In today's tomographic imaging, there are more incomplete data systems, such as few-view system. The advantage
of few-view tomography is less x-ray dose and reduced scanning time. In this work, we study the projection
distribution in few-view fan-beam imaging. It is one of the fundamental problems in few-view imaging because
of its severe lack of projection data. The aim is to reduce data redundancy and to improve the quality of reconstructed
images by research on projection distribution schemes. The reconstruction algorithm for few-view
imaging is based on algebraic reconstruction techniques (ART) and total variation (TV) constraint approached
by E. Sidky et al in 2006. Study of few-view fan-beam projection distribution is performed mainly through
comparison of several distribution types in projection space and reconstructed images. Results show that the
distribution called short-scan type obtains the best image in five typical distributions.
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