Estimating Rate Parameters in Super-Resolution Imaging via Hidden Continuous Markov Chains with Discretized Emissions

ShikunNie

UBC

"Estimating Rate Parameters in Super-Resolution Imaging via Hidden Continuous Markov Chains with Discretized Emissions"

In this talk, I will illustrate how to model the dynamics of the fluorophores used in single-molecule localization microscopy (SMLM) as a hidden Markov chain with discretized emissions. I will generalize the proposed models in literature into a simple framework model. With the 3-state model as a particular example of our general formulation, I will show the process to obtain the transmission matrix by constructing a system of linear inhomogeneous transport partial differential equations (PDEs), which is solved by repeated Laplace-Inverse Laplace transforms. To demonstrate the usefulness of the transmission matrix, we designed two simple algorithms to solve the inference problem of the transition rates. In conclusion, the general formation is widely applicable to various techniques in SMLM, representative of the SMLM camera and adaptable to solve other active research problems such as molecule counting problems.
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