Flexible and Adaptive Software-Framework for X-Ray-enabled AI for CoViD-19 detection (FastRAi)

Contact Persons

Dr. Thomas Wendler (wendler@tum.de)


FastRAi aims to develop neural network based applications for X-ray based CoVid-19 diagnosis. The applications are developed using labelled CT data. Neural networks are powerful artificial intelligence models that learn to perform tasks by analyzing training examples. While these methods have shown to be able to perform on par with human doctors for complicated medical diagnosis tasks, such as skin cancer classification, they suffer from a fundamental drawback: The need for large amount of annotated samples required to develop the networks. FastRAI aims to bypass this, by leveraging the TUM’s expertise in simulating artificial X-rays from CT scans. Thereby a large amount of simulated X-rays and corresponding labels can be generated using only a smaller amount of labelled CT scans. These simulated scans can then be used to train neural networks that are able to analyze real scans.

Research Partners

M3i GmbH 

deepc GmbH

Project Members

Matthias Grimm

Magda Paschali

Tobias Czempiel

Matthias Keicher

John Zielke

Ganesh Chandrasekaran

Dr. med. Simon Weidert

Dr. Stefan Taing

Dr. Szilard Szabo

Dr. med. Franz Pfister

Sebastian Byas