Practical Course:
Machine Learning in Medical Imaging
Nassir Navab, Diana Mateus, Loic Peter, Sebastian Poelsterl, Pierre Chatelain
Type: Master Practical Course
Module IN2106
SWS: 6
ECTS: 10 Credits
Location: MI 03.13.010
Time: Wednesday 10:30-12:00
Course Language: English
Announcements
- For the final presentation each group will have max 7 minutes + 3 minutes for questions
- Reports are to be handled latest on the 31st of July by email to your supervisor. No extensions will be given
- Second information meeting will take place in seminar room 03.13.010, on Wednesday the 10th of April at 11:00
- Shifting the schedule to 10:30-12:00
- First information meeting will take place in seminar room 03.13.010, on Wednesday the 6th of February at 13:30
About the Course
In this course students will learn through practice the application of different machine learning methods to problems involving medical images. The Master-Praktikum will consist in:
- (1) a few introductory lectures on machine learning and its application in different problems involving medical imaging,
- (2) a number of exercises to apply different learning approaches to toy example data,
- (3) a machine learning project with a real medical application to be solved in groups (pairs).
Regular meetings will be held individually with each group to follow up the progress of the project along the semester
Evaluation
- Homework attestations (20%)
- Practical implementation of the project (50%)
- Midterm (5%) and final (15%) Presentations:Use the CAMP templates for PowerPoint CAMPmaster.pot, or Latex: CAMP-latex-template.zip.
- Report (10%): Maximum 8 pages. Please download and use the llncs2e.zip Latex template.
Registration
- Please register through TUMOnline.
- Maximum number of participants: 16.
Requirements
- Basic knowledge in MATLAB and C/C++ programming is an advantage.
Preliminary Schedule
Project assignments
