Brain MR image simulation for deep learning based medical image analysis networks.

Journal: Computer methods and programs in biomedicine
Published Date: Mar 7, 2024

Abstract

BACKGROUND AND OBJECTIVE: As large sets of annotated MRI data are needed for training and validating deep learning based medical image analysis algorithms, the lack of sufficient annotated data is a critical problem. A possible solution is the generation of artificial data by means of physics-based simulations. Existing brain simulation data is limited in terms of anatomical models, tissue classes, fixed tissue characteristics, MR sequences and overall realism.

Authors

  • Aymen Ayaz
    Biomedical Engineering Department, Eindhoven University of Technology, Eindhoven, the Netherlands. Electronic address: a.ayaz@tue.nl.
  • Yasmina Al Khalil
    Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. Electronic address: y.al.khalil@tue.nl.
  • Sina Amirrajab
    Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. Electronic address: s.amirrajab@tue.nl.
  • Cristian Lorenz
    Philips Research Laboratories, Hamburg, Germany. Electronic address: cristian.lorenz@philips.com.
  • Jürgen Weese
    Philips Research Laboratories, Hamburg, Germany.
  • Josien Pluim
  • Marcel Breeuwer
    Department of Biomedical Engineering, Medical Image Analysis group, Eindhoven University of Technology, Eindhoven, The Netherlands.

Keywords

External Resources

Popular Topics
Recent Journals