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. 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 PMID Download
  3. 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.", Pathology, 2021.
    Abstract DOI PMID Download
  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. Wahlby, 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.", European Urology Focus, 2021;7(4):687-691.
    Abstract DOI PMID Download
  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 Download
  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. Calli, 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 Download
  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. E. Munari, M. Marconi, G. Querzoli, G. Lunardi, P. Bertoglio, F. Ciompi, A. Tosadori, A. Eccher, N. Tumino, L. Quatrini, P. Vacca, G. Rossi, A. Cavazza, G. Martignoni, M. Brunelli, G. Netto, L. Moretta, G. Zamboni and G. Bogina, "Impact of PD-L1 and PD-1 Expression on the Prognostic Significance of CD8+, Tumor-Infiltrating Lymphocytes in Non-Small Cell Lung Cancer.", Frontiers in immunology, 2021;12:680973.
    Abstract DOI PMID Download
  12. E. Munari, F. Mariotti, L. Quatrini, P. Bertoglio, N. Tumino, P. Vacca, A. Eccher, F. Ciompi, M. Brunelli, G. Martignoni, G. Bogina and L. Moretta, "PD-1/PD-L1 in Cancer: Pathophysiological, Diagnostic and Therapeutic Aspects.", International journal of molecular sciences, 2021;22(10).
    Abstract DOI PMID
  13. M. Hermsen, V. Volk, J. Brasen, 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 Download
  14. 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
  15. 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 Download
  16. 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 Download
  17. B. de Vos, N. Lessmann, P. de Jong and I. Isgum, "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 Download
  18. 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. Isgum 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 Download
  19. 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 Download
  20. 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
  21. 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 Download
  22. 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 Download
  23. 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 Download
  24. 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 Download
  25. M. Balkenhol, F. Ciompi, Z. Swiderska-Chadaj, R. van de Loo, M. Intezar, I. Otte-Holler, 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.", The Breast, 2021;56:78-87.
    Abstract DOI PMID
  26. 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.", Toxicologic Pathology, 2021;49(4):714-719.
    Abstract DOI PMID Download
  27. A. Schreuder, C. Jacobs, N. Lessmann, M. Broeders, M. Silva, I. Isgum, 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
  28. 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
  29. 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 Download
  30. 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 Algorithm Download
  31. 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 Download
  32. 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 Download
  33. 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 Download
  34. A. Hering, S. Hager, 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 Download
  35. 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 Algorithm Download
  36. 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
  37. A. Sekuboyina, M. Husseini, A. Bayat, M. Loffler, H. Liebl, H. Li, G. Tetteh, J. Kukacka, C. Payer, D. Stern, 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, E. 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. Huynh, 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 Download
  38. 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 Download
  39. E. Calli, 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 Download
  40. N. Marini, S. Otálora, D. Podareanu, M. van Rijthoven, J. van der Laak, F. Ciompi, H. Muller and M. Atzori, "Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images", Frontiers in Computer Science, 2021;3.
    Abstract DOI
  41. J. Bogaerts, M. Steenbeek, M. van Bommel, J. Bulten, J. van der Laak, J. de Hullu and M. Simons, "Recommendations for diagnosing STIC: a systematic review and meta-analysis", 2021;480(4):725-737.
    Abstract DOI Download
  42. 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 Download
  43. 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 Download
  44. 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 Download
  45. 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 Download
  46. F. Ciompi, M. Veta, J. van der Laak and N. Rajpoot, "Editorial Computational Pathology", IEEE} Journal of Biomedical and Health Informatics, 2021;25(2):303-306.
    Abstract DOI
  47. 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
  48. K. van Leeuwen, F. Meijer, S. Schalekamp, M. Rutten, E. van Dijk, B. vam 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

Preprints

  1. A. Reinke, M. Eisenmann, M. Tizabi, C. Sudre, T. Radsch, M. Antonelli, T. Arbel, S. Bakas, M. Cardoso, V. Cheplygina, K. Farahani, B. Glocker, D. Heckmann-Notzel, F. Isensee, P. Jannin, C. Kahn, J. Kleesiek, T. Kurc, M. Kozubek, B. Landman, G. Litjens, K. Maier-Hein, B. Menze, H. Muller, J. Petersen, M. Reyes, N. Rieke, B. Stieltjes, R. Summers, S. Tsaftaris, B. van Ginneken, A. Kopp-Schneider, P. Jager and L. Maier-Hein, "Common Limitations of Image Processing Metrics: A Picture Story", arXiv preprint arXiv:2104.05642, 2021.
    Abstract arXiv
  2. 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", arXiv preprint arXiv:2106.05735, 2021.
    Abstract arXiv
  3. A. Hering, L. Hansen, T. Mok, A. Chung, H. Siebert, S. Häger, A. Lange, S. Kuckertz, S. Heldmann, W. Shao and others, "Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning", arXiv preprint arXiv:2112.04489, 2021.
    Abstract arXiv
  4. W. Xie, C. Jacobs and B. van Ginneken, "Dense regression activation maps for lesion segmentation in CT scans of COVID-19 patients", arXiv:2105.11748, 2021.
    Abstract arXiv

Papers in conference proceedings

  1. 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
  2. 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
  3. W. Xie, C. Jacobs and B. van Ginneken, "Deep Clustering Activation Maps for Emphysema Subtyping", Medical Imaging with Deep Learning, 2021.
    Abstract Url
  4. 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
  5. A. Reinke, M. Eisenmann, M. Tizabi, C. Sudre, T. Radsch, M. Antonelli, T. Arbel, S. Bakas, J. Cardoso, V. Cheplygina, K. Farahani, B. Glocker, D. Heckmann-Notzel, F. Isensee, P. Jannin, C. Kahn, J. Kleesiek, T. Kurc, M. Kozubek, B. Landman, G. Litjens, K. Maier-Hein, A. Martel, H. Muller, J. Petersen, M. Reyes, N. Rieke, B. Stieltjes, R. Summers, S. Tsaftaris, B. van Ginneken, A. Kopp-Schneider, P. Jager and L. Maier-Hein, "Common limitations of performance metrics in biomedical image analysis", Medical Imaging with Deep Learning, 2021.
    Abstract DOI
  6. 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
  7. N. Marini, S. Otalora, F. Ciompi, G. Silvello, S. Marchesin, S. Vatrano, G. Buttafuoco, M. Atzori, H. Muller, N. Burlutskiy, Z. Li, F. Minhas, T. Peng, N. Rajpoot, B. Torbennielsen, J. Der Van Laak, M. Veta, Y. Yuan and I. Zlobec, "Multi-Scale Task Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations", 2021.
    Abstract
  8. 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
  9. 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
  10. 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
  11. 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
  12. R. Fick, B. Tayart, C. Bertrand, S. Lang, T. Rey, F. Ciompi, C. Tilmant, I. Farre and S. Hadj, "A Partial Label-Based Machine Learning Approach For Cervical Whole-Slide Image Classification: The Winning TissueNet Solution", 2021 43rd Annual International Conference of the {IEEE} Engineering in Medicine and Biology Society ({EMBC}), 2021.
    Abstract DOI
  13. 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
  14. 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

Abstracts

  1. K. van Leeuwen, M. Rutten, S. Schalekamp, M. de Rooij and B. van Ginneken, "Clinical use of artificial intelligence in radiology departments in the Netherlands: a survey", European Congress of Radiology, 2021.
    Abstract
  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. K. van Leeuwen, F. Meijer, S. Schalekamp, M. Rutten, E. van Dijk, B. van Ginneken, T. Govers and M. de Rooij, "Artificial Intelligence in Acute Stroke: an Early Health Technology Assessment of Vessel Occlusion Detection on Computed Tomography", European Congress of Radiology, 2021.
    Abstract
  4. 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
  5. Y. Jiao, M. Rijthoven, J. Li, K. Grunberg, S. Fei and F. Ciompi, "Automatic Lung Cancer Segmentation in Histopathology Whole-Slide Images with Deep Learning", European Congress on Digital Pathology (ECDP), 2021.
    Abstract
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. K. van Leeuwen, M. de Rooij, M. Rutten, B. van Ginneken and S. Schalekamp, "Performance Of A Commercial Software Package For Lung Nodule Detection On Chest Radiographs Compared With 8 Expert Readers", Annual Meeting of the Radiological Society of North America, 2021.
    Abstract
  12. A. Saha, J. Bosma, C. Roest, M. Hosseinzadeh, J. Futterer 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
  13. K. van Leeuwen, M. de Rooij, M. Rutten, S. Schalekamp and B. van Ginneken, "Commercial Artificial Intelligence Solutions For Radiology: A Market Update", Annual Meeting of the Radiological Society of North America, 2021.
    Abstract
  14. 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

PhD theses

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

Master theses

  1. J. Verboom, "Deep Learning for Fracture Detection in the Radius and Ulna on Conventional Radiographs", Master thesis, 2021.
    Abstract
  2. E. Martynova, "Artificial intelligence-assisted detection of adhesions on cine-MRI", Master thesis, 2021.
    Abstract
  3. I. Guclu, "Programmatically generating annotations for de-identification of clinical data", Master thesis, 2021.
    Abstract
  4. R. HACKING, "Combining CT scans and clinical features for improved automated COVID-19 detection", Master thesis, 2021.
    Abstract
  5. 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", Master thesis, 2021.
    Abstract Url