Publications of Daan Geijs

2024

Papers in international journals

  1. 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
  2. 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

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

2021

Papers in international journals

  1. 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
  2. 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. 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

2019

Master theses

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

2018

Papers in conference proceedings

  1. 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

2017

Papers in conference proceedings

  1. 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