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Super resolution in CT
Author(s) -
Yan Ziye,
Li Jianwu,
Lu Yao,
Yan Hongxia,
Zhao Yanfeng
Publication year - 2015
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.22125
Subject(s) - imaging phantom , projection (relational algebra) , computer science , resolution (logic) , medical diagnosis , plane (geometry) , computer vision , computed tomography , artificial intelligence , image resolution , iterative reconstruction , algorithm , nuclear medicine , physics , optics , mathematics , medicine , radiology , geometry
The general framework of super resolution in computed tomography (CT) system is introduced. Two data acquisition ways before or after the reconstruction respectively are described. Three models including the sinogram model, the in‐plane model and the z‐ axis model, are addressed to adapt super resolution to CT system. The improved iterative back projection algorithm is used in this work. Experimental results based on simulated data, GE performance phantom scanned by GE LightSpeed VCT system, one patient volunteer scanned by TOSHIBA Aquilion system, and a special experimental apparatus demonstrate that super resolution is effective to improve the resolution of CT images. The sinogram model is suitable for future CT system; the in‐plane model is restricted to some special clinical diagnoses; and the z‐ axis model is practicable for current general clinical CT images. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 92–101, 2015