scholarly journals Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance

2014 ◽  
Vol 41 (7) ◽  
pp. 071911 ◽  
Author(s):  
Ke Li ◽  
John Garrett ◽  
Yongshuai Ge ◽  
Guang-Hong Chen
2015 ◽  
Vol 42 (9) ◽  
pp. 5209-5221 ◽  
Author(s):  
Ke Li ◽  
Daniel Gomez-Cardona ◽  
Jiang Hsieh ◽  
Meghan G. Lubner ◽  
Perry J. Pickhardt ◽  
...  

Modelling ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 78-104
Author(s):  
Vasili B. V. Nagarjuna ◽  
R. Vishnu Vardhan ◽  
Christophe Chesneau

Every day, new data must be analysed as well as possible in all areas of applied science, which requires the development of attractive statistical models, that is to say adapted to the context, easy to use and efficient. In this article, we innovate in this direction by proposing a new statistical model based on the functionalities of the sinusoidal transformation and power Lomax distribution. We thus introduce a new three-parameter survival distribution called sine power Lomax distribution. In a first approach, we present it theoretically and provide some of its significant properties. Then the practicality, utility and flexibility of the sine power Lomax model are demonstrated through a comprehensive simulation study, and the analysis of nine real datasets mainly from medicine and engineering. Based on relevant goodness of fit criteria, it is shown that the sine power Lomax model has a better fit to some of the existing Lomax-like distributions.


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