Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison", IEEE Transactions on Artificial Intelligence, 2021.
    Abstract DOI
  38. C. Jacobs, A. Setio, E. Scholten, P. Gerke, H. Bhattacharya, F. M. Hoesein, M. Brink, E. Ranschaert, P. de Jong, M. Silva, B. Geurts, K. Chung, S. Schalekamp, J. Meersschaert, A. Devaraj, P. Pinsky, S. Lam, B. van Ginneken and K. Farahani, "Deep Learning for Lung Cancer Detection in Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists", Radiology: Artificial Intelligence, 2021;3(6):e210027.
    Abstract DOI
  39. M. Hosseinzadeh, A. Saha, P. Brand, I. Slootweg, M. de Rooij and H. Huisman, "Deep learning–assisted prostate cancer detection on bi-parametric MRI: minimum training data size requirements and effect of prior knowledge", European Radiology, 2021.
    Abstract DOI
  40. M. Antonelli, A. Reinke, S. Bakas, K. Farahani, AnnetteKopp-Schneider, B. Landman, G. Litjens, B. Menze, O. Ronneberger, R. Summers, B. van Ginneken, M. Bilello, P. Bilic, P. Christ, R. Do, M. Gollub, S. Heckers, H. Huisman, W. Jarnagin, M. McHugo, S. Napel, J. Pernicka, K. Rhode, C. Tobon-Gomez, E. Vorontsov, H. Huisman, J. Meakin, S. Ourselin, M. Wiesenfarth, P. Arbelaez, B. Bae, S. Chen, L. Daza, J. Feng, B. He, F. Isensee, Y. Ji, F. Jia, N. Kim, I. Kim, D. Merhof, A. Pai, B. Park, M. Perslev, R. Rezaiifar, O. Rippel, I. Sarasua, W. Shen, J. Son, C. Wachinger, L. Wang, Y. Wang, Y. Xia, D. Xu, Z. Xu, Y. Zheng, A. Simpson, L. Maier-Hein and M. Cardoso, "The Medical Segmentation Decathlon", 2021.
    Abstract
  41. A. Saha, M. Hosseinzadeh and H. Huisman, "End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effects of Attention Mechanisms, Clinical Priori and Decoupled False Positive Reduction", Medical Image Analysis, 2021:102155.
    Abstract DOI GitHub Algorithm
  42. K. Leeuwen, F. Meijer, S. Schalekamp, M. Rutten, E. Dijk, B. Ginneken, T. Govers and M. Rooij, "Cost ‑ effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke : an early health technology assessment", Insights into Imaging, 2021;12:133.
    Abstract DOI
  43. N. Hendrix, E. Scholten, B. Vernhout, S. Bruijnen, B. Maresch, M. de Jong, S. Diepstraten, S. Bollen, S. Schalekamp, M. de Rooij, A. Scholtens, W. Hendrix, T. Samson, L. Sharon Ong, E. Postma, B. van Ginneken and M. Rutten, "Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs", Radiology: Artificial Intelligence, 2021:e200260.
    Abstract DOI Algorithm
  44. T. Perik, E. van Genugten, E. Aarntzen, E. Smit, H. Huisman and J. Hermans, "Quantitative CT perfusion imaging in patients with pancreatic cancer: a systematic review", Abdominal Radiology, 2021.
    Abstract DOI
  45. F. Michallek, H. Huisman, B. Hamm, S. Elezkurtaj, A. Maxeiner and M. Dewey, "Accuracy of fractal analysis and PI‑RADS assessment of prostate magnetic resonance imaging for prediction of cancer grade groups: a clinical validation study", European Radiology, 2021.
    Abstract DOI
  46. D. Winkel, A. Tong, B. Lou, A. Kamen, D. Comaniciu, J. Disselhorst, A. Rodr\'ıguez-Ruiz, H. Huisman, D. Szolar, I. Shabunin, M. Choi, P. Xing, T. Penzkofer, R. Grimm, H. von Busch and D. Boll, "A Novel Deep Learning Based Computer-Aided Diagnosis System Improves the Accuracy and Efficiency of Radiologists in Reading Biparametric Magnetic Resonance Images of the Prostate", Investigative Radiology, 2021;Publish Ahead of Print.
    Abstract DOI
  47. K. van Leeuwen, M. de Rooij, S. Schalekamp, B. van Ginneken and M. Rutten, "How does artificial intelligence in radiology improve efficiency and health outcomes?", Pediatric Radiology, 2021.
    Abstract DOI
  48. J. Twilt, K. van Leeuwen, H. Huisman, J. Fütterer and M. de Rooij, "Artificial Intelligence Based Algorithms for Prostate Cancer Classification and Detection on Magnetic Resonance Imaging: A Narrative Review", Diagnostics, 2021;11(6).
    Abstract DOI
  49. E. Çallı, K. Murphy, S. Kurstjens, T. Samson, R. Herpers, H. Smits, M. Rutten and B. van Ginneken, "Deep learning with robustness to missing data: A novel approach to the detection of COVID-19", PLoS One, 2021;16(7):e0255301.
    Abstract DOI

Papers in conference proceedings

  1. A. Reinke, M. Eisenmann, M. Tizabi, C. Sudre, T. Rädsch, M. Antonelli, T. Arbel, S. Bakas, J. Cardoso, V. Cheplygina, K. Farahani, B. Glocker, D. Heckmann-Nötzel, F. Isensee, P. Jannin, C. Kahn, J. Kleesiek, T. Kurc, M. Kozubek, B. Landman, G. Litjens, K. Maier-Hein, A. Martel, H. Müller, J. Petersen, M. Reyes, N. Rieke, B. Stieltjes, R. Summers, S. Tsaftaris, B. van Ginneken, A. Kopp-Schneider, P. Jäger and L. Maier-Hein, "Common limitations of performance metrics in biomedical image analysis", Medical Imaging with Deep Learning, 2021.
    Abstract DOI
  2. S. Häger, S. Heldmann, A. Hering, S. Kuckertz and A. Lange, "Variable Fraunhofer MEVIS RegLib Comprehensively Applied to Learn2Reg Challenge", Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data. MICCAI 2020, 2021;12587:74-79.
    Abstract DOI
  3. A. Hering, F. Peisen, T. Amaral, S. Gatidis, T. Eigentler, A. Othman and J. Moltz, "Whole-Body Soft-Tissue Lesion Tracking and Segmentation in Longitudinal CT Imaging Studies", Medical Imaging with Deep Learning, 2021.
    Abstract Url
  4. M. van Rijthoven, M. Balkenhol, M. Atzori, P. Bult, J. van der Laak and F. Ciompi, "Few-shot weakly supervised detection and retrieval in histopathology whole-slide images", Medical Imaging, 2021;11603:137 - 143.
    Abstract DOI
  5. D. Geijs, H. Pinckaers, A. Amir and G. Litjens, "End-to-end classification on basal-cell carcinoma histopathology whole-slides images", Medical Imaging, 2021;11603:1160307.
    Abstract DOI
  6. W. Xie, C. Jacobs and B. van Ginneken, "Deep Clustering Activation Maps for Emphysema Subtyping", Medical Imaging with Deep Learning, 2021.
    Abstract Url
  7. W. Aswolinskiy, D. Tellez, G. Raya, L. van der Woude, M. Looijen-Salamon, J. van der Laak, K. Grunberg and F. Ciompi, "Neural image compression for non-small cell lung cancer subtype classification in H&E stained whole-slide images", Medical Imaging 2021: Digital Pathology, 2021;11603:1 - 7.
    Abstract DOI
  8. G. Smit, F. Ciompi, M. Cigéhn, A. Bodén, J. van der Laak and C. Mercan, "Quality control of whole-slide images through multi-class semantic segmentation of artifacts", Medical Imaging with Deep Learning, 2021.
    Abstract Url
  9. A. Saha, J. Bosma, J. Linmans, M. Hosseinzadeh and H. Huisman, "Anatomical and Diagnostic Bayesian Segmentation in Prostate MRI —Should Different Clinical Objectives Mandate Different Loss Functions?", Medical Imaging Meets NeurIPS Workshop - 35th Conference on Neural Information Processing Systems (NeurIPS), 2021.
    Abstract arXiv
  10. B. de Wilde, R. ten Broek and H. Huisman, "Cine-MRI detection of abdominal adhesions with spatio-temporal deep learning", Medical Imaging with Deep Learning, 2021.
    Abstract arXiv
  11. K. Faryna, J. van der Laak and G. Litjens, "Tailoring automated data augmentation to H&E-stained histopathology", Medical Imaging with Deep Learning, 2021.
    Abstract Url
  12. J. Vermazeren, L. van Eekelen, L. Meesters, M. Looijen-Salamon, S. Vos, E. Munari, C. Mercan and F. Ciompi, "muPEN: Multi-class PseudoEdgeNet for PD-L1 assessment", Medical Imaging with Deep Learning, 2021.
    Abstract Url

Abstracts

  1. C. de Vente, C. González-Gonzalo, E. Thee, M. van Grinsven, C. Klaver and C. Sánchez, "Making AI Transferable Across OCT Scanners from Different Vendors", Association for Research in Vision and Ophthalmology, 2021.
    Abstract Url
  2. C. González-Gonzalo, E. Thee, B. Liefers, C. Klaver and C. Sánchez, "Deep learning for automated stratification of ophthalmic images: Application to age-related macular degeneration and color fundus images", European Society of Retina Specialists, 2021.
    Abstract Url
  3. N. Alves, J. Hermans and H. Huisman, "CT-based Deep Learning Towards Early Detection Of Pancreatic Ductal Adenocarcinoma", Annual Meeting of the Radiological Society of North America, 2021.
    Abstract
  4. W. Hendrix, N. Hendrix, M. Prokop, E. Scholten, B. Van Ginneken, M. Rutten and C. Jacobs, "Trends in the Incidence of Pulmonary Nodules in Chest Computed Tomography: 10-Year Results from Two Dutch Hospitals", European Congress of Radiology, 2021.
    Abstract DOI
  5. K. Venkadesh, A. Schreuder, E. Scholten, S. Atkar-Khattra, J. Mayo, Z. Saghir, M. Wille, B. van Ginneken, S. Lam, M. Prokop and C. Jacobs, "Integration Of A Deep Learning Algorithm Into The Clinically Established PanCan Model For Malignancy Risk Estimation Of Screen-detected Pulmonary Nodules In First Screening CT", Annual Meeting of the Radiological Society of North America, 2021.
    Abstract
  6. J. Bosma, A. Saha, M. Hosseinzadeh and H. Huisman, "Augmenting AI with Automated Segmentation of Report Findings Applied to Prostate Cancer Detection in Biparametric MRI", Annual Meeting of the Radiological Society of North America, 2021.
    Abstract
  7. C. González-Gonzalo, F. Verbraak, R. Schlingemann, C. Klaver, A. Lee, A. Tufail and C. Sánchez, "Trustworthy AI: closing the gap between development and integration of AI in Ophthalmology", European Association for the Study of Diabetes Eye Complications Study Group, 2021.
    Abstract Url
  8. C. González-Gonzalo, E. Thee, B. Liefers, C. de Vente, C. Klaver and C. Sánchez, "Hierarchical curriculum learning for robust automated detection of low-prevalence retinal disease features: application to reticular pseudodrusen", Association for Research in Vision and Ophthalmology, 2021.
    Abstract Url
  9. A. Saha, J. Bosma, C. Roest, M. Hosseinzadeh, J. Fütterer and H. Huisman, "Deep Learning with Bayesian Inference for Prostate Cancer Diagnosis across Longitudinal Biparametric MRI", Annual Meeting of the Radiological Society of North America, 2021.
    Abstract

PhD theses

  1. A. Schreuder, "Lung cancer screening: use the scan to decide who to scan when", 2021.
    Abstract Url
  2. D. Tellez, "Advancing computational pathology with deep learning: from patches to gigapixel image-level classification", 2021.
    Abstract Url