Document Detail


Longitudinal image deblurring in spiral CT.
MedLine Citation:
PMID:  7972755     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
F J Schlueter; G Wang; P S Hsieh; J A Brink; D M Balfe; M W Vannier
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Radiology     Volume:  193     ISSN:  0033-8419     ISO Abbreviation:  Radiology     Publication Date:  1994 Nov 
Date Detail:
Created Date:  1994-11-28     Completed Date:  1994-11-28     Revised Date:  2000-12-18    
Medline Journal Info:
Nlm Unique ID:  0401260     Medline TA:  Radiology     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  413-8     Citation Subset:  AIM; IM    
Affiliation:
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO 63110.
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MeSH Terms
Descriptor/Qualifier:
Technology, Radiologic
Tomography, X-Ray Computed / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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