Computational Surgineering


The course is meant to let students dive deep into the hospital daily routine, as well as, “get their hands dirty” developing solutions which can help clinicians. The students attending this course will prototype a computer-aided solution tailored for clinical needs of our partners in several hospitals within Munich. 
Besides the project development, students can learn about important aspects for building clinical prototypes and get in contact with our clinical partners. The course includes:

  1. Access to lecture videos about important aspects for building clinical prototypes: OR training, Tools and methods for software development for medical image processing and computer-assisted interventions, Introduction to regulatory aspects of medical software development (for students who missed IGS and PMSD lectures)
  2. Visit to OR at the clinical partner’s department 
  3. Preliminary presentation
  4. Project development
  5. Weekly/Bi-weekly reviews with tutors (help with bug fixing, administrative stuff, connection to experts)
  6. Prototype demonstration - ideally presented to the doctors - end of the semester
  • The preliminary meeting is scheduled for Feb 5th, from 17:00 to 17:30, with the following Zoom link:

Preliminary meeting slides: 

Prerequisites and Registration

Experience in programming, in particular Python are needed. Basics of Medical Imaging (e.g., IN2021, IN2022) and Computer Vision are recommended.

  • Registration must be done through TUM Matching Platform (please pay attention to the Deadlines)
  • Your chances to be assigned to the course increase if you give the course a higher rank in your choices.
  • The maximum number of participants: 24.


Students completing this practical course successfully will be able to:

  • Use a subset of common software development tools for medical image processing and computer-assisted interventions
  • Consider regulatory constraints needed to be taken into account when developing medical software
  • Understand the daily clinical routine within one specialty/clinical department
  • Refine a clinical solution for an unmet clinical need to be able to generate a prototype
  • Analyze one clinical application in order to generate a requirement specification for the chosen clinical challenge
  • Develop a clinical prototype (mainly software, if applicable also involving hardware) and demonstrate it on phantoms, ex-vivo, or using retrospective data
  • Present their work in front of an audience of medical technologists and clinicians