Optimization of hypovascular liver lesion detectability in dual-energy CT using deep learning image reconstruction: a phantom study for potential iodine dose reduction.
Saved in:
| Title: | Optimization of hypovascular liver lesion detectability in dual-energy CT using deep learning image reconstruction: a phantom study for potential iodine dose reduction. |
|---|---|
| Authors: | Gulizia M; Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland. marianna.gulizia@chuv.ch., Dromain C; Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland., Haefliger L; Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland., Chettab H; Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland., Chevallier C; Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland., Viry A; Institute of Radiation Physics, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland. |
| Source: | European radiology experimental [Eur Radiol Exp] 2026 Jul 01; Vol. 10 (1). Date of Electronic Publication: 2026 Jul 01. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: SpringerOpen Country of Publication: England NLM ID: 101721752 Publication Model: Electronic Cited Medium: Internet ISSN: 2509-9280 (Electronic) Linking ISSN: 25099280 NLM ISO Abbreviation: Eur Radiol Exp Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 2509-9280 |
|---|---|
| DOI: | 10.1186/s41747-026-00759-2 |
