Machine Learning for Medical Image Analysis (Seminar)
|Course title:||Machine Learning for Medical Image Analysis|
|Lecturers:||Dr. Lisa Koch, Dr. Christian Baumgartner|
|Teaching assistants:||to be announced|
|Venue:||to be announced|
The seminar starts with an introductory lecture to provide a compact overview of the research field (machine learning for medical image analysis), as well as a tutorial on critical analysis and presentation of research papers. Throughout the remainder of the course, each student presents a paper from a collection of seminal work in the field. Strong emphasis will be put on an engaging group discussion of the paper.
The learning objectives of this seminar consist of three parts: (1) the students will gain a solid understanding of key contributions to the field of machine learning for medical image analysis, (2) the students learn to critically read and analyse original research papers and judge their impact, and (3) the students will improve their scientific communication skills with an oral presentation and participation in discussions sessions.
- 15.9.: Website is online
Each student chooses one paper from the provided collection to present during the course of the seminar. The students may get support in the preparation of their presentation by the seminar assistants. Everybody is encouraged to read each paper before it is being presented and engage in a discussion following the presentations. To foster interesting discussions, each paper will also be assigned two “critics” who study the paper and prepare questions for the discussion. Each student will be graded based on both their presentation (80%) and their participation in the assigned discussions (20%). Attendance is required to pass the course (3 absences allowed).
Slides for the introductory lecture will be uploaded
Schedule and List of Papers
Schedule and selection of discussed papers will be announced shortly