  Metabolic imaging with PET/CT using $^{18}$F-Fludeoxyglucose ($^{18}$F-FDG)
as well as other imaging biomarkers has achieved wide acceptance in oncology,
cardiology and neurology not only because of the unique metabolic information
generated by this modality, but also because of its ability to quantify
biological processes. However, PET quantification is affected by many technical
and physiologic factors, and then recognized as an important problem for
diagnosis, determination of prognosis, and response monitoring in oncology. In
this work, we investigated the effect of reduced PET emission count statistics
on the accuracy and precision of tracer quantification, and proposed
Inhomogeneous Poisson Process Parameter Estimation (I3PE) method. In I3PE
method, we modelled the coincidence event as Inhomogeneous Poisson Process, and
estimate its parameter directly from the streaming listmode data. To evaluate
the effectiveness, a experiment using $^{18}$F-FDG was implemented on
LIGHTNING. The results not only demonstrate I3PE method, but also evaluated the
minimal detectable activity of the using PET machine. According $0.3\%$ mean
error rate criterion, LIGHTNING can detect several nano-Curie, cooperated with
I3PE method.
