Enhanced visualization in endoleak detection through iterative and AI-noise optimized spectral reconstructions

Enhanced visualization in endoleak detection through iterative and AI-noise optimized spectral reconstructions

Abstract To assess the image quality parameters of dual-energy computed tomography angiography (DECTA) 40-, and 60 keV virtual monoenergetic images (VMIs) combined with deep learning-based image reconstruction model (DLM) and iterative reconstructions (IR). CT scans of 28 post EVAR patients were enr...

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Bibliographic Details
Main Authors: Wojciech Kazimierczak, Natalia Kazimierczak, Justyna Wilamowska, Olaf Wojtowicz, Ewa Nowak, Zbigniew Serafin
Format: Article
Language:English
Published: Nature Portfolio 2024-02-01
Series:Scientific Reports
Subjects:
Abdominal aortic aneurysms
Endoleak
Endovascular aneurysm repair
Dual-energy computed tomography angiography
Virtual monoenergetic images
Image reconstruction, deep learning model
Online Access:https://doi.org/10.1038/s41598-024-54502-1

Internet

https://doi.org/10.1038/s41598-024-54502-1

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