Thomas van den Heuvel

Thomas van den Heuvel is a postdoc in the Diagnostic Image Analysis Group and the Medical Ultrasound Imaging Centre. His work is part of the POCUS-AI research line in which he combines Point-of-care ultrasound (POCUS) with artificial intelligence. His main focus is development of software for automated detection of maternal risk factors in resource-limited settings. He is supervised by Chris de Korte and Bram van Ginneken.

Thomas studied Biomedical Engineering at Eindhoven University of Technology (TU/e). During his studies he participated in the Honors Program of the TU/e and did an internship at Yale University. In January 2019, he obtained his PhD degree from the Radboud University in Nijmegen, the Netherlands.

Current research projects:

• BabyChecker: AI for low-cost prenatal ultrasound
• Automated Detection of Developmental Hip Dysplasia

Finished research projects:

• Automated COVID-19 classification using ultrasound

Member of:

• Diagnostic Image Analysis Group