  We introduce a procedure to automatically count and locate the fluorescent
particles in a microscopy image. Our procedure employs an approximate
likelihood estimator derived from a Poisson random field model for photon
emission. Estimates of standard errors are generated for each image along with
the parameter estimates, and the number of particles in the image is determined
using an information criterion and likelihood ratio tests. Realistic
simulations show that our procedure is robust and that it leads to accurate
estimates, both of parameters and of standard errors. This approach improves on
previous ad hoc least squares procedures by giving a more explicit stochastic
model for certain fluorescence images and by employing a consistent framework
for analysis.
