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van der Laak, Jeroen

  1. HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images
    2020/06/22 by Mart van Rijthoven, van Rijthoven, Mart, Maschenka Balkenhol +8 · 10 citations
    Computer Science · Engineering · Medicine · #AI in cancer detection #Cervical Cancer and HPV Research #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Radiomics and Machine Learning in Medical Imaging #cs.CV #cs.LG #eess.IV #electronic engineering #information engineering
  2. The importance of stain normalization in colorectal tissue classification with convolutional networks
    2017/02/20 by Francesco Ciompi, Ciompi, Francesco, Oscar Geessink +16 · 4 citations
    Computer Science · Medicine · #AI in cancer detection #Digital Imaging for Blood Diseases #Radiomics and Machine Learning in Medical Imaging #cs.CV #cs.LG
  3. Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels
    2020/06/05 by Hans Pinckaers, Pinckaers, Hans, Wouter Bulten +5 · 3 citations
    Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #cs.CV #eess.IV #electronic engineering #information engineering
  4. Uncertainty-guided annotation enhances segmentation with the human-in-the-loop
    2024/02/16 by Nadieh Khalili, Joey Spronck, Khalili, Nadieh +7 · 2 citations
    Medicine · #Radiomics and Machine Learning in Medical Imaging #Artificial Intelligence in Healthcare and Education #COVID-19 diagnosis using AI
  5. Hierarchical Vision Transformers for Context-Aware Prostate Cancer Grading in Whole Slide Images
    2023/12/19 by Grisi, Clément, Litjens, Geert, van der Laak, Jeroen · 1 citation
    #68T07 #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #I.2.10