Quantitative Analysis of Airway Tree in Low-dose Chest CT with a New Model-based Iterative Reconstruction Algorithm: Comparison to Adaptive Statistical Iterative Reconstruction in Routine-dose CT

摘要

Objective: We aimed to evaluate a new model-based iterative reconstruction (MBIRn) algorithm either with spatial resolution and noise reduction balance (MBIRSTND) or spatial resolution preference (MBIRRP20) for quantitative analysis of airway in low-dose chest computed tomography (CT) with a computer-aided detection (CAD) software, in comparison to adaptive statistical iterative reconstruction (ASIR) in routine-dose CT.