[1]薛旭涛,韩志威,刘 燕,等.基于模型迭代重建算法在减少后颅窝CT图像硬化伪影中的价值研究[J].陕西医学杂志,2021,50(12):1550-1553.[doi:DOI:10.3969/j.issn.1000-7377.2021.12.021]
　XUE Xutao,HAN Zhiwei,LIU Yan,et al.Value of model-based iterative reconstruction in reducing beam hardening artifacts in CT images of posterior fossa[J].,2021,50(12):1550-1553.[doi:DOI:10.3969/j.issn.1000-7377.2021.12.021]
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基于模型迭代重建算法在减少后颅窝CT图像硬化伪影中的价值研究
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《陕西医学杂志》[ISSN:1000-7377/CN:61-1281/TN]

卷:
50
期数:
2021年12期
页码:
1550-1553
栏目:
临床研究
出版日期:
2021-12-05

文章信息/Info

Title:
Value of model-based iterative reconstruction in reducing beam hardening artifacts in CT images of posterior fossa
作者:
薛旭涛1; 韩志威2; 刘 燕1; 张 箭1; 李鲜宁1; 严 涛1
(1.西电集团医院放射影像科,陕西 西安 710077; 2.空军军医大学西京医院,陕西 西安 710032)
Author(s):
XUE Xutao; HAN Zhiwei; LIU Yan; ZHANG Jian; LI Xianning; YAN Tao
(Department of Radiology,XD Group Hospital,Xi'an 710077,China)
关键词:
硬化伪影;  图像噪声;  伪影指数;  基于模型迭代重建;  滤波反投影;  自适应迭代重建
Keywords:
Beam hardening artifacts;  Image noise;  Artifact Index;  MBIR;  FBP;  ASIR
分类号:
R 455.3
DOI:
DOI:10.3969/j.issn.1000-7377.2021.12.021
文献标志码:
A
摘要:
目的:探讨基于模型迭代重建(MBIR)算法在减少后颅窝CT图像硬化伪影中的价值。方法:使用能谱CT颅脑条件扫描静止状态下容纳9支试管的血管模型,试管内分别填满纯水、钙溶液,以及1、2、5、10、20、30 mgI/ml溶液。得到原始扫描数据后分别使用标准算法滤波反投影(FBP)、自适应迭代重建(ASIR)40(40% ASIR与FBP混合)、MBIR中标准设置(MBIRSTND)和优化低密度对比设置(MBIRNR40)四种算法重建层厚0.625 mm的图像,放置感兴趣区测量试管周围噪声,计算不同密度试管周围的伪影指数(AI)。随机抽取80例颅脑CT扫描病例,使用FBP、ASIR40、MBIRSTND、MBIRNR40四种算法重建层厚0.625 mm的图像,选取后颅窝亨氏暗区最明显层面放置感兴趣区测量小脑白质及脑干CT值的噪声并计算脑干AI,并采用5分法对图像进行主观评分。比较不同重建图像试管周围噪声及AI。比较不同重建图像后颅窝内脑干噪声、AI及主观评分分布情况。结果:不同重建图像试管周围和脑干的噪声、AI间两两比较差异均有统计学意义,其中FBP噪声和AI最大,MBIRNR40噪声和AI最小,MBIRSTND噪声和AI小于ASIR40(均P<0.05)。MBIRSTND和MBIRNR40图像后颅窝脑干亨氏暗区伪影减少,质量较好。MBIRSTND图像主观评分分布与FBP和ASIR40比较差异有统计学意义(Z=2.859、2.913,均P<0.05)。MBIRNR40图像主观评分分布与FBP和ASIR40比较差异亦有统计学意义(Z=2.836、2.850,均P<0.05)。MBIRSTND与MBIRNR40、FBP与ASIR40图像主观评分分布比较差异无统计学意义(均P>0.05)。结论:MBIR能够显著降低后颅窝脑实质图像噪声,抑制后颅窝伪影,提高后颅窝图像质量,特别是优化低密度对比设置的MBIRNR40。
Abstract:
Objective:To explore the value of model-based iterative reconstruction(MBIR)in reducing beam hardening artifacts in posterior fossa CT images.Methods:The blood vessel model containing 9 test tubes was scanned by energy spectrum CT under craniocerebral parameters,and the test tubes were filled with pure water,calcium solution,and 1,2,5,10,20,30 mgI/ml solution.After obtaining the original scan data,filter back projection(FBP),adaptive statistical iterative reconstruction(ASIR)40(40% ASIR and FBP mixed),MBIR standard setting(MBIRSTND)and optimized low-density contrast setting(MBIRNR40)were used to reconstruct the image with a layer thickness of 0.625 mm,and the area of interest was placed to measure the noise around the test tube,and the Artifact Index(AI)around the test tube with different densities was calculated.80 cases of patients with brain CT scans were randomly selected,and FBP,ASIR40,MBIRSTND,MBIRNR40 were used to reconstruct the image with a thickness of 0.625 mm,the most obvious layer of the Heinz dark area of the posterior fossa was selected,and the area of interest was placed to measure the noise of CT value in cerebellar white matter and brainstem,and the AI of the brainstem was calculated.The image was subjectively scored by the 5-point method.The noise and AI around the test tube with different reconstructed images were compared.Compare The distribution of brainstem noise,AI and subjective scores in the posterior fossa after different reconstructed images.Results:The noise and AI of different reconstructed images around the test tube and brainstem had statistically significant differences,Among them,FBP noise and AI were the largest,MBIRNR40 noise and AI were the smallest,MBIRSTND noise and AI were less than ASIR40(all P<0.05).The artifacts of the Heinz dark area of the posterior fossa in MBIRSTND and MBIRNR40 images were reduced,and the quality was better.The subjective score distribution of MBIRSTND images was significantly different from FBP and ASIR40(Z=2.859,2.913,both P<0.05).The subjective score distribution of MBIRNR40 images was also significantly different from FBP and ASIR40(Z=2.836,2.850,both P<0.05).There were no significant differences in the subjective score distribution of MBIRSTND and MBIRNR40,FBP and ASIR40 images(all P>0.05).Conclusion:MBIR can significantly reduce the image noise of brain parenchyma and suppress the artifacts in posterior fossa,and improve the image quality of the posterior fossa,especially for MBIRNR40.

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备注/Memo

备注/Memo:
基金项目:西安市科技计划项目(2019115413YX009SF042)
更新日期/Last Update: 2021-12-07