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November 13, 2025Journal of Clinical Imaging Science

Comparison of image quality in carotid dual-energy computed tomography angiography at 55 keV virtual monoenergetic imaging using deep learning and adaptive iterative reconstruction algorithm

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Authors

XLXiaohan LiuCWChong WangJLJuan Long

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Overview

This prospective study demonstrates improved image quality in carotid dual-energy CT, indicating deep learning enhances visibility in high-BMI patients.

Key Points

  • DLIR-H significantly improved image quality, reducing background noise and enhancing delineation of vascular structures.
  • Background noise reduction and increased signal-to-noise ratio were observed with DLIR-H compared to traditional methods.
  • Prospective analysis of image quality was conducted in 48 patients undergoing dual-energy computed tomography examinations.
  • Findings suggest DLIR-H offers superior performance in individuals with a body mass index ≥24 kg/m2, highlighting its clinical significance.

Cite This Study

Liu et al. (2025) studied this question.

synapsesocial.com/papers/692523bbc0ce034ddc354a21https://doi.org/10.25259/jcis_109_2025
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