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Computer Aided Medical Procedures II

Module IN2022

This Module is offered by TUM Department of Informatics.

This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.

Basic Information

IN2022 is a semester module in English language at Master’s level which is offered in summer semester.

This Module is included in the following catalogues within the study programs in physics.

  • Catalogue of non-physics elective courses
Total workloadContact hoursCredits (ECTS)
150 h 60 h 5 CP

Content, Learning Outcome and Preconditions


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

Folgende Inhalte werden beispielhaft behandelt und ggf. durch industrielle oder klinische Fallstudien von Experten lokaler Kliniken und medizintechnischer Firmen ergänzt:
- Image Processing
++ Spatial-domain filtering
++ Frequency-domain filtering
++ Image transformations
- Image Segmentation
++ Pixel-based methods
++ Graph-based methods and graphical models
++ Variational methods
- Bildregistrierung
++ Intensity- and landmark-based methods
++ inter-/intra-patient and inter-/intra-modality registration
++ Graph-based methods and graphical models
++ Variational methods
- Fundamentals of Machine Learning
++ Clustering
++ Principal Component Analysis
- Fundamentals of 3D Volume Visualization
++ Physical foundations
++ Overview over different rendering techniques

These topics are augmented by invited talks of clinical or industrial experts.

Exercises where participants have to implement and apply respective algorithms to given problems provide the possibility of gaining a deeper insight and understanding.

Learning Outcome

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 or pre-diploma in informatics or another scientific or technological course of studies

Courses, Learning and Teaching Methods and Literature

Courses and Schedule

VI 4 Computer Aided Medical Procedures II (IN2022) Eck, U. Kim, S. Navab, N. Wed, 12:30–14:00, MI 03.13.010
Thu, 14:30–16:00, MI 03.13.010

Learning and Teaching Methods

Lecture, exercises, programming exercises for individual study


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

Module Exam

Description of exams and course work

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.

Exam Repetition

The exam may be repeated at the end of the semester.

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