Will Transformers change gastrointestinal endoscopic image analysis? A comparative analysis between CNNs and Transformers, in terms of performance, robustness and generalization von Kusters, Carolus H.J., Jaspers, Tim J.M., Boers, Tim G.W., Jong, Martijn R., Jukema, Jelmer B., Fockens, Kiki N., de Groof, Albert J., Bergman, Jacques J., van der Sommen, Fons, De With, Peter H.N.

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The use of a real-time computer-aided detection system for visible lesions in the Barrett’s esophagus during live endoscopic procedures: a pilot study (with video) von Fockens, Kiki N., Jukema, Jelmer B., Jong, Martijn R., Boers, Tim, van der Putten, Joost A., Kusters, Carolus H.J., Pouw, Roos E., Duits, Lucas C., van der Sommen, Fons, de With, Peter H., de Groof, A. Jeroen, Bergman, Jacques J., Alkhalaf, Alaa, Herrero, Lorenza Alvarez, Baldaque-Silva, Francisco, Barret, Maximilien, Bergman, Jacques J., Beyna, Torsten, Boers, Tim G., Elbe, Peter, Fockens, Kiki N., de Groof, Albert J., Houben, Martin H., Jong, Martijn, Jukema, Jelmer B., Kusters, Koen C., Mallant-Hent, Rosalie C., Villarejo, Guiomar Moral, Nagengast, Wouter, Fernández-Sordo, Jacobo Ortiz, Pech, Oliver, Pouw, Roos E., van der Putten, Joost A., Ragunath, Krish, Scholten, Pieter, Seewald, Stefan, der Sommen, Fons van, Westerhof, Jessie, Weusten, Bas L., de With, Peter H.

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Robustness evaluation of deep neural networks for endoscopic image analysis: Insights and strategies von Jaspers, Tim J.M., Boers, Tim G.W., Kusters, Carolus H.J., Jong, Martijn R., Jukema, Jelmer B., de Groof, Albert J., Bergman, Jacques J., de With, Peter H.N., van der Sommen, Fons

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Foundation models in gastrointestinal endoscopic AI: Impact of architecture, pre-training approach and data efficiency von Boers, Tim G.W., Fockens, Kiki N., van der Putten, Joost A., Jaspers, Tim J.M., Kusters, Carolus H.J., Jukema, Jelmer B., Jong, Martijn R., Struyvenberg, Maarten R., de Groof, Jeroen, Bergman, Jacques J., de With, Peter H.N., van der Sommen, Fons

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Investigating the Impact of Image Quality on Endoscopic AI Model Performance von Jaspers, Tim J. M., Boers, Tim G. W., Kusters, Carolus H. J., Jong, Martijn R., Jukema, Jelmer B., de Groof, Albert J., Bergman, Jacques J., de With, Peter H. N., van der Sommen, Fons

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CNNs vs. Transformers: Performance and Robustness in Endoscopic Image Analysis von Kusters, Carolus H. J., Boers, Tim G. W., Jaspers, Tim J. M., Jukema, Jelmer B., Jong, Martijn R., Fockens, Kiki N., de Groof, Albert J., Bergman, Jacques J., van der Sommen, Fons, de With, Peter H. N.

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Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: the role of human/artificial intelligence interaction von van der Zander, Quirine E.W., Roumans, Rachel, Kusters, Carolus H.J., Dehghani, Nikoo, Masclee, Ad A.M., de With, Peter H.N., van der Sommen, Fons, Snijders, Chris C.P., Schoon, Erik J.

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Exploring the Effect of Dataset Diversity in Self-Supervised Learning for Surgical Computer Vision von Jaspers, Tim J M, Ronald L P D de Jong, Yasmina Al Khalil, Zeelenberg, Tijn, Kusters, Carolus H J, Li, Yiping, van Jaarsveld, Romy C, Bakker, Franciscus H A, Ruurda, Jelle P, Brinkman, Willem M, Peter H N De With, Fons van der Sommen

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A deep learning system for detection of early Barrett's neoplasia: a model development and validation study von Fockens, K N, Jong, M R, Jukema, J B, Boers, T G W, Kusters, C H J, van der Putten, J A, Pouw, R E, Duits, L C, Montazeri, N S M, van Munster, S N, Weusten, B L A M, Alvarez Herrero, L, Houben, M H M G, Nagengast, W B, Westerhof, J, Alkhalaf, A, Mallant-Hent, R C, Scholten, P, Ragunath, K, Seewald, S, Elbe, P, Baldaque-Silva, F, Barret, M, Ortiz Fernández-Sordo, J, Villarejo, G Moral, Pech, O, Beyna, T, van der Sommen, F, de With, P H, de Groof, A J, Bergman, J J

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A CAD System for Real-Time Characterization of Neoplasia in Barrett's Esophagus NBI Videos von Kusters, Carolus H. J., Boers, Tim G. W., Jukema, Jelmer B., Jong, Martijn R., Fockens, Kiki N., de Groof, Albert J., Bergman, Jacques J., der Sommen, Fons van, de With, Peter H. N.

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Comparing Training Strategies Using Multi-Assessor Segmentation Labels for Barrett's Neoplasia Detection von Boers, Tim G. W., Kusters, Carolus H. J., Fockens, Kiki N., Jukema, Jelmer B., Jong, Martijn R., de Groof, Jeroen, Bergman, Jacques J., van der Sommen, Fons, de With, Peter H. N.

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Optimizing Multi-expert Consensus for Classification and Precise Localization of Barrett’s Neoplasia von Kusters, Carolus H. J., Boers, Tim G. W., Jaspers, Tim J. M., Jong, Martijn R., van Eijck van Heslinga, Rixta A. H., de Groof, Albert J., Bergman, Jacques J., van der Sommen, Fons, De With, Peter H. N.

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Exploring the Effect of Dataset Diversity in Self-supervised Learning for Surgical Computer Vision von Jaspers, Tim J. M., de Jong, Ronald L. P. D., Al Khalil, Yasmina, Zeelenberg, Tijn, Kusters, Carolus H. J., Li, Yiping, van Jaarsveld, Romy C., Bakker, Franciscus H. A., Ruurda, Jelle P., Brinkman, Willem M., De With, Peter H. N., van der Sommen, Fons

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Computer-aided diagnosis improves characterization of Barrett’s neoplasia by general endoscopists (with video) von Jukema, Jelmer B., Kusters, Carolus H.J., Jong, Martijn R., Fockens, Kiki N., Boers, Tim, van der Putten, Joost A., Pouw, Roos E., Duits, Lucas C., Weusten, Bas L.A.M., Herrero, Lorenza Alvarez, Houben, Martin H.M.G., Nagengast, Wouter B., Westerhof, Jessie, Alkhalaf, Alaa, Mallant-Hent, Rosalie, Scholten, Pieter, Ragunath, Krish, Seewald, Stefan, Elbe, Peter, Silva, Francisco Baldaque, Barret, Maximilien, Ortiz Fernández-Sordo, Jacobo, Moral Villarejo, Guiomar, Pech, Oliver, Beyna, Torsten, Montazeri, Nahid S.M., der Sommen, Fons van, de With, Peter H., de Groof, A. Jeroen, Bergman, Jacques J., Alkhalaf, Alaa, Herrero, Lorenza Alvarez, Baldaque-Silva, Francisco, Barret, Maximilien, Bergman, Jacques J., Beyna, Torsten, Bisschops, Raf, Boers, Tim G., Curvers, Wouter, Deprez, Pierre H., Duits, Lucas C., Elbe, Peter, Esteban, Jose Miguel, Falk, Gary W., Fockens, Kiki N., Ginsberg, Gregory G., de Groof, Albert J., Haidry, Rehan, Houben, Martin H., Infantolino, Anthony, Iyer, Prasad G., Jong, Martijn, Jonge, Pieter-Jan de, Jukema, Jelmer B., Koch, Arjun, Komanduri, Srinadh, Konda, Vani, Kusters, Koen C., Leclerq, Philippe, Leggett, Cadman L., Lightdale, Charles J., Mallant-Hent, Rosalie C., Villarejo, Guiomar Moral, Fernández-Sordo, Jacobo Ortiz, Pech, Oliver, Penman, Ian, Pouw, Roos E., van der Putten, Joost A., Ragunath, Krish, Scholten, Pieter, Seewald, Stefan, Sethi, Amritha, Smith, Michael S., van der Sommen, Fons, Trindade, Arvind, Wani, Sachin, Waxman, Irving, Westerhof, Jessie, Weusten, Bas L., de With, Peter H., Wolfsen, Herbert C.

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The use of a real-time computer-aided detection system for visible lesions in the Barrett's esophagus during live endoscopic procedures: a pilot study (with video) von Fockens, Kiki N, Jukema, Jelmer B, Jong, Martijn, Pouw, Roos E, Duits, Lucas C, de Groof, Albert J, Bergman, Jacques J, Boers, Tim G, van der Putten, Joost A, Kusters, Carolus H.J, der Sommen, Fons van, de With, Peter H, Alkhalaf, Alaa, Herrero, Lorenza Alvarez, Baldaque-Silva, Francisco, Barret, Maximilien, Weusten, Bas L, BONS-AI consortium

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