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Optimal short scan convolution reconstruction for fan beam CT
Author(s) -
Parker Dennis L.
Publication year - 1982
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.595078
Subject(s) - weighting , convolution (computer science) , scanner , iterative reconstruction , mathematics , image quality , algorithm , data set , set (abstract data type) , image (mathematics) , mathematical analysis , computer science , computer vision , artificial intelligence , physics , statistics , acoustics , artificial neural network , programming language
The problem of using a divergent fan beam convolution reconstruction algorithm in conjunction with a minimal complete (180° plus the fan angle) data set is reviewed. It is shown that by proper weighting of the initial data set, image quality essentially equivalent to the quality of reconstructions from 360° data sets is obtained. The constraints on the weights are that the sum of the two weights corresponding to the same line‐integral must equal one, in regions of no data the weights must equal zero, and the weights themselves as well as the gradient of the weights must be continuous over the full 360°. After weighting the initial data with weights that satisfy these constraints, image reconstruction can be conveniently achieved by using the standard (hardwired if available) convolver and backprojector of the specific scanner.