深度学习重建算法对肺静脉CT图像质量的改善价值  

The Value of Deep Learning-based Reconstruction Algorithms for Improving the Quality of Pulmonary Vein CT Images

作　　者：陈涵潇 田祥洁 雷美娟 CHEN Hanxiao;TIAN Xiangjie;LEI Meijuan(Department of Radiology,the Third Affiliated Hospital of Sun Yat-Sen University,Guangdong 510000,China;Stomatological Hospital,School of Stomatology,Southern Medical University,Guangdong 510200,China)

机构地区：[1]中山大学附属第三医院放射科,广东510000 [2]南方医科大学口腔医院(口腔医学院),广东510200

出　　处：《影像技术》2024年第5期45-50,共6页Image Technology

摘　　要：目的:通过对比常规自适应迭代重建算法(ASiR-V),研究基于深度学习的图像重建算法(DLIR)对左心房及肺静脉CT图像质量和诊断信心的提高。方法:回顾性纳入31例行左心房及肺静脉CT成像的患者,对其原始数据使用滤波反投影(FBP)、30%ASiR-V、70%ASiR-V、DLIR-M(中)和DLIR-H(高)5种重建算法分别进行重建,测量左心房的CT值,计算相应背景噪声(SD)值、信噪比(SNR)值和对比噪声比(CNR)值。由2名工作多年放射科医师分别评价5组重建图像的图像质量。结果:客观评价:5组重建图像在左心房的SD值、CNR值和SNR值的差异均有统计学意义(P<0.001)。其中DLIR-H最好,FBP和30%ASiR-V、DLIR-M与70%ASiR-V无显著性差异。随DLIR重建等级增加,SD值降低,SNR值和CNR值升高。主观评价:2位放射科医师对图像质量的主观评价一致性良好(kappa值为0.814),DLIR-H表现出最佳主观图像质量分数。结论:DLIR与FBP、ASiR-V算法相比,降噪效果更明显,图像质量更好。Objective:To investigate the improvement of image quality and diagnostic confidence in CT images of the left atrium and pulmonary veins with deep learning image reconstruction(DLIR)compared to conventional adaptive iterative reconstruction algorithms(ASiR-V).Methods:Thirty-one patients with CT imaging of the left atrium and pulmonary veins were retrospectively included,and their raw data were reconstructed using five reconstruction algorithms:filtered back projection(FBP),30%ASiR-V,70%ASiR-V,DLIR-M(medium)and DLIR-H(high),respectively,to measure CT values of the left atrium and calculate the corresponding background noise(Standard Deviation,SD)values,signal-to-noise ratio(SNR)values and contrast-to-noise ratio(CNR)values were calculated.The image quality of each of the five sets of reconstructed images was evaluated by two radiologists who had worked for many years.Results:Objective evaluation:The differences in SD,CNR and SNR values in the left atrium were statistically significant(P<0.001)in all five groups.DLIR-H was the best,with no significant differences between FBP and 30%ASiR-V,DLIR-M and 70%ASiR-V.The SD values decreased and the SNR and CNR values increased with increasing DLIR reconstruction grade.Subjective evaluation:The subjective evaluation of image quality by the two radiologists was consistent(kappa value of 0.814),with DLIR-H showing the best subjective image quality score.Conclusion:DLIR is more effective in noise reduction and has better image quality than the FBP and ASiR-V algorithms.

关 键 词：深度学习 迭代重建 滤波反投影 图像质量 

分 类 号：R4[医药卫生—临床医学]