Enhancing Cone-Beam CT Image Quality in TIPSS Procedures Using AI Denoising

Enhancing Cone-Beam CT Image Quality in TIPSS Procedures Using AI Denoising

<i>Purpose:</i> This study evaluates a deep learning-based denoising algorithm to improve the trade-off between radiation dose, image noise, and motion artifacts in TIPSS procedures, aiming for shorter acquisition times and reduced radiation with maintained diagnostic quality. <i>M...

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Bibliographic Details
Main Authors: Reza Dehdab, Andreas S. Brendlin, Gerd Grözinger, Haidara Almansour, Jan Michael Brendel, Sebastian Gassenmaier, Patrick Ghibes, Sebastian Werner, Konstantin Nikolaou, Saif Afat
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Diagnostics
Subjects:
TIPSS (Transjugular Intrahepatic Portosystemic Shunt)
cone-beam computed tomography
AI denoising
image quality analysis
radiation dose reduction
Online Access:https://www.mdpi.com/2075-4418/14/17/1989

Internet

https://www.mdpi.com/2075-4418/14/17/1989

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