Bram van Ginneken

Bram van Ginneken was born in Nuenen in 1970. He studied Physics at Eindhoven University of Technology and Utrecht University. In 2001, he obtained his PhD at the Image Sciences Institute on Computer-Aided Diagnosis in Chest Radiography, where he continued to work and set up a research group on medical image analysis. His PhD research on automated detection of tuberculosis resulted in medical device software called CAD4TB. With installations in over 75 countries worldwide, CAD4TB is the most widely used autonomous AI solution for the interpretation of medical images. In 2010, he moved to Radboud University Medical Center where he set up the Diagnostic Image Analysis Group and was appointed full professor in 2012. He (co-)authored over 300 publications in international journals. Since 2010, he also works for the Fraunhofer Institute for Digital Medicine MEVIS in Bremen, Germany. In 2014, he founded Thirona, a company that develops software for CT lung image analysis. He pioneered the concept of challenges in medical image analysis and created grand-challenge.org. In 2024, he founded Plain Medical, a company that develops AI solutions to reduce the workload of radiologists.

Current research projects:

• AI4Adhesion
• AI4ImageGuidedIntervention
• AI-based Diagnostic Decision Making in Primary Care
• Automated Detection and Grading of Hip Osteoartritis
• BabyChecker: AI for low-cost prenatal ultrasound
• Deep PCA
• Fracture detection in hand radiographs
• Automated Detection of Developmental Hip Dysplasia
• MRI-based decision support tool for patients with chronic lower back pain
• Building multi-modal interactive health records
• Oncology
• PARADIGM: The diagnostic potential of 3D ultrasound with AI in maternity care
• Automatic quantification of traumatic brain injuries
• ULS23
• Development and validation of a deep-learning system for wisdom tooth removal

Finished research projects:

• Natural language processing of radiology reports for lesion detection
• Automated AAA detection on CT scans
• AI for Radiology
• AMI
• Body composition assessment in 3D CT and MR images
• Few-shot learning for medical image segmentation
• Image Analysis in Acute Stroke
• AI-driven incidental lung nodule analysis
• Robust identification of the L3 vertebra
• Artificial intelligence for lung cancer screening
• MistraL: Mitigation Strategies for COVID-19 transmission in Lesotho Using AI on Chest X-rays and Novel Rapid Diagnostic Tests
• Machine Learning in Acute Care: Liver & Spleen
• Detecting and characterizing vertebral fractures in CT scans

Software:

• Automated Gleason Grading
• CIRRUS Lung Screening
• Grand-challenge.org
• Pulmonary Nodule Malignancy Prediction

Member of:

• Diagnostic Image Analysis Group
• CARA Lab