Module CS4370-KP04, CS4370
Advanced Techniques of Medical Image Processing (FVMB2014)
Duration
1 Semester
Turnus of offer
not available anymore
Credit points
4
Course of studies, specific fields and terms:
- Master Medical Informatics 2014, optional subject, medical image processing
Classes and lectures:
- Advanced Techniques of Medical Image Processing (exercise, 1 SWS)
- Advanced Techniques of Medical Image Processing (lecture, 2 SWS)
Workload:
- 20 hours exam preparation
- 45 hours in-classroom work
- 55 hours private studies
Contents of teaching:
- Applications of medical image processing techniques
- Image superresolution
- Denoising and inhomogeneity correction
- Linear and non-linear dimensionality reduction
- Patch-based image processing and non-local means
- Fusion of (probabilistic) segmentations (NLM and STAPLE)
- Random-walk algorithm for interactive segmentation
- Non-linear registration and motion estimation (optical flow)
- Similarity metrics for multi-modal fusion
- Introduction into graphical models and discrete optimisation
- Viterbi algorithm and message passing (stereo depth estimation)
- Graph cut segmentation and further applications
- Extraction image features and descriptors
- Matching of corresponding landmarks
Qualification-goals/Competencies:
- Students know a wide range of methods for segmentation, registration and processing of medical images.
- They can describe these methods with correct technical terminology.
- They can transfer image processing techniques into energy minimisation problems.
- They can solve minimisation problems using sparse linear systems.
- They understand methodological relations between different applications and techniques.
- They understand the transfer of continuous problems into the discrete domain.
- They understand solvers for discrete optimisation problems.
- They can compare different algorithms to another and make suitable problem-related choices of methods.
- They have an extended overview of application areas for medical image analysis.
Grading through:
- Written or oral exam as announced by the examiner
Responsible for this module:
Literature:
- H. Handels : Medizinische Bildverarbeitung Stuttgart: Vieweg &Teubner 2009
- M. Sonka, V. Hlavac, R. Boyle : Image Processing, Analysis and Machine Vision 2nd edition. Pacific Grove: PWS Publishing 1998
Language:
- offered only in German
Last Updated:
17.07.2019