Publications of Daan Geijs

all all years 2024 2021 2019 2018 2017

Papers in international journals

  1. V. Varra, K. Shahwan, K. Johnson, R. Kirven, T. Walker, D. Geijs, G. Litjens and D. Carr, "Deep Learning for Automated Segmentation of Basal Cell Carcinoma on Mohs Micrographic Surgery Frozen Section Slides", Dermatologic Surgery, 2024.
    Abstract DOI PMID
  2. 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.
    Abstract DOI PMID
  3. 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.
    Abstract DOI PMID
  4. 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.
    Abstract DOI PMID
  5. 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 Cited by ~27
  6. 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 Cited by ~20

Papers in conference proceedings

  1. 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.
    Abstract DOI
  2. 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 Cited by ~2
  3. D. Geijs, M. Intezar, J. van der Laak and G. Litjens, "Automatic color unmixing of IHC stained whole slide images", Medical Imaging, 2018;10581.
    Abstract DOI Cited by ~11
  4. 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.
    Abstract DOI arXiv Cited by ~38

Master theses

  1. D. Geijs, "Tumor segmentation in fluorescent TNBC immunohistochemical multiplex images using deep learning", Master thesis, 2019.
    Abstract