Curation of Medical Image Data using lnteractive Learning
Stefan Denner (Ph.D. Student)
Artificial intelligence (Al)'s potential applications in medical imaging are vast and significant. One of the chief obstacles to the development and clinical implementation of Al algorithms is the availability of sufficiently large, curated, and representative training data based on expert labeling. Collecting such curated data requires many hours of manual work but is crucial for downstream model performances. Within my PhD, we investigate human-centered machine learning methods enabling physicians to curate high-quality datasets. Our goal is to support physicians in this process by understanding the dataset's limitations and suggesting new samples leading to a more representative and robust dataset. Therefore, we leverage similarity and representation learning methods in an interactive learning approach.
|Primary Host:||Klaus Maier-Hein (German Cancer Research Center & University of Heidelberg)|
|Exchange Host:||Mihaela van der Schaar (University of Cambridge, The Alan Turing Institute & University of California)|
|PhD Duration:||20 April 2022 - 19 April 2025|
|Exchange Duration:||01 February 2023 - 28 February 2023 01 June 2023 - 30 June 2023|