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Multiple helical scans and the reconstruction of over FOV-sized objects in cone-beam CT 被引量:1
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作者 韩玉 闫镔 +3 位作者 李磊 宇超群 李建新 包尚联 《Chinese Physics B》 SCIE EI CAS CSCD 2012年第6期588-594,共7页
In cone-beam computed tomography (CBCT), there are often cases where the size of the specimen is larger than the field of view (FOV) (referred to as over FOV-sized (OFS)). To acquire the complete projection da... In cone-beam computed tomography (CBCT), there are often cases where the size of the specimen is larger than the field of view (FOV) (referred to as over FOV-sized (OFS)). To acquire the complete projection data for OFS objects, some scan modes have been developed for long objects and short but over-wide objects. However, these modes still cannot meet the requirements for both longitudinally long and transversely wide objects. In this paper, we propose a multiple helical scan mode and a corresponding reconstruction algorithm for both longitudinally long and transversely wide objects. The simulation results show that our model can deal with the problem and that the results are acceptable, while the OFS object is twice as long compared with the FOV in the same latitude. 展开更多
关键词 large object multiple helical scans reconstruction algorithm cone-beam computed to-mography
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Scalable X-ray scintillators with bright singlet-triplet hybrid self-trapping excitons
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作者 Shi-Yu Song Chao-Jun Gao +7 位作者 Rui Zhou Bing-Zhe Wang Wen-Bo Zhao Qing Cao Yan-Wei Hu Lin Dong Kai-Kai Liu Chong-Xin Shan 《Light(Science & Applications)》 2025年第9期2616-2627,共12页
Size-scalable X-ray scintillators with high transparency and robust photon yield allow for imaging large objects with greater precision and detail.Solution-processable scintillators,typically crafted from quantum dots... Size-scalable X-ray scintillators with high transparency and robust photon yield allow for imaging large objects with greater precision and detail.Solution-processable scintillators,typically crafted from quantum dots(QDs),are promising candidates for highly efficient scintillation applications.However,the restricted size and low transparency in QD-based scintillators lead to less efficient X-ray imaging for large objects requiring high resolution.Herein,we demonstrate a meter-scale ZnO QD scintillator with a visible range transmittance exceeding 96%,featuring bright singlet-triplet hybrid self-trapping excitons(STEs).The quantum yields(QYs)of singlet excitons and triplet excitons are 44.7%and 26.3%.Benefiting from a large Stokes shift and bright triplet excitons,the scintillator has a negligible self-absorption and elevated photon yields.Additionally,the scintillator exhibits exchange invariance,demonstrating identical optical performance upon exchanging the coordinates(r)of the QDs.Featuring bright singlet-triplet hybrid STEs and high transparency,the scintillator achieves high resolution X-ray imaging of 42-line pairs per millimeter(42 lp mm^(-1))at a meter scale.Moreover,demonstrations of 5000 cm^(2) X-ray imaging and real-time dynamic X-ray imaging are presented.The lowest detectable dose rate for X-ray detection is as low as 37.63±0.4 nGy s^(-1).This work presents a novel sizable and transparent scintillator with bright singlet-triplet hybrid STEs,showcasing their potential in high-resolution and sizable object X-ray imaging. 展开更多
关键词 quantum dots zno qd scintillator high transparency quantum dots qds imaging large objects scalable scintillators photon yield singlet triplet hybrid self trapping excitons
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Point cloud simplification algorithm based on particle swarm optimization for online measurement of stored bulk grain 被引量:3
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作者 Shao Qing Xu Tao +3 位作者 Yoshino Tatsuo Zhao Yujie Yang Wenting Zhu Hang 《International Journal of Agricultural and Biological Engineering》 SCIE EI CAS 2016年第1期71-78,共8页
The simplification of 3D laser scanning point cloud is an important step of surface reconstruction and volume estimation of bulk grain in granary.This study presented an adaptive simplification algorithm based on part... The simplification of 3D laser scanning point cloud is an important step of surface reconstruction and volume estimation of bulk grain in granary.This study presented an adaptive simplification algorithm based on particle swarm optimization(PSO).It introduced PSO into the average distance method,a conventional simplification method.The basic idea of this algorithm was to adaptively determine the optimal point reducing intervals of scanning lines according to original point cloud density by PSO.By using the 3D point cloud scanned from bulk grain surface in granary,the proposed algorithm was validated.Compared with the average distance method,the proposed algorithm obtained more evenly distributed point set,smaller reduction ratio(6.96%)and higher volume estimation accuracy(relative error was less than 3‰).The 3D laser scanner(GSLS003,Jilin University and SkyViTech Co.,Ltd.,Hangzhou,China)used in this study could scan the complete picture of the grain surface in a granary in one time,so the acquired point cloud data do not have to be jointed.For the good simplification performance and capability of updating the reducing interval at any moment,the proposed algorithm and the 3D laser scanner could be used to realize online real-time measurement of stored bulk grain volume in granary. 展开更多
关键词 point cloud simplification algorithm particle swarm optimization(PSO) 3D laser scanning large object stored grain
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