Informatikanwendungen in der Medizin II

What it is about

You will learn advanced methods of medical image processing, segmentation and registration as well as the fundamentals of machine learning and 3D volume visualization. In the end you will be able to distinguish the most important algorithm types, assess when they are applied, implement central procedures in Python, and apply them to clinical questions.

What you will be able to do

• Understand the fundamentals and application areas of advanced image processing algorithms
• Explain differences between procedures for image filtering, segmentation and registration
• Implement algorithms for image processing, segmentation and registration in Python
• Understand the fundamentals of machine learning (clustering, principal component analysis)
• Know methods for 3D volume visualization and their physical foundations
• Analyse challenging tasks in computer-assisted diagnosis and intervention and develop solution approaches

What the module consists of

• VorlesungConveying the subject foundations and algorithms
• TutorübungDiscussion of weekly tasks and deepening
• Selbststudium (Aufgaben)Practical exercises for implementation and application to real problems
• GastvorlesungenInsights into industrial/clinical case studies linked to clinical application

Teaching method

• VorlesungIntroduction to theory and algorithms
• TutorübungDiscussion and model solutions to exercises for deepening understanding
• Aufgaben zum SelbststudiumImplementations and applications for practical experience and self-assessment
• Gastvorlesungen von Kliniken/UnternehmenEstablishing the link to clinical and industrial practice