Time - Regularization Methods in Sparse X-ray Tomography

Paola Elefante (University of Helsinki)

Frank Adams 2,

Developing methods to handle sparse measurements in X-ray tomography offers promising opportunities of radiation dose-reduction and cutting manifacturing costs by limiting sources and detectors. How to reconstruct a moving object, such as running engine, a mouse, or a beating human heart, from time-dependent radiographic sparse data? Several experiments with undersampled tomographic data are carried out on simulated phantoms, enforcing some degree of regularity both spatially and temporally with different techniques.

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