• 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

相似文献

1
Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction.提高数字乳腺断层合成的图像质量:一种基于自动检测和扩散的减少金属伪影方法。
Phys Med Biol. 2017 Sep 15;62(19):7765-7783. doi: 10.1088/1361-6560/aa8803.
2
A diffusion-based truncated projection artifact reduction method for iterative digital breast tomosynthesis reconstruction.基于扩散的截断投影伪影减少方法在迭代数字乳腺断层合成重建中的应用。
Phys Med Biol. 2013 Feb 7;58(3):569-87. doi: 10.1088/0031-9155/58/3/569. Epub 2013 Jan 14.
3
Image quality of microcalcifications in digital breast tomosynthesis: effects of projection-view distributions.数字乳腺断层合成中微钙化的图像质量:投影视角分布的影响。
Med Phys. 2011 Oct;38(10):5703-12. doi: 10.1118/1.3637492.
4
Voting strategy for artifact reduction in digital breast tomosynthesis.数字乳腺断层合成中减少伪影的投票策略。
Med Phys. 2006 Jul;33(7):2461-71. doi: 10.1118/1.2207127.
5
High-attenuation artifact reduction in breast tomosynthesis using a novel reconstruction algorithm.使用新型重建算法减少乳腺断层合成中的高衰减伪影。
Eur J Radiol. 2019 Jul;116:21-26. doi: 10.1016/j.ejrad.2019.04.014. Epub 2019 Apr 23.
6
Segmented separable footprint projector for digital breast tomosynthesis and its application for subpixel reconstruction.用于数字乳腺断层合成的分段可分离式足迹投影仪及其在亚像素重建中的应用
Med Phys. 2017 Mar;44(3):986-1001. doi: 10.1002/mp.12092.
7
A novel pre-processing technique for improving image quality in digital breast tomosynthesis.一种用于提高数字乳腺断层合成图像质量的新型预处理技术。
Med Phys. 2017 Feb;44(2):417-425. doi: 10.1002/mp.12078. Epub 2017 Feb 2.
8
A new projection correction based voting strategy for breast calcification artifact reduction.一种基于新投影校正的投票策略,用于减少乳腺钙化伪影。
Phys Med Biol. 2023 Sep 11;68(18). doi: 10.1088/1361-6560/acf093.
9
Developing breast lesion detection algorithms for digital breast tomosynthesis: Leveraging false positive findings.开发数字乳腺断层合成中的乳腺病变检测算法:利用假阳性发现。
Med Phys. 2022 Dec;49(12):7596-7608. doi: 10.1002/mp.15883. Epub 2022 Aug 19.
10
Evaluation of a new image reconstruction method for digital breast tomosynthesis: effects on the visibility of breast lesions and breast density.数字乳腺断层合成新技术图像重建方法的评估:对乳腺病变和乳腺密度可见度的影响。
Br J Radiol. 2019 Nov;92(1103):20190345. doi: 10.1259/bjr.20190345. Epub 2019 Sep 5.

引用本文的文献

1
Image Quality Enhancement for Digital Breast Tomosynthesis: High-Density Object Artifact Reduction.数字乳腺断层合成图像质量增强:高密度物体伪影减少。
J Imaging Inform Med. 2024 Oct;37(5):2649-2661. doi: 10.1007/s10278-024-01084-z. Epub 2024 Mar 27.
2
Model-based deep CNN-regularized reconstruction for digital breast tomosynthesis with a task-based CNN image assessment approach.基于模型的深度卷积神经网络正则化重建在基于任务的卷积神经网络图像评估方法下的数字乳腺断层合成
Phys Med Biol. 2023 Dec 13;68(24):245024. doi: 10.1088/1361-6560/ad0eb4.

本文引用的文献

1
Computer-aided detection of retained surgical needles from postoperative radiographs.术后X光片中手术遗留针的计算机辅助检测
Med Phys. 2017 Jan;44(1):180-191. doi: 10.1002/mp.12011. Epub 2017 Jan 3.
2
Breast cancer screening with tomosynthesis (3D mammography) with acquired or synthetic 2D mammography compared with 2D mammography alone (STORM-2): a population-based prospective study.与单纯二维钼靶(2D 钼靶)相比,采用获得性或合成二维钼靶(2D 钼靶)的断层合成乳腺 X 线摄影术(3D 乳腺 X 线摄影术)进行乳腺癌筛查(STORM-2):一项基于人群的前瞻性研究。
Lancet Oncol. 2016 Aug;17(8):1105-1113. doi: 10.1016/S1470-2045(16)30101-2. Epub 2016 Jun 23.
3
Breast cancer screening using tomosynthesis in combination with digital mammography compared to digital mammography alone: a cohort study within the PROSPR consortium.与单纯数字乳腺摄影相比,使用断层合成技术联合数字乳腺摄影进行乳腺癌筛查:PROSPR联盟内的一项队列研究。
Breast Cancer Res Treat. 2016 Feb;156(1):109-16. doi: 10.1007/s10549-016-3695-1. Epub 2016 Mar 1.
4
Digital breast tomosynthesis (DBT): a review of the evidence for use as a screening tool.数字乳腺断层合成(DBT):用作筛查工具的证据综述。
Clin Radiol. 2016 Feb;71(2):141-50. doi: 10.1016/j.crad.2015.11.008. Epub 2015 Dec 23.
5
Computer-aided detection system for clustered microcalcifications in digital breast tomosynthesis using joint information from volumetric and planar projection images.利用容积图像和平面投影图像的联合信息对数字乳腺断层合成中的簇状微钙化进行计算机辅助检测的系统。
Phys Med Biol. 2015 Nov 7;60(21):8457-79. doi: 10.1088/0031-9155/60/21/8457. Epub 2015 Oct 14.
6
Increased Cancer Detection Rate and Variations in the Recall Rate Resulting from Implementation of 3D Digital Breast Tomosynthesis into a Population-based Screening Program.将三维数字化乳腺断层合成技术应用于基于人群的筛查项目后,癌症检出率提高及召回率出现差异。
Radiology. 2016 Mar;278(3):698-706. doi: 10.1148/radiol.2015142036. Epub 2015 Oct 9.
7
Computer aided detection of surgical retained foreign object for prevention.用于预防手术中遗留异物的计算机辅助检测
Med Phys. 2015 Mar;42(3):1213-22. doi: 10.1118/1.4907964.
8
Multiscale bilateral filtering for improving image quality in digital breast tomosynthesis.用于改善数字乳腺断层合成中图像质量的多尺度双边滤波
Med Phys. 2015 Jan;42(1):182-95. doi: 10.1118/1.4903283.
9
Digital breast tomosynthesis: studies of the effects of acquisition geometry on contrast-to-noise ratio and observer preference of low-contrast objects in breast phantom images.数字乳腺断层合成:乳腺体模图像中采集几何结构对对比度噪声比及低对比度物体观察者偏好影响的研究
Phys Med Biol. 2014 Oct 7;59(19):5883-902. doi: 10.1088/0031-9155/59/19/5883. Epub 2014 Sep 11.
10
Early clinical experience with digital breast tomosynthesis for screening mammography.数字乳腺断层合成筛查钼靶的早期临床经验。
Radiology. 2015 Jan;274(1):85-92. doi: 10.1148/radiol.14131319. Epub 2014 Sep 1.

提高数字乳腺断层合成的图像质量:一种基于自动检测和扩散的减少金属伪影方法。

Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction.

作者信息

Lu Yao, Chan Heang-Ping, Wei Jun, Hadjiiski Lubomir M, Samala Ravi K

出版信息

Phys Med Biol. 2017 Sep 15;62(19):7765-7783. doi: 10.1088/1361-6560/aa8803.

DOI:10.1088/1361-6560/aa8803
PMID:28832336
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5735824/
Abstract

In digital breast tomosynthesis (DBT), the high-attenuation metallic clips marking a previous biopsy site in the breast cause errors in the estimation of attenuation along the ray paths intersecting the markers during reconstruction, which result in interplane and inplane artifacts obscuring the visibility of subtle lesions. We proposed a new metal artifact reduction (MAR) method to improve image quality. Our method uses automatic detection and segmentation to generate a marker location map for each projection (PV). A voting technique based on the geometric correlation among different PVs is designed to reduce false positives (FPs) and to label the pixels on the PVs and the voxels in the imaged volume that represent the location and shape of the markers. An iterative diffusion method replaces the labeled pixels on the PVs with estimated tissue intensity from the neighboring regions while preserving the original pixel values in the neighboring regions. The inpainted PVs are then used for DBT reconstruction. The markers are repainted on the reconstructed DBT slices for radiologists' information. The MAR method is independent of reconstruction techniques or acquisition geometry. For the training set, the method achieved 100% success rate with one FP in 19 views. For the test set, the success rate by view was 97.2% for core biopsy microclips and 66.7% for clusters of large post-lumpectomy markers with a total of 10 FPs in 58 views. All FPs were large dense benign calcifications that also generated artifacts if they were not corrected by MAR. For the views with successful detection, the metal artifacts were reduced to a level that was not visually apparent in the reconstructed slices. The visibility of breast lesions obscured by the reconstruction artifacts from the metallic markers was restored.

摘要

在数字乳腺断层合成(DBT)中,标记乳腺先前活检部位的高衰减金属夹会在重建过程中导致沿与标记相交的射线路径的衰减估计出现误差,从而产生层间和层内伪影,模糊细微病变的可见性。我们提出了一种新的金属伪影减少(MAR)方法来提高图像质量。我们的方法使用自动检测和分割为每个投影(PV)生成标记位置图。设计了一种基于不同PV之间几何相关性的投票技术,以减少误报(FP),并标记PV上的像素以及成像体积中代表标记位置和形状的体素。一种迭代扩散方法用来自相邻区域的估计组织强度替换PV上标记的像素,同时保留相邻区域中的原始像素值。然后将修复后的PV用于DBT重建。标记会重新绘制在重建的DBT切片上,以供放射科医生参考。MAR方法独立于重建技术或采集几何结构。对于训练集,该方法在19个视图中实现了100%的成功率,仅有1个FP。对于测试集,对于核心活检微夹,按视图计算的成功率为97.2%,对于乳房肿瘤切除术后大标记簇,成功率为66.7%,在58个视图中共有10个FP。所有FP均为大的致密良性钙化,如果不通过MAR进行校正,也会产生伪影。对于成功检测的视图,金属伪影减少到在重建切片中肉眼不可见的程度。被金属标记的重建伪影遮挡的乳腺病变的可见性得以恢复。