Likelihood Inference for Particle Location in Fluorescence Microscopy
Open Access
Author:
Hughes, John
Graduate Program:
Statistics
Degree:
Master of Science
Document Type:
Master Thesis
Date of Defense:
None
Committee Members:
John Fricks, Thesis Advisor/Co-Advisor John Fricks, Thesis Advisor/Co-Advisor
Keywords:
organelle particle tracking fluorescence microscopy Poisson random field maximum likelihood methods molecular motor nanotechnology
Abstract:
We introduce a procedure to automatically count and locate the fuorescent 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 making the stochastic model for certain fluorescence images more explicit and by employing a consistent framework for analysis.
