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首页 > 过刊浏览>2018年第29卷第7期 >2133-2151. DOI:10.13328/j.cnki.jos.005546
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CT投影采样策略对重建质量影响综述
作者:
作者简介:

杨富强(1985-),男,陕西西安人,博士,主要研究领域为CT理论与应用,计算机集成制造;高宗照(1993-),男,硕士,主要研究领域为CT理论与应用,计算机集成制造;张定华(1958-),男,博士,教授,博士生导师,CCF高级会员,主要研究领域为航空宇航先进制造技术,锥束CT,计算机图形图像处理;廖金明(1994-),男,硕士,主要研究领域为CT理论与应用,计算机集成制造;黄魁东(1978-),男,博士,副教授,主要研究领域为航空宇航先进制造技术,锥束CT,计算机图形图像处理.

通讯作者:

黄魁东,E-mail:kdhuang@nwpu.edu.cn

基金项目:

国家自然科学基金（51675437，51605389）；陕西省自然科学基础研究计划（2016JM5003）；西北工业大学研究生创意创新种子基金（Z2017021）


Review of the Effect of Computed Tomography Projection Sampling Strategy on Reconstruction Quality
Author:
Fund Project:

National Natural Science Foundation of China (51675437, 51605389); Natural Science Foundation Research Project of Shaanxi Province, China (2016JM5003); Graduate Starting Seed Fund of Northwestern Polytechnical University (Z2017021)

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    摘要:

    针对计算机断层成像（computed tomography，简称CT）中投影数据与图像重建关系，综述了CT在投影策略方面对重建质量的影响.对不同采样策略获取的不完全投影数据，应用迭代类算法对投影数据进行重建，研究了均匀采样和非均匀采样情况下不同数据结构对重建图像质量的影响.对仿真数据和实际数据重建结果进行分析，同时对不同策略下的投影数据结合其数据分布特点探讨了重建质量优劣的原因.可以为CT重建领域的研究工作者提供全面的采样方法梳理和总结，为当前不完全投影数据获取方式对应的算法改进提供思路，最后对当前研究重点和未来发展加以展望.

    Abstract:

    Computed tomography (CT) is an imaging technique which produces cross sectional map of object from its projections. Image reconstruction algorithms require collection of projections covering the whole measurement range. Incomplete projection is still a hot research topic. This paper reviews the relationship between projection data and image reconstruction in computed tomography, and summarizes the effect of computed tomography on reconstruction quality. For the incomplete projection data acquired by different sampling strategies, the iterative algorithm is used to reconstruct the projection data. The effects of different data structures on the reconstructed image quality under uniform sampling and non-uniform sampling are studied, and the results are compared and analyzed. Meanwhile, the reasons of the reconstruction quality of the pros and cons are discussed in conjunction with the projection data distribution with different strategies. This paper provides a comprehensive sampling method for researchers in the field of CT reconstruction, and offers some ideas for the improvement of the corresponding algorithm for incomplete projection data. Furthermore, it also points out current focus of the study and research direction in future.

    参考文献
    [1] Zhuang TZ. Principle and Algorithm of CT. Shanghai:Shanghai Jiaotong University Press, 1992. 77-97(in Chinese).
    [2] Yu Z, Thibault J, Bouman CA, Sauer K D, Hsieh J. Fast model-based x-ray CT reconstruction using spatially nonhomogeneous ICD optimization. IEEE Trans. on Image Processing, 2011,20(1):161-175.
    [3] Wu WW, Quan C, Liu FL. Filtered back-projection image reconstruction algorithm for opposite parallel linear CT scanning. Acta Optica Sinica, 2016,36(9):0911009(in Chinese with English abstract).
    [4] Tuy HK. Inversion formula for cone-beam reconstruction. SIAM Journal on Applied Mathematics, 1983,43(3):546-552.
    [5] Smith BD. Image reconstruction from cone-beam projections:Necessary and sufficient conditions and reconstruction methods. IEEE Trans. on Medical Imaging, 1985,4(1):14-25.
    [6] Ma JM, Zhang JM, Zhu GQ, Wang QS, Hang CC, Duan BJ. Total variation constrained iterative filtered back-projection CT reconstruction method. Acta Optica Sinica, 2015,35(2):234002(in Chinese with English abstract).
    [7] Wang XC, Yan B, Liu HK, Li L, Wei X, Hu GE. Efficient reconstruction from truncated data in circular cone-beam CT. Acta Physica Sinica, 2013,62(9):098702(in Chinese with English abstract).
    [8] Yu H, Wang G. Compressed sensing based interior tomography. Physics in Medicine & Biology, 2009,54(9):2791-2805.
    [9] Ritschl L. Method for recording a complete projection data set in the central layer for CT reconstruction using a C-Arm X-Ray apparatus with a limited rotation range. US20150049856, 2017-5-23.
    [10] Yang FQ, Zhang DH, Huang KD, Wang K, Xu Z. Review of reconstruction algorithms with incomplete projection data of computed tomography. Acta Physica Sinica, 2014,63(5):58701(in Chinese with English abstract).
    [11] Wang LY, Liu HK, Li L, Yan B, Zhang HM, Cai AL, Chen JL, Hu GE. Review of sparse optimization-based computed tomography image reconstruction from few-view projections. Acta Physica Sinica, 2014,63(20):15-24(in Chinese with English abstract).
    [12] Zou Y, Pan X. Exact image reconstruction on PI-lines from minimum data in helical cone-beam CT. Physics in Medicine & Biology, 2004,49(6):941-959.
    [13] Pack JD, Noo F, Clackdoyle R. Cone-Beam reconstruction using the back-projection of locally filtered projections. IEEE Trans. on Medical Imaging, 2005,24(1):70-85.
    [14] Yu L, Zou Y, Sidky EY, Pelizzari CA, Munro P, Pan XC. Region of interest reconstruction from truncated data in circular cone-beam CT. IEEE Trans. on Medical Imaging, 2005,25(7):869-881.
    [15] Cho S, Pearson E, Pelizzari CA, Pan XC. Region-of-Interest image reconstruction with intensity weighting in circular cone-beam CT for image-guided radiation therapy. Medical Physics, 2009,36(4):1184-1192.
    [16] Guo J, Zeng L, Zou X. An improved half-covered helical cone-beam CT reconstruction algorithm based on localized reconstruction filter. Journal of X-Ray Science and Technology, 2011,19(3):293-312.
    [17] Kong H, Pan J. A projection access scheme based on prime number increment for cone-beam iterative reconstruction. Lecture Notes in Electrical Engineering, 2011,87:179-185.
    [18] Herman GT, Meyer LB. Algebraic reconstruction techniques can be made computationally efficient positron emission tomography application. IEEE Trans. on Medical Imaging, 1993,12(3):600-609.
    [19] Mueller K, Yagel R, Cornhill JF. The weighted-distance scheme:A globally optimizing projection ordering method for ART. IEEE Trans. on Medical Imaging, 1997,16(2):223-230.
    [20] Guan H, Gordon R. A projection access order for speedy convergence of ART (algebraic reconstruction technique):A multilevel scheme for computed tomography. Physics in Medicine and Biology, 1994,39(11):2005-2022.
    [21] Liu Y, Wang J, Fan Y, Liang Z. Noise study on cone-beam CT FDK image reconstruction by improved area-simulating-volume technique. SPIE Medical Imaging, 2014, 903339.
    [22] Baek J, Pelc NJ. Local and global 3D noise power spectrum in cone-beam CT system with FDK reconstruction. Medical Physics, 2011,38(4):2122-2131.
    [23] Shi H, Luo S. A novel scheme to design the filter for CT reconstruction using FBP algorithm. BioMedical Engineering OnLine, 2013,12(1):1-15.
    [24] Ma J, Chen W. An improved exact FBP algorithm for image reconstruction in cone-beam helical CT. In:Proc. of the Int'l Conf. on Computational Intelligence and Security. 2006. 1635-1640.
    [25] Demircan-Tureyen E, Kamasak ME. A compressed sensing based approach on discrete algebraic reconstruction technique. In:Proc. of the IEEE Engineering in Medicine and Biology. IEEE, 2015. 7494.
    [26] Park JC, Song B, Kim JS, Park SH, Kim HK, Liu Z, Suh TS, Song WY. Fast compressed sensing-based CBCT reconstruction using Barzilai-Borwein formulation for application to on-line IGRT. Medical Physics, 2012,39(3):1207-1217.
    [27] Hashemi S, Beheshti S, Gill PR, Paul NS, Cobbold RSC. Accelerated compressed sensing based CT image reconstruction. Computational & Mathematical Methods in Medicine, 2015,(2):161797.
    [28] Bian J, Siewerdsen JH, Han X, Sidky EY, Prince JL, Pelizzari CA, Pan XC. Evaluation of sparse-view reconstruction from flat-panel-detector cone-beam CT. Physics in Medicine and Biology, 2010,55(22):6575-6599.
    [29] Chen P, Pan JX, Liu B. Simulation arithmetic of X-CT projection based on consecutive spectrum. Nondestructive Testing, 2009,31(2):102-104(in Chinese with English abstract).
    [30] Huang KD, Zhang DH, Li MJ, Zhang H. Image lag modeling and correction method for flat panel detector in cone-beam CT. Acta Physica Sinica, 2013,62(21):210702(in Chinese with English abstract).
    [31] Wang LY. Research on algorithms for cone-beam CT image reconstruction from limited view projections[MS. Thesis]. Zhengshou:The PLA Information Engineering University, 2010. 9-24(in Chinese with English abstract).
    [32] Chen LJ. Medical CT image reconstruction based on framework of Lambda tomography[Ph.D. Thesis]. Guangzhou:Southern Medical University, 2008. 17-30(in Chinese with English abstract).
    [33] Ma J, Liang Z, Fan Y, Liu Y, Huang J, Li LH, Chen WF, Lu HB. Variance estimation of x-ray CT sinogram in radon domain. Proc. of the SPIE-The Int'l Society for Optical Engineering, 2012,8313(2):145-150.
    [34] Jing W, Lu H, Liang Z, Eremina D, Zhang GX, Wang S, Chen J, Manzione J. An experimental study on the noise properties of X-ray CT sinogram data in radon space. Physics in Medicine & Biology, 2008,53(12):3327.
    [35] Zhang SL, Zhang DH, Zhao QB, Wang K. Research on ART of image reconstruction method for ICT. Nondestructive Testing, 2007,29(8):453-456(in Chinese with English abstract).
    [36] Liu Y, Hong S, Zhang Q, Zhu H, Shu H, Gui Z. Median prior constrained TV algorithm for sparse view low-dose CT reconstruction. Computers in Biology & Medicine, 2015,60(C):117-131.
    [37] Shangguan H, Liu Y, Cui X, Bai YJ, Zhang Q, Gui ZG. Sparse-View statistical iterative head CT image reconstruction via joint regularization. Int'l Journal of Imaging Systems & Technology, 2016,26(1):3-14.
    [38] Niu S, Gao Y, Bian Z, Huang J, Chen W, Yu G, Liang Z, Ma J. Sparse-View x-ray CT reconstruction via total generalized variation regularization. Physics in Medicine & Biology, 2014,59(12):2997-3017.
    [39] Sidky EY, Pan X. Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization. Physics in Medicine & Biology, 2008,53(17):4777-4807.
    [40] Zeng L, Guo JQ, Liu BD. Limited-Angle cone-beam computed tomography image reconstruction by total variation minimization and piecewise-constant modification. Journal of Inverse and Ill-Posed Problems, 2013,21(6):735-754.
    [41] Chen ZQ, Jin X, Li L, Wang G. A limited-angle CT reconstruction method based on anisotropic TV minimization. Physics in Medicine and Biology, 2013,58(7):2119-2141.
    [42] Guo J, Qi H, Xu Y, Chen ZJ, Li SL, Zhou LH. Iterative image reconstruction for limited-angle CT using optimized initial image. Computational & Mathematical Methods in Medicine, 2016,2016(3):1-9.
    [43] Abbas S, Min J, Cho S. Super-Sparsely view-sampled cone-beam CT by incorporating prior data. Journal of X-Ray Science and Technology, 2013,21(1):71-83.
    [44] Yazdanpanah AP, Regentova E, Bebis G. Algebraic iterative reconstruction-reprojection (AIRR) method for high performance sparse-view CT reconstruction. Applied Mathematics & Information Sciences, 2016,10(6):1-8.
    [45] Courdurier M, Noo F, Defrise M, Kudo H. Solving the interior problem of computed tomography using a priori knowledge. Inverse Problem, 2008,24(6):1-27.
    [46] Lu X Q, Sun Y. Limited angle computed tomography reconstruction algorithm based on multiplicative regularization method. Acta Optica Sinica, 2010,30(5):1285-1290(in Chinese with English abstract).
    [47] Guerrero ME, Jacobs R, Loubele M, Schutyser F, Suetens P, van Steenberghe D. State-of-the-Art on cone beam CT imaging for preoperative planning of implant placement. Clinical Oral Investigations, 2006,10(1):1-7.
    [48] Yu H, Wang G. SART-Type half-threshold filtering approach for ct reconstruction. IEEE Access, 2017,2:602-613.
    [49] Gregor J, Lenox M, Bingham P, Arrowood L. Multi-Core cluster implementation of SIRT with application to cone beam micro-CT. In:Proc. of the Nuclear Science Symp. Conf. Record. IEEE, 2009. 4120-4125.
    [50] Candes EJ, Romberg J, Tao T. Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information. IEEE Trans. on Information Theory, 2006,52(2):489-509.
    [51] Donoho DL. Compressed sensing. IEEE Trans. on Information Theory, 2006,52(4):1289-1306.
    [52] Wang DX, Liu QJ, Liu SL. Algorithm study for L2,1-norm minimization problems. Journal of Fuzhou University, 2013,(1):12-14(in Chinese with English abstract).
    [53] Boyd S, Parikh N, Chu E, Peleato B, Eckstein J. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations & Trends in Machine Learning, 2010,3(1):1-122.
    [54] http://www.caam.rice.edu/~optimization/L1/TVAL3/
    [55] Deng L. Research on the imaging technologies for short scan in cone beam CT[MS. Thesis]. Zhengzhou:The PLA Information Engineering University, 2015. 1-7(in Chinese with English abstract).
    [56] Sun YS, Zhang LY. Research of variable step-size constant modulus medical CT image blind equalization algorithm based on mean square error. Computer Engineering & Applications, 2011,47(31):164-166(in Chinese with English abstract).
    [57] Pirahansiah F, Norul HS, Sahran S. Peak signal-to-noise ratio based on threshold method for image segmentation. In:Proc. of the 2010 Int'l Conf. on Computer Applications and Industrial Electronics (ICCAIE). IEEE, 2013. 468-472.
    [58] He L, Zhang Q, Shangguan H, Zhang F, Zhang PC, Liu Y, Sun WY, Gui ZG. Adaptive total generalized variation denoising algorithm for low-dose CT images. Journal of Computer Applications, 2016,36(1):243-247(in Chinese with English abstract).
    [59] Quinto ET. Tomographic reconstructions for incomplete data-numerical inversion of the exterior Radon transform. Inverse Problems, 1988,4(3):867-876.
    [60] Gao H, Luo Y, Chen K, Ma G, Wu LX. An image reconstruction model and hybrid algorithm for limited-angle projection data. In:Proc. of the IEEE Int'l Conf. on Bioinformatics and Biomedicine. IEEE, 2015. 405-408.
    [61] Xu Q. Statistical reconstruction methods for insufficient X-ray CT projection data[Ph.D. Thesis]. Xi'an:Xi'an Jiaotong University, 2012. 5-10(in Chinese with English abstract).
    [62] Chang M, Xiao YS, Chen ZQ. DART-TV:A high precision reconstruction algorithm for discrete tomography. In:Proc. of the National Digital Radiography and CT New Technology Seminar. 2014. 227-233(in Chinese with English abstract).
    [63] Jiang BY, Tang J, Li PM, Gong NX, Qian H, Lu YP. High energy X-ray industrial CT technology and its application in automotive industry. In:Proc. of the Annual Conf. of the National Nondestructive Testing. 2013. 913-917(in Chinese with English abstract).
    [64] Zhao JL. The study of CT image fusion and reconstruction based on graded variable voltage[MS. Thesis]. Taiyuan:North University of China, 2016. 14-21(in Chinese with English abstract).
    [65] Maestre-Deusto FJ, Scavello G, Pizarro J, Galindo PL. ADART:An adaptive algebraic reconstruction algorithm for discrete tomography. IEEE Trans. on Image Processing, 2011,20(8):2146-2152.
    [66] Batenburg K, Sijbers J. DART:A practical reconstruction algorithm for discrete tomography. IEEE Trans. on Image Processing A Publication of the IEEE Signal Processing Society, 2011,20(9):2542-2553.
    [67] Kovarik L, Stevens A, Li A, Browning DN. Implementing an accurate and rapid sparse sampling approach for low-dose atomic resolution STEM imaging. Applied Physics Letters, 2016,109(16):164102.
    [68] Abbas S, Lee T, Shin S, Lee R, Cho S. Effects of sparse sampling schemes on image quality in low-dose CT. Medical Physics, 2013,40(11):111915.
    [69] Rui X, Cheng L, Long Y, Fu L, Alessio AM, Asma E, Kinahan PE, De Man B. Ultra-Low dose CT attenuation correction for PET/CT:Analysis of sparse view data acquisition and reconstruction algorithms. Physics in Medicine & Biology, 2015,60(19):7437-7460.
    [70] Mao BL, Chen XZ, Xiao DY, Fan SY, Teng YY, Kang Y. Ordered subset image reconstruction studied by means of total variation minimization and fast first-order method in low dose computed tomography. Acta Physica Sinica, 2014,63(13):138701(in Chinese with English abstract).
    [71] Li J, Sun Y. L1-Norm-Based differential phase-contrast computerized tomography reconstruction algorithm with sparse angular resolution. Acta Optica Sinica, 2012,32(3):311002(in Chinese with English abstract).
    [72] Huang KD, Xu Z, Zhang DH, Zhang H, Shi WL. Robust scatter correction method for cone-beam CT using an interlacing-slit plate. Chinese Physics C, 2016,40(6):95-102.
    附中文参考文献:
    [1] 庄天戈.CT原理与算法.上海:上海交通大学出版社,1992.77-97.
    [3] 伍伟文,全超,刘丰林.相对平行直线扫描CT滤波反投影图像重建.光学学报,2016,36(9):0911009.
    [6] 马继明,张建奇,宋顾周,王群书,韩长材,段宝军.全变分约束迭代滤波反投影CT重建.光学学报,2015,35(2):234002.
    [7] 汪先超,闫镔,刘宏奎,李磊,魏星,胡国恩.一种圆轨迹锥束CT中截断投影数据的高效重建算法.物理学报,2013,62(9):98702.
    [10] 杨富强,张定华,黄魁东,王鹍,徐哲.CT不完全投影数据重建算法综述.物理学报,2014,63(5):58701.
    [11] 王林元,刘宏奎,李磊,闫镔,张瀚铭,蔡爱龙,陈建林,胡国恩.基于稀疏优化的计算机断层成像图像不完全角度重建综述.物理学报,2014,63(20):15-24.
    [29] 陈平,潘晋孝,刘宾.连续能谱X-CT投影仿真算法.无损检测,2009,31(2):102-104.
    [30] 黄魁东,张定华,李明君,张华.锥束CT平板探测器成像的余晖建模与校正方法.物理学报,2013,62(21):210702.
    [31] 王林元.锥束CT有限角度三维重建算法研究[硕士学位论文].郑州:解放军信息工程大学,2010.9-24.
    [32] 陈凌剑.Lambda Tomography框架下的医学CT图像重建[博士学位论文].广州:南方医科大学,2008.17-30.
    [35] 张顺利,张定华,赵歆波,王凯.工业CT图像重建的ART算法研究.无损检测,2007,29(8):453-456.
    [46] 卢孝强,孙怡.基于乘性正则化的有限角度CT重建算法.光学学报,2010,30(5):1285-1290.
    [52] 王东霞,刘秋菊,刘书伦.一种L2,1范数最小化问题的算法研究.福州大学学报,2013,(1):12-14.
    [55] 邓林.锥束CT短扫描成像技术研究[硕士学位论文].郑州:解放军信息工程大学,2015.1-7.
    [56] 孙云山,张立毅,段继忠.均方误差控制步长恒模医学CT图像盲均衡算法.计算机工程与应用,2011,47(31):164-166.
    [58] 何琳,张权,上官宏,张芳,张鹏程,刘祎,孙未雅,桂志国.低剂量CT图像的自适应广义总变分降噪算法.计算机应用,2016,36(1):243-247.
    [61] 许琼.X线CT不完备投影数据统计重建研究[博士学位论文].西安:西安交通大学,2012.5-10.
    [62] 常铭,肖永顺,陈志强.DART-TV:高精度离散断层图像重建算法.见:全国射线数字成像与CT新技术研讨会.2014.227-233.
    [63] 江宝宇,汤建,李普明,龚宁湘,钱海,卢艳平.高能X射线工业CT技术在汽车工业中的应用.见:全国无损检测学术年会.2013. 913-917.
    [64] 赵晋利.递变电压CT图像融合重建研究[硕士学位论文].太原:中北大学,2016.14-21.
    [70] 毛宝林,陈晓朝,孝大宇,康雁.基于全变分最小化和快速一阶方法的低剂量CT有序子集图像重建.物理学报,2014,63(13):138701.
    [71] 李镜,孙怡.基于L1范数的微分相位衬度CT稀疏角度重建算法.光学学报,2012,32(3):311002.
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杨富强,张定华,黄魁东,高宗照,廖金明. CT投影采样策略对重建质量影响综述.软件学报,2018,29(7):2133-2151

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