Correlation of Automated in Vivo Image Quality With Radiologist’s Performance in Abdomen Computed Tomography Across Conventional and Deep Learning Reconstructions
The new formalism can robustly reflect CT systems clinical performance irrespective of reconstruction algorithm. The methodology can be more readily applied to assess the real-world performance of CT systems.
Authors
- Francesco Ria (ORCID: https://orcid.org/0000-0001-7455-4290)
- Corey Jensen
- Xinming Liu
- Ehsan Samei
- Craig K. Abbey
- Mojtaba Zarei
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- University of California, Santa Barbara (US)
- Wisdom Health (United States) (US)
- Duke University Health System (US)
- Advanced Imaging Research (United States) (US)
- Society of Abdominal Radiology (US)
Publication Details
- Journal
- Journal of Computer Assisted Tomography
- Published
- 2026-01-15
- DOI
- https://doi.org/10.1097/rct.0000000000001845
- Primary Topic
- Radiation Dose and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00