Image reconstruction of multiphoton microscopy data

  • Authors:

  • Jared M. Doot;Kevin W. Eliceiri;Robert D. Nowak;Rebecca Willett

  • Affiliations:

  • University of Wisconsin-Madison, Electrical and Computer Engineering, Madison, WI;University of Wisconsin-Madison, Electrical and Computer Engineering, Madison, WI;University of Wisconsin-Madison, Electrical and Computer Engineering, Madison, WI;Duke University, Electrical and Computer Engineering, Durham, NC

  • Venue:
  • ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
  • Year:
  • 2009

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Abstract

The techniques introduced in this paper allow for accurate multiscale image reconstruction of multi-photon microscopy data. Multiphoton microscopy (MPM) is a tool for the non-invasive imaging of living organisms and tissue. The data acquired using this technique can contain information about the position, excited state lifetime, and spectra of the observed photons. The small number of photons collected, however, limits the quality of the reconstruction. The multiscale framework in this paper results in an accurate representation of both the intensity and excited state lifetime information. Using a multiscale reconstruction approach based on a penalized likelihood function, the underlying image is more accurately represented as compared to a naive aggregate binning approach.