Instructors: Prof. Dr. Nassir Navab, Dr. Shahrooz Faghihroohi, Azade Farshad, Yousef Yeganeh

Registration

• Registration must be done through TUM Matching Platform (please pay attention to the Deadlines)
• In order to increase your priority, please also apply via our own Registration system.
• The maximum number of participants: 20-24.

Announcements

• The preliminary meeting slides can be found here: 
• The preliminary meeting is scheduled for Feb 2nd, 10:00 (Zoom link is visible on TUMonline in the course description).
• ُُThe mid- and final presentations happen in hybrid form (the meeting info will be shared with participants via email).

Introduction

• The aim of the course is to provide the students with notions about various machine learning techniques. The course is subdivided into a lecture block and a project.
  • The lectures will include DL topics relevant to medical imaging applications. 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.

Course Structure

In this Master Praktikum (Hauptseminar), the grading is divided as follows: 

• Presentation: 50% Intermediate and Final Presentation (Done by all tutors -- mainly on your presentation skill, progress so far compared to other groups ...etc.)
  • Use the CAMP templates for PowerPoint camp-tum-jhu-slides.zip
  • The guideline for mid-presentation can be found here: Guideline for intermediate presentation (SS2023 MLMI).pdf
  • The guideline for the final presentation can be found here: GuidelineMLMI_Final presentation_SS23.pdf
• Project Progress: 50% Project Progress (Done by your tutor -- mainly on your weekly progress on lrz git repository.

Schedule of Lectures

Proposed Projects