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本文引用的文献

1
Prior image constrained compressed sensing: implementation and performance evaluation.先验图像约束压缩感知:实现与性能评估。
Med Phys. 2012 Jan;39(1):66-80. doi: 10.1118/1.3666946.
2
Time-resolved interventional cardiac C-arm cone-beam CT: an application of the PICCS algorithm.时分辨介入心脏病学 C 臂锥形束 CT:PICCS 算法的应用。
IEEE Trans Med Imaging. 2012 Apr;31(4):907-23. doi: 10.1109/TMI.2011.2172951. Epub 2011 Oct 20.
3
New approaches to region of interest computed tomography.感兴趣区 CT 新方法。
Med Phys. 2011 Jun;38(6):2868-78. doi: 10.1118/1.3583696.
4
Effects of the penalty on the penalized weighted least-squares image reconstruction for low-dose CBCT.受罚加权最小二乘图像重建对低剂量 CBCT 的影响。
Phys Med Biol. 2011 Sep 7;56(17):5535-52. doi: 10.1088/0031-9155/56/17/006. Epub 2011 Aug 3.
5
Nonconvex prior image constrained compressed sensing (NCPICCS): theory and simulations on perfusion CT.非凸先验图像约束压缩感知 (NCPICCS):灌注 CT 的理论与模拟。
Med Phys. 2011 Apr;38(4):2157-67. doi: 10.1118/1.3560878.
6
Reconstruction from truncated projections using mixed extrapolations of exponential and quadratic functions.利用指数和二次函数的混合外推法从截断投影中重建。
J Xray Sci Technol. 2011;19(2):155-72. doi: 10.3233/XST-2011-0284.
7
Interior region-of-interest reconstruction using a small, nearly piecewise constant subregion.使用小的、几乎分段常数的子区域进行内部感兴趣区域重建。
Med Phys. 2011 Mar;38(3):1307-12. doi: 10.1118/1.3549763.
8
Reduced image noise at low-dose multidetector CT of the abdomen with prior image constrained compressed sensing algorithm.基于先验图像约束的压缩感知算法降低腹部低剂量多层 CT 图像噪声。
Radiology. 2011 Jul;260(1):248-56. doi: 10.1148/radiol.11101380. Epub 2011 Mar 24.
9
Improved total variation-based CT image reconstruction applied to clinical data.基于改进全变差的 CT 图像重建应用于临床数据。
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10
Comparison of extended field-of-view reconstructions in C-arm flat-detector CT using patient size, shape or attenuation information.比较使用患者大小、形状或衰减信息的 C 臂平板探测器 CT 的扩展视野重建。
Phys Med Biol. 2011 Jan 7;56(1):39-56. doi: 10.1088/0031-9155/56/1/003. Epub 2010 Nov 30.

使用基于先验图像约束的压缩感知(PICCS)算法从完全截断的投影中重建时间分辨的心脏介入锥形束 CT。

Time-resolved cardiac interventional cone-beam CT reconstruction from fully truncated projections using the prior image constrained compressed sensing (PICCS) algorithm.

机构信息

Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA.

出版信息

Phys Med Biol. 2012 May 7;57(9):2461-76. doi: 10.1088/0031-9155/57/9/2461. Epub 2012 Apr 5.

DOI:10.1088/0031-9155/57/9/2461
PMID:22481501
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3350644/
Abstract

C-arm cone-beam CT could replace preoperative multi-detector CT scans in the cardiac interventional setting. However, cardiac gating results in view angle undersampling and the small size of the detector results in projection data truncation. These problems are incompatible with conventional tomographic reconstruction algorithms. In this paper, the prior image constrained compressed sensing (PICCS) reconstruction method was adapted to solve these issues. The performance of the proposed method was compared to that of FDK, FDK with extrapolated projection data (E-FDK), and total variation-based compressed sensing. A canine projection dataset acquired using a clinical C-arm imaging system supplied realistic cardiac motion and anatomy for this evaluation. Three different levels of truncation were simulated. The relative root mean squared error and the universal image quality index were used to quantify the reconstruction accuracy. Three main conclusions were reached. (1) The adapted version of the PICCS algorithm offered the highest image quality and reconstruction accuracy. (2) No meaningful variation in performance was observed when the amount of truncation was changed. (3) This study showed evidence that accurate interior tomography with an undersampled acquisition is possible for realistic objects if a prior image with minimal artifacts is available.

摘要

C 臂锥形束 CT 可在心脏介入环境中替代术前多探测器 CT 扫描。然而,心脏门控导致视场角欠采样,探测器的小尺寸导致投影数据截断。这些问题与传统的层析重建算法不兼容。在本文中,采用了先验图像约束压缩感知(PICCS)重建方法来解决这些问题。将所提出的方法的性能与 FDK、具有外推投影数据的 FDK(E-FDK)和基于全变差的压缩感知进行了比较。使用临床 C 臂成像系统获取的犬科投影数据集为该评估提供了真实的心脏运动和解剖结构。模拟了三种不同程度的截断。使用相对均方根误差和通用图像质量指数来量化重建准确性。得出了三个主要结论。(1) 经改编的 PICCS 算法提供了最高的图像质量和重建准确性。(2) 当截断量发生变化时,性能没有明显变化。(3) 本研究表明,如果有最小伪影的先验图像可用,则对于真实物体,使用欠采样采集进行准确的内部层析是可能的。