Esimation of radiation exposure
Thesis by: Nicola Leucht
Advisor:
Prof. Dr. Nassir Navab
Supervision by:
Pascal Fallavollita;
Patrick Wucherer;
Séverine Habert
Abstract
In the last decade the use of interventional X-ray imaging, especially for fluoroscopy-guided procedures, has increased dramatically. Therefore the radiation exposure of the surgeons has also increased. Although radiation protection measures such as lead vests are used there are still unprotected regions, most notably the hands and the head. Over time these regions can receive significant amounts of radiation.
Within this project a system is developed for approximating the radiation exposure of the physicians' hands during surgery. The goal is to sensibilize physicians to their radiation exposure and to give them a feedback tool.
The objective of the project is to estimate the radiation dose the hands of the surgeon receive.
Using machine learing algorithms and the GEANT4 simulation framework the radiation dose is predicted.
The hardware setup consists of a mobile C-arm/surgical simulator with multimodal sensors.
The sensors are capable of recording depth and rgb values. Based on these values the hands of the surgeons are detected. Knowing the position of the surgeons hands enables the predicition of the applied radiation.
Resources
Literature
- [Ladikos2010] A. Ladikos, C. Cagniart, R. Gothbi, M. Reiser, N. Navab, "Estimating Radiation Exposure in Interventional Environments", Medical Image Computing and Computer-Assisted Intervention (MICCAI), September 2010 , Beijing, China
- [Pauly2014] O. Pauly, B. Diotte, S. Habert, S. Weidert, E. Euler, P. Fallavollita, N. Navab, "Visualization inside the operating room: 'Learning' what the surgeon wants to see", The 5th International Conference on Information Processing in Computer-Assisted Interventions (IPCAI)