Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries (Ait4Surgery)
Third party funded individual grant
Acronym: Ait4Surgery
Start date : 01.06.2018
End date : 31.05.2021
Project details
Scientific Abstract
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.
Involved:
Andreas Maier
Project Leader
Björn Eskofier
Project Leader
Rebecca Fahrig
Project Member
Peter Blank
Project Member
Prathmesh Madhu
Project Member
Jennifer Maier
Project Member
Julia Schottenhamml
Project Member
Contributing FAU Organisations:
Lehrstuhl für Informatik 5 (Mustererkennung)
Machine Learning and Data Analytics Lab
Technische Fakultät
Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics)
