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Department of Radiology Research

Welcome to the research website of the Department of Radiology at Radboud University Nijmegen Medical Centre.

Research at the Department of Radiology has a strong focus on early detection and early treatment of common diseases. It covers fundamental research on a molecular level, development of new medical devices and software tools, and translates these results to clinical applications that can be used in daily routine. Our mission is to bridge the gap between research and practice and to help shape the future of healthcare. We use technology to make healthcare more affordable by increasing automation of diagnostic and therapeutic procedures, thus freeing manpower for those areas in patient care in which the "human touch" is most needed.

The three fundamental science groups cover ultrasound (MUSIC), biomedical MR (BioMR) and diagnostic image analysis (DIAG). Clinical research is mainly focused on prostate, breast, chest and vascular disease.

With the menu on the right you can learn more about our researchers, view or download publications or navigate to any of the research groups within the Department of Radiology.

Highlight

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Lung cancer, by far the most deadly cancer worldwide, usually becomes symptomatic only when it is already advanced. With low dose CT scanning, lung cancer can be detected in an early stage, when it can still be treated successfully. Bram van Ginneken has been awarded a 1.5 million Euro VICI grant, in the NWO Vernieuwingsimpuls programme, for his proposal Lung CT Screening: More for Less. The goal of this project is to automate the reading of lung screening CT scans as much as possible, using computer detection algorithms and automatic volumetric segmentation of lung nodules, as illustrated above for one lung nodule that grows over a period of three years. From this analysis the probability that a suspicious lesions represents lung cancer can be accurately estimated and appropriate work up for the patient can be determined. We will also develop an automatic computer algorithm to estimate risk for cardiovascular and chronic obstructive lung disease from lung CT screening scans. All this information can be combined by an expert system to make a personal recommendation for the screening interval: not everybody needs a yearly CT. In this way we hope it will be possible to make screening both more effective and less costly.

See more in the Highlight Archive.

News

For older news, see the News Archive.