New filtered back-projection algorithm

doi:10.3778/j.issn.1002-8331.2009.32.005

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (32): 16-18.DOI: 10.3778/j.issn.1002-8331.2009.32.005

• 博士论坛 • Previous Articles Next Articles

New filtered back-projection algorithm

WANG Bao-ping¹，ZHANG Lin-xi¹，FAN Jiu-lun²，XIE Wei-xin³

1.National Key Laboratory of UVA Specialty Technique，Northwestern Polytechnical University，Xi’an 710072，China
2.Department of Information and Control，Xi’an Institute of Post and Telecommunications，Xi’an 710061，China
3.Institute of Information Engineering，Shenzhen University，Shenzhen，Guangdong 518060，China

Received:2008-12-17 Revised:2009-09-21 Online:2009-11-11 Published:2009-11-11
Contact: WANG Bao-ping

新的滤波-逆投影成像算法

王保平¹，张麟兮¹，范九伦²，谢维信³

1.西北工业大学无人机特种技术国防科技重点实验室，西安 710072
2.西安邮电学院信控系，西安 710061
3.深圳大学信息工程学院，广东深圳 518060

通讯作者: 王保平

Abstract

Abstract: The filtered back-projection algorithm is relatively perfect algorithm in turntable imaging，it is widely used in CT and signal processing.The time frequency coupling of the algorithm is neglected，so making imaging quality descend.A new filtered back-projection algorithm is proposed.The new method is tested by using practice measure data and simulating data，the experimentation results show that the new algorithm is effective.

Key words: time frequency coupling, filtered back-projection, imaging

摘要： 滤波-逆投影是一种公认的比较理想的转台成像方法，广泛应用于很多领域。但该算法忽略了时频耦合问题，使其成像效果受到了一定的影响。为此，提出了一种新型的滤波-逆投影算法。经过实验分析对比，证明了新算法的有效性。

关键词: 时频耦合, 滤波-逆投影, 成像

CLC Number:

TN911.23

WANG Bao-ping¹，ZHANG Lin-xi¹，FAN Jiu-lun²，XIE Wei-xin³. New filtered back-projection algorithm[J]. Computer Engineering and Applications, 2009, 45(32): 16-18.

王保平¹，张麟兮¹，范九伦²，谢维信³. 新的滤波-逆投影成像算法[J]. 计算机工程与应用, 2009, 45(32): 16-18.

[1]	LU Lixia, ZOU Junzhong, GUO Yucheng, ZHANG Jian, WANG Bei. Prediction of Knee Injury Based on Multimodal Fusion [J]. Computer Engineering and Applications, 2021, 57(9): 225-232.
[2]	ZHENG Kun, KONG Jiangping, ZHOU Jing, CI Kangyi, CHANG Peng. Review of iPPG and Application of Physiological Parameter Detection in Education [J]. Computer Engineering and Applications, 2021, 57(5): 25-35.
[3]	NI Zongjun, CHEN Hui, ZHANG Yun, SU Min, ZHENG Xiujuan. Non-contact Physiological Parameter Estimation Method Based on Adaptive Denoising [J]. Computer Engineering and Applications, 2021, 57(5): 153-160.
[4]	GAO Jin, ZHAO Yunpeng, Godfred Kim Mensah, LI Xinyun, LIU Zhifen, CHEN Junjie, GUO Hao. Research on Spatial Dynamics Analysis and Classification of Resting-State Functional Brain Connections [J]. Computer Engineering and Applications, 2021, 57(2): 150-155.
[5]	LU Xiaoling, WU Haifeng, ZENG Yu, KONG Lingxu, LUO Jinling. 3D Transfer Learning Network for Classification of Alzheimer’s Disease [J]. Computer Engineering and Applications, 2021, 57(16): 253-262.
[6]	ZHANG Shanshan, ZHAO Jianhua. Through-the-Wall Radar Imaging Algorithm Based on Inexact Augmented Lagrange Multiplier [J]. Computer Engineering and Applications, 2021, 57(11): 77-83.
[7]	WANG Gongshu, REN Zunxiao, LI Dandan, XIANG Jie, WANG Bin. Analysis and Application Research of Brain Activation Task Differentiation [J]. Computer Engineering and Applications, 2020, 56(21): 272-278.
[8]	ZHOU Qin1, ADU Jianhua1, YIN Lixue2, ZHANG Hongmei2, CUI Wei2, ZENG Qiang1. Recent Advances and Prospects on Left Ventricular Segmentation Method Based on MRI [J]. Computer Engineering and Applications, 2019, 55(2): 28-35.
[9]	LIU Xiaohui, ZHANG Xinyuan, LU Lijun, FENG Qianjin, CHEN Wufan. Proximal iterative reconstruction algorithm for MR images based on primal-dual framework [J]. Computer Engineering and Applications, 2018, 54(8): 28-35.
[10]	XIAO Meihua, LI Wei, LI Yanan, MEI Yingtian. Security communication framework of DICOM protocol based on PACS cloud [J]. Computer Engineering and Applications, 2018, 54(7): 107-113.
[11]	ZHAO Haifeng, XIA Guofeng, SONG Weiming, ZHANG Shaojie. Brain MR image segmentation under strong noise interference [J]. Computer Engineering and Applications, 2018, 54(6): 183-187.
[12]	SUN Lilei1，2, XU Yong3. Research on classification method of mammography based on deep learning [J]. Computer Engineering and Applications, 2018, 54(21): 13-19.
[13]	ZHANG Fan, CHEN Junjie, GUO Hao. Machine learning classification method combining multiple features of brain function hyper-network [J]. Computer Engineering and Applications, 2018, 54(21): 120-127.
[14]	JIA Wenjuan1, WANG Shuihua1, ZHANG Yudong2. Survey on imaging based pathological brain detection [J]. Computer Engineering and Applications, 2018, 54(11): 21-29.
[15]	WANG Yongxin1，2, DIAO Ming1, HAN Chuang2. Underwater image enhancement and color correction model based on homomorphic filter [J]. Computer Engineering and Applications, 2018, 54(11): 30-34.

New filtered back-projection algorithm

新的滤波-逆投影成像算法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics