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We have modelled the changes in elemental composition of brain tissue in different phases of an ischemic stroke. Influence of a number of factors on the absolute Hounsfield units is investigated as possible causes of intra- and interpatient variation. The modeled pathological changes are included in different software brain models. Subsequently we have simulated X-ray images of these brain models acquired by dual energy Cone Beam Computed Tomography (CBCT). Our modelling is based on a combination of analytical and Monte-Carlo methods. As an example of spectral processing virtual monoenergetic images are reconstructed from the simulated projections.
Simulated images are intended to optimize acquisition parameters for clinical studies beforehand and to develop new image processing algorithms to enhance the diagnostic value. As example a water map is calculated to better visualize the formation of an edema after ischemic stroke.
For helical CT scans with a pitch smaller or equal to one the redundancy in the helical projection data can be used to generate images at the identical spatial position for multiple time points. As the scanner moves across the thorax during the scan, these images do not have a fixed time point, but a well-defined temporal distance inbetween the images. Using image based registration a motion vector field can be estimated based on these images. The motion artefacts are corrected in a subsequent motion compensated reconstruction. The method is tested on mathematical phantom data (reconstruction) and clinical lung scans (motion estimation and reconstruction).
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