Speaker
Description
Digital tomosynthesis (DTS) is a limited-angle imaging technique that provides volumetric information at a fraction of computed tomography (CT) dose [1]. However, the restricted angular coverage inherently produces out-of-plane artifacts, degrading slice selectivity and contrast-to-noise ratio (CNR). Slice-thickness filtering (STF) applied after filtered back projection (FBP) reconstruction is a well-established approach for suppressing such artifacts [2]. However, conventional STF employs fixed spectral apodization parameters optimized for nominal conditions and therefore cannot adapt to elevated noise in sparse-view or low-dose acquisitions. In this study, we propose a noise-adaptive slice-thickness filtering (NASF) method, in which the fixed spectral apodization term is replaced with a noise-adaptive weighting function derived from the noise power spectrum (NPS) of the reconstructed volume. The NPS is estimated from homogeneous background regions, and the resulting spectral energy distribution is used to automatically control the strength of high-frequency suppression. This allows the filter to adapt its spectral response to the actual noise level, while the slice-thickness component remains unchanged, preserving geometric slice selectivity. Figure 1 illustrates the overall NASF framework. To experimentally validate the proposed method, DTS projections of a chest phantom were acquired over an angular range of ±20° using 50 projections. Figure 2 shows the reconstruction results. Compared with both FBP and conventional STF, NASF effectively suppresses out-of-plane artifacts (red arrows) while preserving structural details. Figure 3 summarizes the quantitative evaluation using the ROIs shown in Figure 2. NASF achieved full width at half maximum (FWHM) of approximately 25.5 mm in the artifact spread function (ASF), comparable to that of FBP (25.2 mm), while improving CNR to 4.1, corresponding to a 23.1% increase over conventional STF (3.4) and a 53.4% increase over FBP (2.7). These results demonstrate that NASF enables noise-adaptive artifact suppression without compromising spatial resolution, offering a practical alternative to fixed-parameter STF for DTS reconstruction.