Practical Course:
Machine Learning in Medical Imaging
Prof. Nassir Navab, Dr. Shahrooz Faghih Roohi,
Ashkan Khakzar,
Azade Farshad, Anees Kazi
Type: Master Practical Course
Module IN2106
SWS: 6
ECTS: 10 Credits
Location: TBA (Due to the pandemic situation we will have lectures online.)
Time: Thursdays, 16-18
Course Language: English
Announcements:
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 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. The projects are to be realized by couples.
Registration
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
- Strong knowledge of deep learning
- Strong knowledge of Python programming language
Evaluation
- 50% Project Progress (Done by your tutor -- mainly on your weekly progress on lrz git repository)
- 50% 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.
Schedule
Please find lecture materials in Moodle
TBA (please have a look at the schedule for the previous semesters)
Projects
TBA (to have an idea of what our projects are about, please have a look at the ones from the previous semesters)
