Performance of three model-based iterative reconstruction algorithms using a CT task-based image quality metric
G. Muti, S. Riga, L. Berta, D. Curto, C. De Mattia, M. Felisi, F., Rizzetto, A. Torresin, A. Vanzulli, P. E. Colombo

TL;DR
This study compares the task-based image quality of three CT scanners using different model-based iterative reconstruction levels, showing how detectability varies with reconstruction method and dose, aiding protocol optimization.
Contribution
It introduces a comprehensive evaluation of CT image quality using task-based metrics across different vendors and MBIR levels, highlighting differences in detectability.
Findings
Advanced MBIR yields higher detectability index (d')
Different CT systems show varying noise power spectrum behaviors
Detectability index can guide dose reduction and protocol optimization
Abstract
In this study we evaluated the task-based image quality of a low contrast clinical task for the abdomen protocol (e.g., pancreatic tumour) of three different CT vendors, exploiting three model-based iterative reconstruction (MBIR) levels. We used three CT systems equipped with a full, partial, advanced MBIR algorithms. Acquisitions were performed on a phantom at three dose levels. Acquisitions were reconstructed with a standard kernel, using filtered back projection algorithm (FBP) and three levels of the MBIR. The noise power spectrum (NPS), the normalized one (nNPS) and the task-based transfer function (TTF) were computed following the method proposed by the American Association of Physicists in Medicine task group report-233 (AAPM TG-233). Detectability index (d') of a small lesion (small feature; 100 HU and 5-mm diameter) was calculated using non-prewhitening with eye-filter model…
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Taxonomy
TopicsRadiation Dose and Imaging · Digital Radiography and Breast Imaging · Medical Imaging Techniques and Applications
