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. 2011 Feb 22;38(3):1444–1458. doi: 10.1118/1.3549757

Figure 7.

Figure 7

(a) Comparison of the bone insert ESF shape for the FBP algorithm with FWHM=1.4 mm and the AM-700 algorithm with α=0.015. The corresponding lines represent the Gaussian-exponential model fit used for the estimation of the MTF. Smoothing strengths were chosen for comparison as they reconstructed nearly matched image noise (∼1.09%±0.01%). Note the difference in ESF shape between the two algorithms in (a) at nearly matched image noise. The FBP edge-spread functions were found to be well fit by both Gaussian and Gaussian-exponential blurring models. (b) zooms in on the AM-700 ESF fitting to show that the Gaussian blurring model had trouble fitting the steep central transition and shoulder roll-off seen in the AM-700 high-contrast edges. This finding motivated the use of the Gaussian-exponential blurring model to fit all of the edge-spread functions in this work. (c) and (d) display the MTF calculation for the FBP and AM-700 bone inserts, respectively.