CT理论与应用研究2026，Vol.35Issue(1)：67-73,7.DOI:10.15953/j.ctta.2025.220
ClearInfinity算法权重对颅脑能谱CTA中虚拟单能图像质量的影响
Influence of ClearInfinity Algorithm Weight on the Quality of Virtual Monoenergetic Images in Cranial Spectral Computed Tomography Angiography
徐军 1孔祥闯 2黄一豪 2刘志伟 2李昌伟 2柏雪 2宁先英 2胡孝梨 3罗昆 2吴红英2
作者信息
- 1. 长江大学医学部,湖北 荆州 434023
- 2. 华中科技大学同济医学院附属协和医院放射科,武汉 430022||湖北省精准智能放射诊断与介入治疗临床医学研究中心,武汉 430022||湖北省分子影像重点实验室,武汉 430022
- 3. 武汉亚洲心脏病医院放射科,武汉 430022
- 折叠
摘要
Abstract
Objective:To investigate how the weights of the deep learning-based ClearInfinity(CI)algorithm affect the quality of 55 keV virtual monoenergetic images(VMIs)in cranial spectral computed tomography angiography(CTA),and to provide a basis for clinical optimization of reconstruction parameters.Methods:A total of 38 patients who had undergone cranial spectral CTA were retrospectively enrolled.The original data were reconstructed using the CI algorithm with weights of 10%,30%,50%,70%,and 90%to obtain five groups of 55 keV VMIs.Objective evaluation was performed by measuring the vascular CT values,gray matter CT values,background noise(BN),signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR).Double-blind subjective scoring of image noise,vascular edges,and detailed display was performed by two radiologists.Results:No statistically significant differences were observed in the CT values of blood vessels(right internal carotid artery,right middle cerebral artery,and basilar artery)or gray matter among the different weights.However,pairwise comparisons showed statistically significant differences in BN,SNR,and CNR among the weight groups.BN gradually decreased,whereas SNR and CNR gradually increased with increase in algorithm weight.Subjective scores of the five groups showed statistically significant differences,with the average scores from high to low being 4.95±0.22(50%CI),4.87±0.36(70%CI),4.74±0.48(90%CI),4.66±0.58(30%CI),and 4.03±0.62(10%CI).Conclusion:The CI algorithm weight influences image quality:relatively low weights compromise image quality owing to excessive noise,whereas relatively high weights cause over-smoothing and blurring of the image,resulting in the loss of fine structures.Therefore,this study recommends a 50%CI algorithm weight for reconstructing 55 keV VMIs in cranial spectral CTA.关键词
能谱CTA/深度学习/颅脑CTA/图像质量/ClearInfinityKey words
spectral CTA/deep learning/cranial CTA/image quality/ClearInfinity分类
信息技术与安全科学引用本文复制引用
徐军,孔祥闯,黄一豪,刘志伟,李昌伟,柏雪,宁先英,胡孝梨,罗昆,吴红英..ClearInfinity算法权重对颅脑能谱CTA中虚拟单能图像质量的影响[J].CT理论与应用研究,2026,35(1):67-73,7.
