2022 年 40 巻 3 号 p. 120-132
Iterative image reconstruction using nonlinear sparsifying transform with L1 regularization for CT has been reported to preserve contour and texture while decreasing statistical noise. We investigated the spatial resolution characteristics of this algorithm when applied to a conventional angular views with simulation study. A two-dimensional numerical phantom with a 512 × 512 matrix consists of 184 mm background disk with various 20 mm diameter contrast inserts (−60% to +60%). An ideal parallel beam projection data without degrading factors such as scatter and beam hardening was assumed. The spatial resolution expressed as FWHM was estimated from the edge spread function for disk. The FWHM of L1 reconstruction using nonlocal means filter (NLM) and bilateral filter was highly dependent on the contrast, while median filter was not. A threshold 𝛿* exists in parameter 𝛿 of L1 reconstruction with NLM (L1-NLM) for each object with different contrast; 𝛿* determines the spatial resolution blurring contour most. Contour preservation works effectively if 𝛿 is set sufficiently smaller than 𝛿* of each object, but the contour is remarkably blurred if it is set to larger than or equal to 𝛿*. This causes the contrast dependence of spatial resolution in L1-NLM.
