Using Anatomical and Physiological Constraints in Machine Learning for Medical Image Processing

Event Details
Date: 02.05.2023, 17:30 o'clock - 18:30 o'clock 
Location: N2045, Universitätsstraße 1, 86159 Augsburg
Organizer(s): Lehrstuhl für Biomedizinische Informatik, Data Mining und Data Analytics
Topics: Informatik, Gesundheit und Medizin
Series of events: Medical Information Sciences
Event Type: Vortragsreihe
Speaker(s): Dr. Thomas Wendler Vidal
BIOINF ASFDASDF DSFASF ASDF ASDF © University of Augsburg

In diesem Sommersemester wird die im letzten Winter erfolgreich gestartete Vortragsreihe Medical Information Sciences fortgesetzt. Renommierte Wissenschaftlerinnen und Wissenschaftler unterschiedlicher Fachdisziplinen und Forschungsstandorte geben jeden Dienstag ab 17:30 Uhr Einblicke in aktuelle Fragestellungen und Anwendungsgebiete des breiten Forschungsfeldes Medical Information Sciences.


Since the early 2010s, (deep) artificial neural networks started to flood the medical publication landscape, in particular in the fields of radiology, nuclear medicine and radiation oncology, by showing promising results in various tasks such as disease detection, outcome prediction, and therapy planning. Despite excellent reported performances, the deployment of such tools in clinical routine has been slower than expected due to the large variability in medical images. Physics-informed machine learning has been proposed to increase robustness and improve the generalization of deep learning models. An extension of this concept in medical informatics is anatomy- and physiology-informed machine learning. In the frame of the "Medical Information Sciences" lecture series, we present here different projects hosted at the Chair for Computer-Aided Medical Procedures at Technical University of Munich, where we use high-level knowledge of anatomy and physiology to constrain and regularize machine learning models, and as such, produce more robust medical image analysis tools.

Kurzbiographie:
Dr. Thomas Wendler is an Electronic Engineer (Technical University Federico Santa María, Valparaíso, 2004) with a Master of Science in Medical Technolgy (Technical University of Munich, 2007) and a Ph.D. in Computer Science (Technical University of Munich, 2010). After 9 years as CTO and CEO of medical device companies (SurgicEye GmbH, OncoBeta GmbH, ScintHealth GmbH), Dr. Wendler rejoined the Chair for Computer Aided Medical Procedures at Technical University of Munich as group leader at the Interdisciplinary Research Lab at Klinikum rechts der Isar. Dr. Wendler coordinates there the activities of the chair in the fields of Medical Image Processing and Robotic Ultrasound, as well as partnerships with the university hospital in the fields of Machine Learning and Computer-Aided Surgery. Dr. Wendler has authored >40 peer reviewed, has written two book chapters and has been granted 10 patent families (EU, US, DE). He is also currently the Vice-Chair of the Working Group for Digitalization and Artificial Intelligence at the German Society of Nuclear Medicine, and Comunication Officer of the Translational Molecular Imaging and Therapy Committee at the European Association of Nuclear Medicine.

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