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. 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.