Abstract
Over the past few years, computed tomography (CT) reconstruction theory has undergone a rapid development. Since Katsevich published his paper on exact and efficient helical cone-beam CT reconstruction in 2002, intensified research efforts have been made in this field. Various analytic algorithms have been proposed for exact reconstruction from many kinds of projection data. Among them, region-of-interest (ROI) or volume-of-interest (VOI) image reconstruction is one important class of methods in which the projections are usually transversely truncated. During the past three years, some novel algorithms have been developed for exact ROI/VOI reconstruction. Here we present an overview of some key results in this field, especially emphasizing three milestone algorithms: the super-short-scan algorithms, the backprojection- filtration (BPF) or differentiated backprojection (DBP) algorithms, and the POCS (projection onto convex sets) algorithms for interior problem. Finally, we make concluding remarks.
Keywords: Computed tomography (CT), image reconstruction, region-of-interest (ROI), truncated Hilbert transform, interior problem
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