Medical Image Computing

Syllabus

  • Week 2 and 3
    • Lecture (week 2): Introduction to medical image computing
      • Medical imaging modalities
      • Basics of volume visualisation
      • Introduction to medical image analysis
    • Tutorial (week 3): Medical image analysis
  • Week 4 and 5
    • Lecture (week 4): Image registration
      • Transformation models
      • Similarity measures
      • Point-based registration
      • Intensity-based registration
      • Applications
    • Tutorial (week 5): Intensity-based registration and similarity measures
  • Week 6 and 7
    • Lecture (week 6): Medical image segmentation
      • Intensity-based segmentation
      • Model-based segmentation
      • Shape and appearance models
    • Tutorial (week 7): EM-based segmentation of MR images
  • Week 8 and 9
    • Lecture (week 8): Machine learning for medical imaging
      • supervised vs unsupervised learning
      • classification vs regression
      • SVMs, Random Forests, Neural Nets
    • Tutorial (week 9): Regression and classification with different methods, cross-validation

All course material is available via CATE.