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Activity Number: 347 - Contributed Poster Presentations: Section on Statistics in Imaging
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Imaging
Abstract #324713
Title: Modeling and Estimating the Behavior of Photo-Switching Fluorophores in Super-Resolution
Author(s): Lekha Patel* and Edward Cohen
Companies: Imperial College London and Imperial College London
Keywords: Super-resolution ; Imaging ; Hidden Markov Models ; Stochastic Processes ; Estimation ; Signal Processing
Abstract:

Imaging through Super-resolution microscopy allows experimenters to go beyond classical resolution limits in order to image cellular objects at the nanometer scale. The success of super-resolution lies in the stochasticity of a photoswitchable fluorophore's (light emitting molecule) photon emission state allowing sparse subsets of molecules to be accurately imaged. While a spatial point pattern of molecular positions can be revealed using localizations collected across time, multiple blinks from each fluorophore can lead to misrepresentations of their spatial characteristics, which can be alleviated by identifying and inferring upon this photoswitching behavior. We model its true photon emission state as an arbitrary (m+3)-state continuous time homogeneous Markov process with an absorbing state for photo-bleaching. This process motivates a derivation of the observed discrete time imaged process indicating whether or not a fluorophore is seen in a given frame. A novel likelihood based procedure for estimating the underlying transition rates is discussed by formulating a Hidden Markov Model (HMM). We finally show through a simulation study the effectiveness of our estimation method.


Authors who are presenting talks have a * after their name.

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