Lu currently works on the ZonMw funded project B3CARE cooperated with UMC Groningen as a PhD student at the University of Twente Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). In this project, we analysis low-dose CT images using deep learning to improve the technology readiness level.
Lung cancer, chronic obstructive pulmonary disease (COPD), and cardiovascular disease (CVD), the so-called Big-3 (B3), are expected to cause most deaths by 2050. Early detection and prevention are crucial to lowering the disease burden. Innovative low-dose computed tomography (CT) allows simultaneous, integrated assessment of early imaging biomarkers of lung cancer, COPD and CVD. The aim of this project is to advance the technology readiness level of integrated B3 screening. To reach this objective, B3CARE will develop a large, high-quality imaging data biobank to provide biomarker reference values and validate B3 biomarkers using novel image analysis software and novel machine learning approaches.
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