Computer Aided Medical Procedures II

The following contents will be covered as examples and, where appropriate, supplemented by industrial or clinical case studies by experts from local clinics and medical technology companies:
- Image processing
++ Image filtering in the local domain
++ Image filtering in the frequency domain
++ Image transformations
- Image segmentation
++ Pixel-based methods
++ Graph-based methods and graphical models
++ Variation methods
- Image registration
++ Intensity and landmark-based methods
++ Registration of inter/intra patient data and inter/intra modalities
++ Graph-based methods and graphical models
++ Variation methods
- Basics of Machine Learning
++ Clustering
++ Principal Component Analysis
- Fundamentals of 3D Volume Visualization
++ Physical Basics
++ Overview of rendering techniques

In the exercises, there is the possibility for the participants to gain a deeper understanding and practical experience in the implementation or application of the methods to solve real problems.

Upon successful completion of the module participants are able to understand the fundamentals, differences, and application areas of advanced methods for image processing, image segmentation and image registration as well as are able to implement them in MATLAB. Moreover, participants are able to understand the fundamentals of machine learning and 3D volume visualization. Furthermore, participants are able to understand complex problems in the area of computer aided diagnosis and interventions as well as to develop solution strategies based on the covered algorithms in the aforementioned areas.

IN2021 Computer Aided Medical Procedures, Bachelor in informatics or another scientific or technological course of studies.

Attendance of the lecture IN2021 (Computer Aided Medical Procedures) is beneficial but not mandatory.

Lecture, tutorial, problems for individual study. Guest lectures will be held by experts from local hospitals and med-tech companies to ensure that the covered topics are relevant for clinical practice. The assignments are provided on a weekly basis via the teaching portal. They are discussed in the next tutorial class, and a solution is presented. Work on the assignments and participation in the tutorial class are voluntary. They serve as a means for students to deepen and test their acquired knowledge – as a self-monitoring aid to prepare for the written exam.

Slide show, blackboard, programming exercises

[Peters2000] Terry M. Peters: Image-guided surgery: From X-rays to Virtual Reality. Comput Methods Biomech Biomed Engin, 4(1):27-57, 2000
[MICCAI] Various Proceedings of MICCAI (International Society and Conference Series on Medical Image Computing and Computer-Assisted Intervention)
[TMI] Various IEEE Transactions on Medical Imaging

Type of Assessment: exam

The exam takes the form of a written test. The duration is 90 minutes and no material is allowed (closed book). Questions assess whether the student is able to understand the fundamentals, differences, and application areas of advanced algorithms for medical image processing and computer aided surgery.
Small case studies assess whether the student is able to select an appropriate algorithm for a given task or to assess the application of an algorithms as well as its outcome for a given application, respectively.