Image quality of virtual monochromatic and material density iodine images for evaluation of head and neck neoplasms using deep learning-based CT image reconstruction – A retrospective observational study
DECT using both DLIR and MAR for the generation of VMIs and MD iodine images resulted in higher subjective quality of oncologic head and neck images than ASIR-V-based SECT. Noise reduction and noise texture were best achieved with DLIR-based MD iodine images.
Authors
- Stephanie Gräger (ORCID: https://orcid.org/0000-0001-6288-6087)
- Lucja Mlynska
- Florian Bürckenmeyer
- Felix Güttler (ORCID: https://orcid.org/0000-0002-4414-2188)
- Martin Krämer (ORCID: https://orcid.org/0000-0002-0173-9830)
- Ulf Teichgräber (ORCID: https://orcid.org/0000-0002-4048-3938)
- Maja Ingwersen (ORCID: https://orcid.org/0000-0001-6943-2184)
Institutions
- Jena University Hospital (DE)
- Friedrich Schiller University Jena (DE)
Publication Details
- Journal
- European Journal of Radiology
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1016/j.ejrad.2024.111806
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- GE Healthcare