Blind deblurring of spiral CT images-comparative studies on edge-to-noise ratios.
A recently developed blind deblurring algorithm based on the edge-to-noise ratio has been applied to improve the quality of spiral CT images. Since the discrepancy measure used to quantify the edge and noise effects is not symmetric, there are several ways to formulate the edge-to-noise ratio. This article is to investigate the performance of those ratios with phantom and patient data. In the phantom study, it is shown that all the ratios share similar properties, validating the blind deblurring algorithm. The image fidelity improvement varies from 29% to 33% for different ratios, according to the root mean square error (RMSE) criterion; the optimal iteration number determined for each ratio varies from 25 to 35. Those ratios that are associated with most satisfactory performance are singled out for the image fidelity improvement of about 33% in the numerical simulation. After automatic blind deblurring with the selected ratios, the spatial resolution of CT is substantially refined in all the cases tested.
Jiang
Ming
M
Department of Information Science, School of Mathematics, Peking University, Beijing, People's Republic of China. jiangm@ct.radiology.uiowa.edu
Wang
Ge
G
Skinner
Margaret W
MW
Rubinstein
Jay T
JT
Vannier
Michael W
MW
D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D003051:Cochlea / Q000000981:diagnostic imaging; D006801:Humans; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted; D036542:Tomography, Spiral Computed / Q000706:statistics & numerical data*