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Meng F, Shi Y, Li C, Li L, Qin W, Zhu S. Hybrid model of photon propagation based on the analytical and Monte Carlo methods for a dual-head PET system. Phys Med Biol 2021; 66. [PMID: 34330106 DOI: 10.1088/1361-6560/ac195b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Accepted: 07/30/2021] [Indexed: 11/12/2022]
Abstract
The construction of photon propagation has a close relationship with the quality of reconstructed images. The classical Monte Carlo (MC) based method can model the photon propagation precisely, but it is time-consuming. The analytical method can often quickly construct a model, but its precision is a problem. How to fully exploit the advantages of the MC simulation and analytical model is an open problem. Inspired by the characteristics of the depth of interaction (DOI) detectors, which can help confirm the deposited position of a photon with DOI-encoding technology, we virtually discretize each crystal into several subcrystals to obtain the statistical distribution by MC-based simulation. Then, the statistical distribution is combined with a spatially variant solid-angle model. This combination strategy provides a hybrid model to describe photon propagation with relatively high accuracy and low computational cost. Three discretization schemes are compared to optimize the constructed photon propagation model. Several experiments are carried out to evaluate the performance of the proposed hybrid method. The metrics of full width at half maximum (FWHM), contrast recovery (CR), and coefficient of variation (COV) are adopted to quantitate the imaging results. The classical MC-based method is compared as a gold-standard reference. When a crystal is divided into two discretized positions, the convergent tendencies of CRs and COVs are consistent with that based on MC simulation method, respectively. In terms of FWHMs, the resolutions of using the MC-based model and the proposed hybrid model are 0.71 mm and 0.68 mm in the direction parallel to the detector head, respectively. This indicates the potential of the proposed method in positron emission tomography imaging.
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Affiliation(s)
- Fanzhen Meng
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Yu Shi
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Chenfeng Li
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Lei Li
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Wei Qin
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
| | - Shouping Zhu
- Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, People's Republic of China
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Meng F, Zhu S, Cheng J, Cao X, Qin W, Liang J. System Response Matrix Calculation Based on Distance-Driven Model and Solid Angle Model for Dual-Head PET System. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2020. [DOI: 10.1109/trpms.2019.2926580] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Meng F, Wang J, Zhu S, Cheng J, Liang J, Tian J. Comparison of GPU reconstruction based on different symmetries for dual-head PET. Med Phys 2019; 46:2696-2708. [PMID: 30994186 PMCID: PMC6850059 DOI: 10.1002/mp.13529] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 03/04/2019] [Accepted: 03/25/2019] [Indexed: 11/17/2022] Open
Abstract
Purpose Dual‐head positron emission tomography (PET) scanners have increasingly attracted the attention of many researchers. However, with the compact geometry, the depth‐of‐interaction blurring will reduce the image resolution considerably. Monte Carlo (MC)‐based system response matrix (SRM) is able to describe the physical process of PET imaging accurately and improve reconstruction quality significantly. The MC‐based SRM is large and precomputed, which leads to a longer image reconstruction time with indexing and retrieving precomputed system matrix elements. In this study, we proposed a GPU acceleration algorithm to accelerate the iterative reconstruction. Methods It has been demonstrated that the line‐of‐response (LOR)‐based symmetry and the Graphics Processing Unit (GPU) technology can accelerate the reconstruction tremendously. LOR‐based symmetry is suitable for the forward projection calculation, but not for the backprojection. In this study, we proposed a GPU acceleration algorithm that combined the LOR‐based symmetry and voxel‐based symmetry together, in which the LOR‐based symmetry is responsible for the forward projection, and the voxel‐based symmetry is used for the backprojection. Results Simulation and real experiments verify the efficiency of the algorithm. Compared with the CPU‐based calculation, the acceleration ratios of the forward projection and the backprojection operation are 130 and 110, respectively. The total acceleration ratio is 113×. In order to compare the acceleration effect of the different symmetries, we realized the reconstruction with the voxel‐based symmetry and the LOR‐based symmetry strategies. Compared with the LOR‐based GPU reconstruction, the acceleration ratio is 3.5×. Compared with the voxel‐based GPU reconstruction, the acceleration ratio is 12×. Conclusion We have proposed a new acceleration algorithm for the dual‐head PET system, in which both the forward and backprojection operations are accelerated by GPU.
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Affiliation(s)
- Fanzhen Meng
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China
| | - Jianxun Wang
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China
| | - Shouping Zhu
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China
| | - Jian Cheng
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China
| | - Jimin Liang
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China
| | - Jie Tian
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China.,Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
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Meng F, Cao X, Cao X, Wang J, Li L, Chen X, Zhu S, Liang J. Influence of Rotation Increments on Imaging Performance for a Rotatory Dual-Head PET System. BIOMED RESEARCH INTERNATIONAL 2017; 2017:8615086. [PMID: 28154827 PMCID: PMC5244751 DOI: 10.1155/2017/8615086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Revised: 11/15/2016] [Accepted: 12/07/2016] [Indexed: 12/02/2022]
Abstract
For a rotatory dual-head positron emission tomography (PET) system, how to determine the rotation increments is an open problem. In this study, we simulated the characteristics of a rotatory dual-head PET system. The influences of different rotation increments were compared and analyzed. Based on this simulation, the imaging performance of a prototype system was verified. A reconstruction flowchart was proposed based on a precalculated system response matrix (SRM). The SRM made the relationships between the voxels and lines of response (LORs) fixed; therefore, we added the interpolation method into the flowchart. Five metrics, including spatial resolution, normalized mean squared error (NMSE), peak signal-to-noise ratio (PSNR), contrast-to-noise (CNR), and structure similarity (SSIM), were applied to assess the reconstructed image quality. The results indicated that the 60° rotation increments with the bilinear interpolation had advantages in resolution, PSNR, NMSE, and SSIM. In terms of CNR, the 90° rotation increments were better than other increments. In addition, the reconstructed images of 90° rotation increments were also flatter than that of 60° increments. Therefore, both the 60° and 90° rotation increments could be used in the real experiments, and which one to choose may depend on the application requirement.
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Affiliation(s)
- Fanzhen Meng
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Xu Cao
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Xuezhou Cao
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Jianxun Wang
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Liang Li
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Xueli Chen
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Shouping Zhu
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Jimin Liang
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
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