About the research topic
Radiology departments are currently using only a few, generally unrelated artificial intelligence (AI) solutions. The most comprehensive solution currently available for reading chest CTs includes nodules and their surroundings but lacks an important finding - pulmonary embolism (PE). In chest CTs scanned for another reason than PE, it is typically not expected and easily overlooked during routine assessment. With the ever-growing lack of radiologists and backlog, computational analysis yielding timely warning of such critical findings are rapidly gaining importance.
In this project we aim to advance and evaluate an AI software solution for detection of incidental pulmonary embolism (IPE) that is scalable and when added to an existing chest detector covers a comprehensive range of chest CT findings. The detection of IPE will serve as an exemplary use case, beyond which the value of comprehensive AI assessment will be investigated.
Besides BIGR members Martijn Starmans and Erik Kemper, radiologist Jan-Jaap Visser (Erasmus MC),Frans Vos (TU Delft), and Ken Redekop (Erasmus University) are principal investigators in this project. We closely collaborate with the compay contextflow to enable transition of the models to clinical practice.
