Fraunhofer Institute for Digital Medicine MEVIS
Fraunhofer Institute for Digital Medicine MEVIS

Experts from Fraunhofer MEVIS develop digital solutions to cope with the consequences of the COVID-19 pandemic. Our goal is to empower users in clinics and health departments with AI-based image analysis and statistical modeling to make daily challenges caused by COVID-19 manageable.

Fraunhofer MEVIS vs. CORONA

© Fraunhofer MEVIS

COVID-19 Imaging Platform

Computed tomography (CT) plays an important role in the diagnosis and therapy decisions for COVID-19 patients. In the context of FRAUNHOFER VS. CORONA, we have developed an image analysis platform for lung CTs. This includes an efficient integration of image viewing, AI-based segmentation, manual annotation, and structured analysis.

In the multi-institute COMING project, we worked with Fraunhofer IGD and IOSB, who focused on ultrasound image data analysis.

 

ACT-X

Chest X-ray imaging is an inexpensive and widely available imaging technique for diagnosing and monitoring the chest wall, heart, and lungs. What radiography lacks in comparison to CT in terms of image quality, it makes up in wide availability, small radiation dose, and fast and easy emergency diagnosis, even directly in the ICU. In collaboration with clinical experts at Charité Berlin, MEVIS is developing AI-powered tools to assist radiologists in diagnosis, staging, and monitoring of COVID-19-induced lung disease in chest X-ray images.

 

RACOON

The COVID-19 Pandemic Radiological Cooperative Network RACOON is a joint project of the radiology departments at all 36 German university hospitals. Experts at all sites segment and annotate a large number of lung CT scans in a structured and uniform manner. The resulting data is used to develop medical assistance systems and an early warning system based on AI. Fraunhofer MEVIS is one of the three technical partners in RACOON, in addition to the German Cancer Research Center (DKFZ) and the Technical University of Darmstadt.

 

CO-RADS score on Grand Challenge

Together with the Diagnostic Image Analysis Group (Radboud University, Nijmegen), Amsterdam University Medical Center, and Thirona, we developed an automatic classification for the level of suspicion of COVID-19 infection (CO-RADS score). The algorithm analyzes non-contrast CT scans.



CorASiV

The goal of the CorASiV project External Link within the Fraunhofer-Anti-Corona External Link program is to support local health departments in Germany that are challenged by the COVID-19 pandemic. To this end, six Fraunhofer institutes jointly develop and supply custom data analysis, simulation, and visualization solutions. Fraunhofer MEVIS, in close collaboration with Fraunhofer ITWM External Link and the health department in Berlin-Reinickendorf, developed a web application for data visualization and statistical risk modeling. Primary use cases include understanding of infection chains and supporting group quarantine decisions.

© Fraunhofer MEVIS

INDAST/COPERIMOplus

The Intelligent DataSteward - AI and a modern web interface support and consolidate curation, mapping, and quality assessment of heterogeneous clinical and study data. Automated process control, targeted annotations, and focused interaction prepare the big data approach for meaningful and personalized data modeling and risk analysis.

 

NFDI4Health TaskForce

The NFDI4Health project consists of an interdisciplinary team of 18 partners that aim to make structured health data visible and usable for research. Data quality and the protection of personal data play important roles. From this project, a COVID-19 task force was formed to strengthen cooperative medical public health research and to fight the pandemic with relevant research results.

 

Fraunhofer vs. CORONA at HHIS2020

Due to the pandemic, this year's Hamburg Innovation Summit (HHIS2020) took place digitally. During the "Fraunhofer vs. CORONA" webinar, three institutes (IAPT, IME, and MEVIS) presented and discussed their current research against the pandemic. We were pleased to be part of the discussion with the contribution  entitled "What role do radiological images play in COVID-19?”