Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Practical Course:
Machine Learning in Medical Imaging

Prof. Nassir Navab, Dr. Shahrooz Faghih Roohi, Dr. Seong Tae Kim, Ashkan Khakzar, Azade Farshad

Type: Master Practical Course Module IN2106
SWS: 6
ECTS: 10 Credits
Location: TBA (Due to the pandemic situation we will potentially have lectures online.)
Time: Thursdays, 16-18
Course Language: English


  • 16-07-2020: Please submit your application here. You also have to register via matching system. Using our application form is not mandatory, but it will help you get a higher ranking in the matching system from our side.
  • 30-06-2020: Preliminary meeting: Thursday, 16.07.2020 (16:00-16:30) in virtual meeting room (zoom). Zoom access information is announced in Moodle
  • 30-06-2020: Contact information-If you have any question for this seminar, please feel free to contact Dr. Seong Tae Kim (seongtae.kim@tum.de)
  • 30-06-2020: Website is up!

About the Course

The aim of the course is to provide the students with notions about various machine learning techniques. The course is subdivided into a lecture/excercises block and a project.

  • The lectures will include topics in image processing and analysis, unsupervised methods, and supervised methods. Each lecture will be followed by a practical hands-on exercise (e.g. the implementation in Python).
  • The topics of the projects will be distributed at the beginning of the semester. Each topic will be supervised by a different person. The projects are to be realized by couples. The programming language for the projects is to be decided in agreement with your supervisor.


  • Students can only register through TUM Matching Platform themselves if the maximum number of participants hasn't been reached (please pay attention to the Deadlines).
  • Maximum number of participants: 20.
  • Requirements

    • Good knowledge of machine learning methods and terminology: knowledge of the meaning of the words classification, regression, data-set, cross-validation ...
    • Strong knowledge of Python programming language
    • Background in image processing


    • 60% Project Progress (Done by your tutor -- mainly on your weekly progress on lrz git repository)
    • 40% Intermediate and Final Presentation (Done by all tutors -- mainly on your presentation skill, progress so far compared to other groups ...etc.)
    • Presentation: Use the CAMP templates for PowerPoint camp-tum-jhu-slides.zip, or Latex: CAMP-latex-template.


    Please find lecture materials in Moodle

    Date Topic By Slides  
    16.07.2020 Preliminary meeting   Slide  


    ID Project Tutor Group I Group II Material

    Title: Machine Learning in Medical Imaging
    Professor: Prof. Nassir Navab
    Tutors: Dr. Shahrooz Faghih Roohi; Dr. Seong Tae Kim, Ashkan Khakzar, Azade Farshad,
    Type: Praktikum
    Information: 6 SWS, 10 ECTS Credits (Module IN2106)
    Term: 2020WiSe

    Edit | Attach | Refresh | Diffs | More | Revision r1.5 - 16 Jul 2020 - 14:42 - SeongTaeKim

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