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
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.
Information meeting: Wednesday 9th October at 11:00 in the room MI 01.06.020
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.
Schedule
Projects
