医学
算法
氡变换
图像质量
迭代重建
数学
血管造影
放射科
人工智能
图像(数学)
计算机科学
数学分析
作者
Jia Xu,Shitian Wang,Xuan Wang,Yun Wang,Huadan Xue,Jing Yan,Min Xu,Zhengyu Jin
标识
DOI:10.1016/j.ejrad.2022.110388
摘要
To investigate whether contrast-enhancement-boost (CE-boost) in combination with hybrid iterative reconstruction (Hybrid IR, also named HIR [AIDR 3D, adaptive iterative dose reduction three dimensional]) and model-based iterative reconstruction (MBIR [FIRST, forward projected model-based IR solution]) algorithms can improve the image quality of abdominal CT angiography (CTA).This retrospective study included 50 patients who underwent abdominal CTA. Both arterial and portal phases were reconstructed using three different algorithms [filtered-back projection (FBP), AIDR 3D, and FIRST] separately. CE-boost was performed additionally to generate AIDR 3D-boost and FIRST-boost images. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the arteries and portal system were compared among the five datasets (FBP, AIDR 3D, FIRST, AIDR 3D-boost, FIRST-boost). In subjective analyses, two radiologists independently ordered images (5, best; 1, worst) based on the visual image quality of distal arterial or portal venous branches. The Friedman and the Dunn-Bonferroni post-hoc tests were used for statistical analysis.FIRST-boost arterial and portal images had the lowest noise compared with FBP, AIDR 3D, FIRST, and AIDR 3D-boost images (all P < 0.05), and significantly higher SNR and CNR than FBP, AIDR 3D, and FIRST images (all P < 0.05). AIDR 3D-boost images showed lower noise, and higher SNR and CNR than FBP and AIDR 3D images (all P < 0.05). FIRST-boost images had higher subjective grading scores than FBP, AIDR 3D, and AIDR 3D-boost images (all P < 0.05).The postprocessing technique CE-boost can improve the image quality of abdominal CTA images. MBIR in combination with CE-boost (FIRST-boost) images had the best image quality compared with the other four image datasets.
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