Abstract

In an earlier paper, we derived the distribution of the number of photons detected in two-photon laser scanning microscopy when the counter has a dead period. We assumed a Poisson number of emissions, exponential waiting times, and an infinite time horizon, and used an equivalent inhomogeneous Poisson process formulation. We then used that result to improve image quality as measured by the signal-to-noise ratio. Here, we extend that study in two directions. First, we treat the finite-horizon case to assess the accuracy of the simpler infinite-horizon approximation. Second, we use a direct approach by conditioning on the Poisson count for the infinite-horizon case to derive several polynomial identities.

Highlights

  • Two-photon laser scanning microscopy (TPLSM) is a valuable tool for imaging living tissues

  • In our earlier work [13], the distribution of D was derived by using inhomogeneous Poisson approach under the infinite time period assumption

  • We obtain the distribution of D using an equivalent approaches by using lengthy analysis of the order statistics formula

Read more

Summary

Introduction

Two-photon laser scanning microscopy (TPLSM) is a valuable tool for imaging living tissues. In an earlier paper [13], we used standard model assumptions [7]: Poisson with mean α for the number of photons emitted, exponential emission waiting times (fluorescence lifetimes), and a fixed (standardized) dead period δ upon registration of a photon. In [13] we used this inhomogeneous Poisson process approach to obtain the exact distribution of the number of photons detected, D, for an infinite time horizon.

Distribution of D for a finite horizon
Polynomial identities arising in photon counting problems
Assumptions
Deriving distribution of D using alternate approach
Conclusions

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.