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We present a new method for rigid registration of CT datasets in 3D Radon space based on sparse sampling of scanning projections. The inputs are the two 3D Radon transforms of the CT scans, one densely sampled and the other sparsely sampled (limited number of scan angles/ranges). The output is the rigid transformation that best matches them. The method(More)
We present a new method for rigid registration of CT scans in Radon space. The inputs are the two 3D Radon transforms of the CT scans, one densely sampled and the other sparsely sampled. The output s the rigid transformation that best matches them. The algorithm starts by finding the best matching between each direction vector in the sparse transform and(More)
This paper describes a new method for imageless needle and patient tracking in interventional CT procedures based on fractional CT scanning. Our method accurately locates a needle with a spherical marker attached to it at a known distance from the tip with respect to the patient in the CT scanner coordinate frame with online sparse scan sampling and without(More)
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