A content-adaptive unstructured grid based integral equation method with the tv regularization for spect reconstruction

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Abstract

Existing reconstruction methods for single photon emission computed tomography (SPECT) are most based on discrete models, leading to low accuracy in reconstruction. Reconstruction methods based on integral equation models (IEMs) with a higher order piecewise polynomial discretization on the pixel grid for SEPCT imaging were recently proposed to overcome the accuracy deficiency of the discrete models. Discretization of IEMs based on the pixel grid leads to a system of a large dimension, which may require higher computational costs to solve. We develop a SPECT reconstruction method which employs an IEM of the SPECT data acquisition process and discretizes it on a content-adaptive unstructured grid (CAUG) with the total variation (TV) regularization aiming at reducing computational costs of the integral equation.

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Chen, Y., Huang, J., Li, S., Lu, Y., & Xu, Y. (2020). A content-adaptive unstructured grid based integral equation method with the tv regularization for spect reconstruction. Inverse Problems and Imaging, 14(1), 27–52. https://doi.org/10.3934/ipi.2019062

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