Fast Variance Prediction for Iterative Reconstruction of 3D Helical CT Images
نویسندگان
چکیده
Fast variance prediction for iteratively-reconstructed helical CT images is useful for analysis of resulting images and potentially for dynamic dose adjustment during a scan. Previous methods require impractical computation times to approximate the image variance; other methods are able to approximate variance quickly but only for specific CT geometries, excluding 3D helical CT. In this paper we present an extension of these previous fast methods to predict the variance of iteratively reconstructed images for third-generation 3D helical CT scans. We compare this method in computation time and error to the empirical variance derived from multiple simulated reconstruction realizations.
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