Unbiased Filtered Back-Projection in 4π Compton Imaging With 3D Position Sensitive Detectors

被引:6
作者
Chu, Jiyang [1 ]
Streicher, Michael [1 ]
Fessler, Jeffrey A. [2 ]
He, Zhong [1 ]
机构
[1] Univ Michigan, Dept Nucl Engn & Radiol Sci, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
关键词
3D position-sensitive detector; Compton imaging; filtered back-projection; matrix decomposition; unbiased estimation; REGULARIZATION PARAMETER; CDZNTE DETECTOR; RESTORATION; RECONSTRUCTION; CAMERA; TRANSFORMS; ALGORITHMS; SELECTION;
D O I
10.1109/TNS.2016.2610980
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In Compton imaging, iterative methods provide good performance but are usually computationally intensive. Thus, direct inverse algorithms such as filtered back-projection (FBP) are preferable when computation time is limited. The conventional FBP method assumes that the point spread function of a back-projection image is isotropic and invariant to incident direction, as required by frequency spectrum analysis. However, most of the time this assumption is not true because the detector geometry is rarely uniform. Therefore the conventional FBP reconstructed image is biased. To solve the geometry non-uniformity problem, this paper proposes an unbiased FBP algorithm that groups Compton events having the same Compton rings using a system matrix decomposition strategy. The proposed method produces more isotropic resolution, and preserves the capability to use frequency spectrum analysis. The algorithm has been applied to data from a 3D position-sensitive detector array with 4 crystals and a digital readout system. The resulting images had more isotropic resolution than standard FBP.
引用
收藏
页码:2750 / 2756
页数:7
相关论文
共 25 条
[1]   ON SOME BAYESIAN REGULARIZATION METHODS FOR IMAGE-RESTORATION [J].
ARCHER, G ;
TITTERINGTON, DM .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 1995, 4 (07) :989-995
[2]   COMPUTING FOURIER-TRANSFORMS AND CONVOLUTIONS ON THE 2-SPHERE [J].
DRISCOLL, JR ;
HEALY, DM .
ADVANCES IN APPLIED MATHEMATICS, 1994, 15 (02) :202-250
[3]   Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation [J].
Galatsanos, Nikolas P. ;
Katsaggelos, Aggelos K. .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 1992, 1 (03) :322-336
[4]   A Filtered Back-Projection Algorithm for 4π Compton Camera Data [J].
Haefner, Andrew ;
Gunter, Donald ;
Barnowski, Ross ;
Vetter, Kai .
IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 2015, 62 (04) :1911-1917
[5]  
HALL P, 1987, J ROY STAT SOC B MET, V49, P184
[6]   IMAGE-RESTORATION USING GIBBS PRIORS - BOUNDARY MODELING, TREATMENT OF BLURRING, AND SELECTION OF HYPERPARAMETER [J].
JOHNSON, VE ;
WONG, WH ;
HU, XP ;
CHEN, CT .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1991, 13 (05) :413-425
[7]   A brief survey of bandwidth selection for density estimation [J].
Jones, MC ;
Marron, JS ;
Sheather, SJ .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1996, 91 (433) :401-407
[8]   About the Scattering of Radiation by free Electrons after the new relativistic Quantum dynamics of Dirac. [J].
Klein, O. ;
Nishina, Y. .
ZEITSCHRIFT FUR PHYSIK, 1929, 52 (11-12) :853-868
[9]   Fast spherical Fourier algorithms [J].
Kunis, S ;
Potts, D .
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2003, 161 (01) :75-98
[10]   4-π compton imaging using a 3-D position-sensitive CdZnTe detector via weighted list-mode maximum likelihood [J].
Lehner, CE ;
He, Z ;
Zhang, F .
IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 2004, 51 (04) :1618-1624