Image covariance and lesion detectability in direct fan-beam x-ray computed tomography.
We consider noise in computed tomography images that are reconstructed using the classical direct fan-beam filtered backprojection algorithm, from both full- and short-scan data. A new, accurate method for computing image covariance is presented. The utility of the new covariance method is demonstrated by its application to the implementation of a channelized Hotelling observer for a lesion detection task. Results from the new covariance method and its application to the channelized Hotelling observer are compared with results from Monte Carlo simulations. In addition, the impact of a bowtie filter and x-ray tube current modulation on reconstruction noise and lesion detectability are explored for full-scan reconstruction.
Wunderlich
Adam
A
Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, UT, USA. awunder@ucair.med.utah.edu
Noo
Frédéric
F
D000465:Algorithms; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009010:Monte Carlo Method; D012680:Sensitivity and Specificity; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*