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Seminar Intraoperative Imaging and Machine Learning (IIML)- Lecturers
- Prof. Dr.-Ing. Katharina Breininger, Dr.-Ing. Holger Kunze
- Details
- Seminar
Online/Präsenz
2 cred.h, ECTS studies, ECTS credits: 5, Sprache Englisch, This course will be held in a hybrid format. The first session (Oct. 20) will be via Zoom, further details will be shared at the beginning of the seminar. Please register for this course via StudOn.
Time and place: Wed 8:30 - 10:00, Hörsaal ZMPT; comments on time and place: The on-premise part of the seminar will be held in ZMPT (Henkestraße). The first session (Oct. 20) will be via Zoom, further details will be shared at the beginning of the seminar.
- Fields of study
- WPF MT-MA-BDV ab 1
WPF INF-MA ab 1
WPF ICT-MA ab 1
WPF CE-MA-INF ab 1
- Contents
- For many applications, techniques like deep learning allow for considerably faster algorithm development and allow to automate tasks that were performed manually in the past. In medical imaging, a large variety of time-consuming tasks that interfere with clinical workflows has the potential for automation. However, at the same time new challenges arise like data privacy regulations and ethics concerns.
In this seminar, we want to develop an application that allows for the automation of an X-ray based intraoperative planning or measurement procedure from a holistic perspective. To this end, we will invite a surgeon to explain the medical background and visit the operating room to understand the surgeons’ needs while performing the task. Having understood the underlying medical problem, we will look into topics of data privacy, code of ethics, prototype development, and UI design for surgeons. Furthermore, we will touch regulatory requirements necessary for releasing software to clinics.
At the end of the seminar, the students will have developed and documented a prototypical application for the indented intraoperative use case.
Students will be able to
visit an operation room, following the rules of such an environment
perform their own literature research on a given subject
independently research this subject according to data privacy and ethical standard
present and introduce the subject to their student peers
give a scientific talk in English according to international conference standards
describe their results in a scientific report
- ECTS information:
- Credits: 5
- Additional information
- Expected participants: 10, Maximale Teilnehmerzahl: 15
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2021/2022:
- Biomedizin und Hauptseminar Medizintechnik (BuHSMT)
- Seminar Intraoperative Imaging and Machine Learning (IIML)
- Department: Juniorprofessur für Artificial Intelligence in Medical Imaging
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