Full professor at Heidelberg University and managing director of the National Center for Tumor Diseases (NCT) Heidelberg, Germany
Medical Image Synthesis for Data-Centric AI: Lessons Learnt
Data-centric AI provides an innovative, complementary approach to AI modeling by shifting the emphasis from constructing models to the curation of well-designed datasets. Image synthesis has emerged as a pivotal technique in data-centric AI, enabling the generation of training and validation data with perfect ground truth annotations. This capability addresses significant challenges in medical imaging, where obtaining large, annotated datasets is often impractical or impossible.
In this talk, Lena Maier-Hein will share insights gained from a decade of research on image synthesis in the scope of the ERC grants COMBIOSCOPY and NEURAL SPICING. She will delve into crucial questions such as: “How to close the domain gap between real and synthetic data?”, “How to combine real and synthetic data to address distribution shifts?” and “What are the pitfalls of commonly used validation metrics?”. Beyond the successes and methodologies detailed in research publications, this presentation will also highlight the pitfalls and negative results encountered during the research. The primary aim of the talk is to contribute to a more nuanced and practical understanding of medical image synthesis, ultimately fostering more robust and generalizable AI systems in medical imaging.
Lena Maier-Hein is a full professor at Heidelberg University (Germany) and managing director of the National Center for Tumor Diseases (NCT) Heidelberg. At the German Cancer Research Center (DKFZ) she is head of the division Intelligent Medical Systems (IMSY) and managing director of the “Data Science and Digital Oncology” cross-topic program. Her research concentrates on machine learning-based biomedical image analysis with a specific focus on surgical data science, computational biophotonics and validation of machine learning algorithms. She is a fellow of the Medical Image Computing and Computer Assisted Intervention (MICCAI) society and of the European Laboratory for Learning and Intelligent Systems (ELLIS), president of the MICCAI special interest group on challenges and chair of the international surgical data science initiative.
Lena Maier-Hein serves on the editorial board of the journals Nature Scientific Data, IEEE Transactions on Pattern Analysis and Machine Intelligence and Medical Image Analysis. During her academic career, she has been distinguished with several science awards including the 2013 Heinz Maier Leibnitz Award of the German Research Foundation (DFG) and the 2017/18 Berlin-Brandenburg Academy Prize. She has received a European Research Council (ERC) starting grant (2015-2020) and consolidator grant (2021-2026).