Comparison of noise-magnitude and noise-texture across two generations of iterative reconstruction algorithms from three manufacturers

Abstract Purpose To compare the noise-magnitude and noise-texture across two generations of iterative reconstruction (IR) algorithms proposed by three manufacturers according to the dose level. Materials and Methods Five computed tomography (CT) systems equipped with two generations of IR algorithms (hybrid/statistical IR [H/SIR] or full/partial model-based IR [MBIR]) were compared. Acquisitions on Catphan 600 phantom were performed at 120 kV and three dose levels (3-, 7- and 12-mGy). Raw data were reconstructed using standard “soft tissue” kernel for filtered back projection and one iterative level of two generations of IR algorithms. Contrast to-noise-ratio (CNR) was computed using three regions of interest: two of them placed in the low-density polyethylene (LDPE) and Teflon ® inserts and another placed on the solid water. Noise power spectrum (NPS) was computed to assess the noise-magnitude (NPS peak) and noise-texture (NPS spatial frequency). Results CNR increased significantly in MBIR compared to H/SIR algorithms for General-Electric (GE) Healthcare (45% ± 12 [SD]) and Philips Healthcare systems (62% ± 11 [SD]) ( P P ® insert but not for LDPE insert (mean difference: −4% ± 7 [SD]) ( P =  N.S.). NPS peaks were lower with MBIR than with H/SIR for GE Healthcare (-42% ± 8 [SD]) and Philips Healthcare (−75% ± 4 [SD]) systems, whereas it was greater with MBIR than with H/SIR for Siemens Healthineers (13% ± 11 [SD]) systems. NPS spatial frequencies were higher with MBIR than with H/SIR for Siemens (14% ± 10 [SD]) but lower for others (−17% ± 5 [SD] for GE Healthineers and −55% ± 3 [SD] for Philips Healthcare systems). Conclusion This study demonstrates that recent MBIR algorithms, by comparison with the preceding generation, differ according to the main manufacturers with respect to noise-magnitude and noise-texture.