• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

全迭代重建和混合迭代重建以减少未抬高手臂扫描的腹部CT中的伪影。

Full and hybrid iterative reconstruction to reduce artifacts in abdominal CT for patients scanned without arm elevation.

作者信息

Yasaka Koichiro, Furuta Toshihiro, Kubo Takatoshi, Maeda Eriko, Katsura Masaki, Sato Jiro, Ohtomo Kuni

机构信息

1 Department of Radiology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.

2 Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

出版信息

Acta Radiol. 2017 Sep;58(9):1085-1093. doi: 10.1177/0284185116684675. Epub 2017 Jan 9.

DOI:10.1177/0284185116684675
PMID:28068822
Abstract

Background Abdominal computed tomography (CT) without arm elevation is associated with degraded image quality due to streak artifacts. Purpose To compare the degree of streak artifacts in abdominal CT images without arm elevation between full iterative reconstruction (IR), hybrid IR, and filtered back projection (FBP) using two commercially available scanners. Material and Methods First, a phantom study simulating CT examination without arm elevation was performed. Second, unenhanced axial images of 33 patients (17 and 16 patients for each vendor) who underwent CT without arm elevation were reconstructed with full IR, hybrid IR and FBP. A radiologist placed 50 parallel lines with lengths of 50 pixels vertical to the streaks and quantitatively evaluated the images for streak artifacts in the phantom study. Two radiologists evaluated the images of patients for streak artifacts (on the liver and the kidney) and diagnostic acceptability using a four-point scale. Results The phantom study indicated that full IR algorithms were more effective than FBP in reducing streak artifacts. In the clinical patient study, streak artifacts were significantly more reduced with full IR compared with FBP in both the liver and kidney ( P < 0.012). Streak artifact reduction was limited with hybrid IR. Model-based iterative reconstruction (MBIR) (one of the full IR algorithms) provided diagnostically more acceptable image quality ( P < 0.016) compared with FBP. Conclusion In abdominal CT without arm elevation, full IR enabled a more efficient streak artifact reduction compared with FBP and MBIR was associated with diagnostically more acceptable images.

摘要

背景

不抬高手臂进行腹部计算机断层扫描(CT)时,由于条纹伪影会导致图像质量下降。目的:使用两台商用扫描仪比较全迭代重建(IR)、混合IR和滤波反投影(FBP)在不抬高手臂的腹部CT图像中条纹伪影的程度。材料与方法:首先,进行一项模拟不抬高手臂的CT检查的体模研究。其次,对33例未抬高手臂进行CT检查的患者(每个供应商各17例和16例)的未增强轴向图像分别采用全IR、混合IR和FBP进行重建。一名放射科医生在体模研究中垂直于条纹放置50条长度为50像素的平行线,并对图像的条纹伪影进行定量评估。两名放射科医生使用四点量表对患者的图像(肝脏和肾脏上的)条纹伪影和诊断可接受性进行评估。结果:体模研究表明,全IR算法在减少条纹伪影方面比FBP更有效。在临床患者研究中,与FBP相比,全IR在肝脏和肾脏中均显著减少了条纹伪影(P < 0.012)。混合IR减少条纹伪影的效果有限。与FBP相比,基于模型的迭代重建(MBIR)(全IR算法之一)提供了诊断上更可接受的图像质量(P < 0.016)。结论:在不抬高手臂的腹部CT中,与FBP相比,全IR能更有效地减少条纹伪影,且MBIR与诊断上更可接受的图像相关。

相似文献

1
Full and hybrid iterative reconstruction to reduce artifacts in abdominal CT for patients scanned without arm elevation.全迭代重建和混合迭代重建以减少未抬高手臂扫描的腹部CT中的伪影。
Acta Radiol. 2017 Sep;58(9):1085-1093. doi: 10.1177/0284185116684675. Epub 2017 Jan 9.
2
Assessing the Effects of Deep Learning Reconstruction on Abdominal CT Without Arm Elevation.评估不抬手臂的腹部 CT 深度学习重建的效果。
Can Assoc Radiol J. 2023 Nov;74(4):688-694. doi: 10.1177/08465371231169672. Epub 2023 Apr 11.
3
Comparison of pure and hybrid iterative reconstruction techniques with conventional filtered back projection: image quality assessment in the cervicothoracic region.比较纯迭代和混合迭代重建技术与传统滤波反投影技术:颈胸区域的图像质量评估。
Eur J Radiol. 2013 Feb;82(2):356-60. doi: 10.1016/j.ejrad.2012.11.004. Epub 2012 Nov 27.
4
Model-based iterative reconstruction compared to adaptive statistical iterative reconstruction and filtered back-projection in CT of the kidneys and the adjacent retroperitoneum.基于模型的迭代重建与自适应统计迭代重建及滤波反投影在肾脏及相邻腹膜后CT成像中的比较。
Acad Radiol. 2014 Jun;21(6):774-84. doi: 10.1016/j.acra.2014.02.012.
5
Effects of pure and hybrid iterative reconstruction algorithms on high-resolution computed tomography in the evaluation of interstitial lung disease.纯迭代重建算法和混合迭代重建算法在间质性肺疾病高分辨率计算机断层扫描评估中的作用。
Eur J Radiol. 2017 Aug;93:243-251. doi: 10.1016/j.ejrad.2017.06.003. Epub 2017 Jun 4.
6
Ultra-low peak voltage CT colonography: effect of iterative reconstruction algorithms on performance of radiologists who use anthropomorphic colonic phantoms.超低峰值电压 CT 结肠成像:迭代重建算法对使用人体结肠模型的放射科医生性能的影响。
Radiology. 2014 Dec;273(3):759-71. doi: 10.1148/radiol.14140192. Epub 2014 Jul 11.
7
Ultra-low-dose CT of the lung: effect of iterative reconstruction techniques on image quality.肺部超低剂量CT:迭代重建技术对图像质量的影响。
Acad Radiol. 2014 Jun;21(6):695-703. doi: 10.1016/j.acra.2014.01.023. Epub 2014 Apr 6.
8
Assessment of a model-based, iterative reconstruction algorithm (MBIR) regarding image quality and dose reduction in liver computed tomography.基于模型的迭代重建算法(MBIR)在肝脏 CT 中对图像质量和剂量降低的评估。
Invest Radiol. 2013 Aug;48(8):598-606. doi: 10.1097/RLI.0b013e3182899104.
9
Filtered back projection, adaptive statistical iterative reconstruction, and a model-based iterative reconstruction in abdominal CT: an experimental clinical study.滤波反投影、自适应统计迭代重建和基于模型的迭代重建在腹部 CT 中的应用:一项实验性临床研究。
Radiology. 2013 Jan;266(1):197-206. doi: 10.1148/radiol.12112707. Epub 2012 Nov 20.
10
CT Dose Reduction for Visceral Adipose Tissue Measurement: Effects of Model-Based and Adaptive Statistical Iterative Reconstructions and Filtered Back Projection.CT 剂量降低在测量内脏脂肪组织中的应用:基于模型和自适应统计迭代重建以及滤波反投影的影响。
AJR Am J Roentgenol. 2015 Jun;204(6):W677-83. doi: 10.2214/AJR.14.13411.

引用本文的文献

1
Reducing motion artifacts in the aorta: super-resolution deep learning reconstruction with motion reduction algorithm.减少主动脉中的运动伪影:采用运动减少算法的超分辨率深度学习重建
Jpn J Radiol. 2025 Aug 9. doi: 10.1007/s11604-025-01849-8.
2
Metal artifact reduction combined with deep learning image reconstruction algorithm for CT image quality optimization: a phantom study.金属伪影减少与深度学习图像重建算法相结合用于CT图像质量优化:一项体模研究。
PeerJ. 2025 Jun 4;13:e19516. doi: 10.7717/peerj.19516. eCollection 2025.
3
[Deep Learning Reconstruction Algorithm Combined With Smart Metal Artifact Reduction Technique Improves Image Quality of Upper Abdominal CT in Critically Ill Patients].
[深度学习重建算法结合智能金属伪影减少技术改善危重症患者上腹部CT图像质量]
Sichuan Da Xue Xue Bao Yi Xue Ban. 2024 Nov 20;55(6):1403-1409. doi: 10.12182/20241160102.
4
Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions.人工智能在听力学中的应用:现状与未来方向的范围综述。
Sensors (Basel). 2024 Nov 6;24(22):7126. doi: 10.3390/s24227126.
5
Deep learning reconstruction for high-resolution computed tomography images of the temporal bone: comparison with hybrid iterative reconstruction.深度学习重建颞骨高分辨率 CT 图像:与混合迭代重建的比较。
Neuroradiology. 2024 Jul;66(7):1105-1112. doi: 10.1007/s00234-024-03330-1. Epub 2024 Mar 22.
6
Can deep learning improve image quality of low-dose CT: a prospective study in interstitial lung disease.深度学习能否提高低剂量 CT 图像质量:间质性肺疾病的前瞻性研究。
Eur Radiol. 2022 Dec;32(12):8140-8151. doi: 10.1007/s00330-022-08870-9. Epub 2022 Jun 24.
7
Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.基于深度学习的重建技术改善腹部超高分辨率 CT 图像质量:一项体模研究。
J Appl Clin Med Phys. 2021 Jul;22(7):286-296. doi: 10.1002/acm2.13318. Epub 2021 Jun 23.
8
Deep Learning-based CT Image Reconstruction: Initial Evaluation Targeting Hypovascular Hepatic Metastases.基于深度学习的CT图像重建:针对乏血供肝转移瘤的初步评估
Radiol Artif Intell. 2019 Oct 9;1(6):e180011. doi: 10.1148/ryai.2019180011. eCollection 2019 Nov.
9
Detection of fractures of hand and forearm in whole-body CT for suspected polytrauma in intubated patients.全身 CT 检测疑似多发创伤插管患者的手和前臂骨折。
BMC Musculoskelet Disord. 2020 Jan 22;21(1):49. doi: 10.1186/s12891-020-3068-0.
10
Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT.深度学习重建可提高腹部超高分辨率 CT 的图像质量。
Eur Radiol. 2019 Nov;29(11):6163-6171. doi: 10.1007/s00330-019-06170-3. Epub 2019 Apr 11.