Module CS4371-KP08, CS4371
Advanced Techniques of Medical Image Processing (FVMB)
Duration
1 Semester
Turnus of offer
each winter semester
Credit points
8
Course of studies, specific fields and terms:
- Master MES 2020, optional subject, medical engineering science
- Master Medical Informatics 2019, advanced module, medical computer science
- Master MES 2014, optional subject, medical engineering science
- Master Medical Informatics 2014, optional subject, medical image processing
Classes and lectures:
- Advanced Techniques of Medical Image Processing (lecture, 3 SWS)
- Advanced Techniques of Medical Image Processing (exercise, 2 SWS)
- Advanced Techniques of Medical Image Processing (practical course, 1 SWS)
Workload:
- 60 hours private studies and exercises
- 60 hours private studies
- 90 hours in-classroom work
- 30 hours exam preparation
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 transfer mathematical concepts into practical algorithms for medical image processing.
- They can proficiently implement these concepts in C++.
- 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:
- Oral examination
Responsible for this module:
Literature:
- M. Sonka, V. Hlavac, R. Boyle : Image Processing, Analysis and Machine Vision 2nd edition. Pacific Grove: PWS Publishing 1998
Language:
- offered only in German
Notes:
Admission requirements for taking the module:- None (the competences of the modules mentioned under ''requires'' are needed for this module, but are not a formal prerequisite).
Admission requirements for taking module examination(s):
- Successful completion of exercise assignments and programming tasks as specified at the beginning of the semester.
Module Exam(s):
- CS4371-L1: Advanced Methods in Medical Image Processing, oral examination.
This module replaces the module of the same name CS4370, which is no longer offered.
Last Updated:
24.09.2021