A Maximum Likelihood method for lifetime estimation in photon counting-based Fluorescence Lifetime Imaging Microscopy

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Abstract

In this paper we derive a Maximum Likelihood (ML) framework for photon counting-based fluorescence lifetime estimation in Fluorescence Lifetime Imaging Microscopy (FLIM) from the biophysical phenomenon and instrument models. Data collected at a given pixel consist of photon counts exponentially decreasing along time and are assumed to follow Poisson statistics. Both pointwise approaches and a neighborhood-wise approach are proposed to take explicitly into account the spatial correlation of data. Evaluations and comparisons are presented on simulated as well as on experimental biological image data.

Original languageEnglish
Title of host publication2013 Proceedings of the 21st European Signal Processing Conference, EUSIPCO 2013
PublisherEuropean Signal Processing Conference, EUSIPCO
ISBN (Print)9780992862602
Publication statusPublished - 1 Jan 2013
Event2013 21st European Signal Processing Conference, EUSIPCO 2013 - Marrakech, Morocco
Duration: 9 Sept 201313 Sept 2013

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491

Conference

Conference2013 21st European Signal Processing Conference, EUSIPCO 2013
Country/TerritoryMorocco
CityMarrakech
Period9/09/1313/09/13

Keywords

  • Photon counting
  • Poisson statistics
  • fluorescence microscopy
  • liftetime estimation

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