J. Linmans, G. Raya, J. van der Laak and G. Litjens, "Diffusion models for out-of-distribution detection in digital pathology",
Medical Image Analysis,
2024;93:103088.
J. Bogaerts, J. Bokhorst, M. Simons, M. van Bommel, M. Steenbeek, J. de Hullu, J. Linmans, J. Bart, J. Bentz, T. Bosse, J. Bulten, Y. Chien, M. Desouki, R. Lastra, T. Numan, J. Schoolmeester, L. Schwartz, I. Shih, T. Soong, G. Turashvili, R. Vang, M. Volchek and J. van der Laak, "Deep learning detects premalignant lesions in the Fallopian tube",
npj Women's Health,
2024;2.
J. Linmans, E. Hoogeboom, J. van der Laak and G. Litjens, "The Latent Doctor Model for Modeling Inter-Observer Variability",
IEEE Journal of Biomedical and Health Informatics,
2023:1-12.
J. Linmans, S. Elfwing, J. van der Laak and G. Litjens, "Predictive uncertainty estimation for out-of-distribution detection in digital pathology.",
Medical Image Analysis,
2023;83:102655.
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.
A. Saha, J.S. 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.
J. Linmans, J. van der Laak and G. Litjens, "Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks",
Medical Imaging with Deep Learning,
2020:465-478.