Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries

Third party funded individual grant


Project Details

Project leader:
Prof. Dr.-Ing. Andreas Maier
Prof. Dr. Björn Eskofier

Project members:
Jennifer Maier
Julia Schottenhamml
Prathmesh Madhu
Prof. Dr. Rebecca Fahrig
Peter Blank

Contributing FAU Organisations:
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Lehrstuhl für Informatik 5 (Mustererkennung)
Technische Fakultät

Funding source: Bundesministerium für Bildung und Forschung (BMBF)
Acronym: Ait4Surgery
Start date: 01/06/2018
End date: 31/05/2021


Abstract (technical / expert description):

The goal of this project is the investigation of multimodal methods for the evaluation of interventional workflows in the operation room. This topic will be researched in an international project context with partners in Germany and in Brazil (UNISINOS in Porto Alegre). Methods will be developed to analyze the processes in an OR based on signals from body-worn sensors, cameras and other modalities like X-ray images recorded during the surgeries. For data analysis, techniques from the field of computer vision, machine learning and pattern recognition will be applied. The system will be integrated in a way that body-worn sensors developed by Portabiles as well as angiography systems produced by Siemens Healthcare can be included alongside.


Last updated on 2019-11-03 at 11:16