Self-Supervised Learning for Annotation Efficient Biomedical Image Segmentation.

Journal: IEEE transactions on bio-medical engineering
PMID:

Abstract

OBJECTIVE: The scarcity of high-quality annotated data is omnipresent in machine learning. Especially in biomedical segmentation applications, experts need to spend a lot of their time into annotating due to the complexity. Hence, methods to reduce such efforts are desired.

Authors

  • Luca Rettenberger
  • Marcel Schilling
  • Stefan Elser
  • Moritz Böhland
    Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany.
  • Markus Reischl
    Institut für Automation und angewandte Informatik, Karlsruher Institut für Technologie, Eggenstein-Leopoldshafen.