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PubMed · 887653

Optimum spread functions in linear tomography.

Abstract

Recent attempts to reduce artefacts in tomographic blurring, using a transfer function approach, have so far taken little explicit account of the lessening in the degree of blurring which accompanies transfer function correction. A simple comparative measure R of the blurring effect of a linear tomographic movement is proposed. The parameter R is related to the ratio of the area of the point spread function (PSF) to its peak height. It is shown that the PSF having the greatest value of R (maximum blurring), whilst having an entirely positive transform, is of triangular form. Conversely, any PSF for which the value of R exceeds Rtriangle is inevitably associated with phase reversals. The problem of finding the PSF with R greater than Rtriangle, which leads to the minimum degree of phase reversal, has been tackled by determining the transfer function which, for the given value of R, has the minimum area under its subsidiary maxima. Transfer functions optimized in this way, and their corresponding PSFS, are calculated for four values of R using the method described by Jacquinot and Roizen-Dossier. The results of this procedure are discussed and its possible extensions noted.

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BibTeXRIS

G Harding. 1977. Optimum spread functions in linear tomography.. https://doi.org/10.1088/0031-9155%2F22%2F4%2F008

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Longitudinal image deblurring in spiral CT.

PURPOSE: To assess the feasibility of digital deconvolution techniques to improve longitudinal resolution of spiral computed tomography (CT) multiplanar reformations and evaluate how technical factors in deconvolution affect longitudinal resolution, noise, and edge ringing. MATERIALS AND METHODS: Longitudinal line spread function (LSF) of the system was estimated from longitudinal reformations of transaxial spiral CT images of a step test phantom. By using the estimated LSF, longitudinal reformations of the phantom and three clinical spiral CT studies were deconvolved by the methods of Wiener filtering and constrained iterative deconvolution. Edge ringing and image noise were quantified for Wiener filtering and constrained iterative deconvolution. RESULTS: Longitudinal reformations were substantially deblurred and resolution improved after deconvolution. Anatomic boundaries in clinical images were more clearly delineated after restoration. The methods of Wiener deconvolution and constrained iterative deconvolution improved the sharpness of the phantom step boundary at the expense of increased edge ringing and image noise. CONCLUSION: In longitudinal spiral CT reformations, blurring along the longitudinal axis can be reduced by Wiener filtering or constrained iterative deconvolution.

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