1.Progress on the clinical applications and pharmacological effects of Cuscuta chinensis in the treatment of ocular diseases
Beijing ZHU ; Teng ZHANG ; Yu CHEN
Journal of Pharmaceutical Practice 2020;38(5):409-412
Cuscuta chinensis is a commonly used traditional Chinese herbal medicine. Cuscuta chinensis has a long history of clinical application in the treatment of varieties of ocular diseases. This review summarized the literatures related to its clinical applications, research progresses in the ophthalmic pharmacology and active ingredients. It was aimed to provide a theoretical basis for the further development and utilization of Cuscuta Chinensis as an effective medication.
2.Brain functional network reconstruction based on compressed sensing and fast iterative shrinkage-thresholding algorithm.
Qing GUO ; Yueyang TENG ; Can TONG ; Disen LI ; Xuefei WANG
Journal of Biomedical Engineering 2020;37(5):855-862
The construction of brain functional network based on resting-state functional magnetic resonance imaging (fMRI) is an effective method to reveal the mechanism of human brain operation, but the common brain functional network generally contains a lot of noise, which leads to wrong analysis results. In this paper, the least absolute shrinkage and selection operator (LASSO) model in compressed sensing is used to reconstruct the brain functional network. This model uses the sparsity of
Algorithms
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Brain/diagnostic imaging*
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Humans
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Image Processing, Computer-Assisted
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Magnetic Resonance Imaging
3.The acceleration algorithm for projection decomposition of dual-energy computed tomography image reconstruction based on projection matching.
Xiaowen HOU ; Zipeng LU ; Yueyang TENG ; Dayu XIAO ; Shengyu FAN ; Chaoran YANG ; Yujia LIU ; Yan KANG
Journal of Biomedical Engineering 2018;35(3):376-383
Dual-energy computed tomography (CT) reconstruction imaging technology is an important development direction in the field of CT imaging. The mainstream model of dual-energy CT reconstruction algorithm is the basis material decomposition model, and the projection decomposition is the crucial technique. The projection decomposition algorithm based on projection matching was a general method. With establishing the energy spectrum lookup table, we can obtain the stable solution by the least squares matching method. But the computation cost will increase dramatically when size of lookup table enlarges and it will slow down the computer. In this paper, an acceleration algorithm based on projection matching is proposed. The proposed algorithm makes use of linear equations and plane equations to fit the lookup table data, so that the projection value of the decomposition coefficients can be calculated quickly. As the result of simulation experiment, the acceleration algorithm can greatly shorten the running time of the program to get the stable and correct solution.