Seminar Intraoperative Imaging and Machine Learning [IIML] WiSe21/22 2021/2022 /KursID:2791
- Letzter Beitrag vom 2021-11-03

Einrichtung

Friedrich-Alexander-Universität Erlangen-Nürnberg

Aufzeichnungsart

Vorlesungsreihe

Sprache

Lecturers:
Prof. Katharina Breininger, Dr.-Ing Holger Kunze, Dr. med. Holger Keil
 

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.

Zugehörige Einzelbeiträge

Folge
Titel
Lehrende(r)
Aktualisiert
Zugang
Dauer
Medien
1
AI Algorithms for X-Ray Analysis
Prof. Eva Katharina Breininger
2021-10-27
IdM-Anmeldung
01:20:54
2
Medical Background: Distal Humerus
Prof. Eva Katharina Breininger
2021-11-03
IdM-Anmeldung
00:59:39

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