Publications of Daan Geijs
2024
Papers in international journals
- D. Geijs, L. Hillen, S. Dooper, V. Winnepenninckx, V. Varra, D. Carr, K. Shahwan, G. Litjens and A. Amir, "Weakly-supervised classification of Mohs surgical sections using artificial intelligence", Modern Pathology, 2024:100653.
- E. Smeets, M. Trajkovic-Arsic, D. Geijs, S. Karakaya, M. van Zanten, L. Brosens, B. Feuerecker, M. Gotthardt, J. Siveke, R. Braren, F. Ciompi and E. Aarntzen, "Histology-Based Radiomics for [18F]FDG PET Identifies Tissue Heterogeneity in Pancreatic Cancer", Journal of Nuclear Medicine, 2024:jnumed.123.266262.
- D. Geijs, S. Dooper, W. Aswolinskiy, L. Hillen, A. Amir and G. Litjens, "Detection and subtyping of basal cell carcinoma in whole-slide histopathology using weakly-supervised learning", Medical Image Analysis, 2024;93:103063.
Papers in conference proceedings
- C. Lems, D. Geijs, J. Bokhorst, M. Sülter, L. van Eekelen and F. Ciompi, "Color Deconvolution for Color-Agnostic and Cross-Modality Analysis of Immunohistochemistry Whole-Slide Images with Deep Learning", 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024:1-4.
2021
Papers in international journals
- 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.
- 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.
Papers in conference proceedings
- 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.
2019
Master theses
- D. Geijs, "Tumor segmentation in fluorescent TNBC immunohistochemical multiplex images using deep learning", Master thesis, 2019.
2018
Papers in conference proceedings
- D. Geijs, M. Intezar, J. van der Laak and G. Litjens, "Automatic color unmixing of IHC stained whole slide images", Medical Imaging, 2018;10581.
2017
Papers in conference proceedings
- P. Bándi, R. van de Loo, M. Intezar, D. Geijs, F. Ciompi, B. van Ginneken, J. van der Laak and G. Litjens, "Comparison of Different Methods for Tissue Segmentation In Histopathological Whole-Slide Images", IEEE International Symposium on Biomedical Imaging, 2017:591-595.