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18 March 2008 A preliminary investigation of using prior information for potentially improving image reconstruction in few-view CT
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Abstract
There exists a strong need to reconstruct computed tomographic (CT) images with practically useful quality from a small number of projections in image-guided radiation therapy: for lowering radiation dose delivered to the subject, for shortening the imaging time, and for reducing the imaging-configuration complexity. We have recently developed an iterative image reconstruction algorithm based on total-variation (TV) minimization from incomplete projection data in CT. In numerical studies with a variety of incomplete projection-data sets including truncated data, reduced scan range, and sparse sampling, the developed algorithm seems to yield reasonable reconstruction, as compared to some of the existing algorithms, such as algebraic reconstruction technique (ART) and expectation minimization (EM). The TV-based algorithm begins in general with a uniform image as an initial guess, and goes through iteration steps to minimize the image TV subject to satisfying the given incomplete projection data. In image-guided radiation therapy (IGRT), a patient usually undergoes CT scanning for treatment planning, which can provide the reference image for image guidance. Therefore, we propose a TV-based algorithm with a priori information in few-view CT for IGRT, in an attempt to further reduce the number of projections needed for image reconstruction from what the TV-based algorithm uses when no a priori information is included. In this work, we report the initial results of a preliminary numerical study that we have conducted to demonstrate this approach.
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Seungryong Cho, Emil Y. Sidky, Junguo Bian, Charles A. Pelizzari, and Xiaochuan Pan "A preliminary investigation of using prior information for potentially improving image reconstruction in few-view CT", Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging, 69132C (18 March 2008); https://doi.org/10.1117/12.772063
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