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Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep Learning

  • John-Melle Bokhorst
  • Lucia Rijstenberg
  • Danny Goudkade
  • Iris Nagtegaal
  • Jeroen van der Laak
  • Francesco Ciompi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11039)

Abstract

Colorectal cancer patients would benefit from a valid, reliable and efficient detection of Tumor Budding (TB), as this is a proven prognostic biomarker. We explored the application of deep learning techniques to detect TB in Hematoxylin and Eosin (H&E) stained slides, and used convolutional neural networks to classify image patches as containing tumor buds, tumor glands and background. As a reference standard for training we stained slides both with H&E and immunohistochemistry (IHC), where one pathologist first annotated buds in IHC and then transferred the obtained annotations to the corresponding H&E image. We show the effectiveness of the proposed three-class approach, which allows to substantially reduce the amount of false positives, especially when combined with a hard-negative mining technique. Finally we report the results of an observer study aimed at investigating the correlation between pathologists at detecting TB in IHC and H&E.

Keywords

Deep learning Computational pathology Colorectal carcinoma Tumor budding 

Notes

Acknowledgement

This project was funded by a research grant from the Dutch Cancer Society, project number 10602/2016-2. The authors would like to thank Irene Otte-Holler and Rob van de Loo for staining and scanning the WSI’s.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • John-Melle Bokhorst
    • 1
    • 2
  • Lucia Rijstenberg
    • 2
  • Danny Goudkade
    • 3
  • Iris Nagtegaal
    • 2
  • Jeroen van der Laak
    • 1
    • 2
  • Francesco Ciompi
    • 1
    • 2
  1. 1.Diagnostic Image Analysis GroupRadboud University Medical CenterNijmegenNetherlands
  2. 2.Department of PathologyRadboud University Medical CenterNijmegenNetherlands
  3. 3.Department of PathologyMaastricht University Medical CenterMaastrichtNetherlands

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