Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization
Applying the super-resolution-based slice generation on thick-slice CT images prior to automatic nodule evaluation significantly increases the accuracy of pulmonary nodule volumetry and corresponding pulmonary nodule category.
Authors
- Jong Hyo Kim (ORCID: https://orcid.org/0000-0002-5695-4976)
- Chulkyun Ahn (ORCID: https://orcid.org/0000-0003-2919-4892)
- Dong Kim (ORCID: https://orcid.org/0000-0002-1523-6396)
Institutions
- Seoul National University (KR)
- Seoul National University Hospital (KR)
- Paulsson (United States) (US)
- Advanced Institute of Convergence Technology (KR)
Publication Details
- Journal
- Tomography
- Published
- 2025-01-27
- DOI
- https://doi.org/10.3390/tomography11020013
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.72