Geert Van Eyndhoven

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X-ray computed tomography (CT) is a powerful tool for noninvasive imaging of time-varying objects. In the past, methods have been proposed to reconstruct images from continuously changing objects. For discretely or structurally changing objects, however, such methods fail to reconstruct high quality images, mainly because assumptions about continuity are no(More)
The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing, and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique.(More)
If objects or patients move during a CT scan, reconstructions suffer from severe motion artifacts. Time dependent computed to-mography (4DCT) tries to minimize these artifacts by estimating motion and/or reconstruction simultaneously. Most current methods assume a known deformation or a reconstruction without artifacts at a certain time point. This work(More)
X-ray computed tomography (CT) is a powerful tool for non-invasive cardiac imaging. However, radiation dose is a major issue. In this paper, we propose an iterative reconstruction method that reduces the radiation dose without compromising image quality. This is achieved by exploiting prior knowledge in two ways: the reconstructed object is assumed to(More)
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