The deviation from Poisson statistics in PET data could be described by the Conway-Maxwell-Poisson (CMP) distribution model, which is characterized by the centring parameter 2 and the dispersion parameter nu, the latter quantifying the deviation from a Poisson distribution model. In particular, the parameter nu allows quantifying over-dispersion (nu < 1) or under-dispersion (nu > 1) of data. A simple and efficient method for lambda and nu parameters estimation is introduced and assessed using Monte Carlo simulation for a wide range of activity values.
A Conway-Maxwell-Poisson (CMP) model to address data dispersion on positron emission tomography
Santarelli Maria Filomena;Landini Luigi
2016
Abstract
The deviation from Poisson statistics in PET data could be described by the Conway-Maxwell-Poisson (CMP) distribution model, which is characterized by the centring parameter 2 and the dispersion parameter nu, the latter quantifying the deviation from a Poisson distribution model. In particular, the parameter nu allows quantifying over-dispersion (nu < 1) or under-dispersion (nu > 1) of data. A simple and efficient method for lambda and nu parameters estimation is introduced and assessed using Monte Carlo simulation for a wide range of activity values.File in questo prodotto:
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