DrZ.ac

misplaced, punctuation

The Value of Multispectral Observations in Photon-limited Quantitative Tissue Analysis

[DOI]  [PDF

Abstract

Multispectral fluorescence data can be used within sparse decomposition methods to separate key cellular structures, even when the number of photons per spectral band is very small. However, there are two key costs associated with multispectral data acquisition: (a) for a fixed data acquisition time, increasing the number of spectral bands means decreasing the number of photons (and hence SNR) per band, and (b) the optical system becomes more complex and expensive. These costs lead to important tradeoffs between the information content and the noise of the observations. This paper describes a mathematical framework for assessing this tradeoff and supporting experimental results.

Citation

Z. T. Harmany, X. Jiang and R. M. Willett, “The value of multispectral observations in photon-limited quantitative tissue analysis”, in IEEE Statistical Signal Processing Workshop (SSP), 2012, 237–240.

BibTeX

@inproceedings{harmany-ssp2012-valuemultispectral,
  doi = {10.1109/SSP.2012.6319670},
  title = {The value of multispectral observations in photon-limited quantitative tissue analysis},
  author = {Harmany, Zachary T. and Jiang, Xin and Willett, Rebecca M.},
  booktitle = {IEEE Statistical Signal Processing Workshop (SSP)},
  month = {aug},
  year = {2012},
  pages = {237–240},
  abstract = {Multispectral fluorescence data can be used within sparse decomposition methods to separate key cellular structures, even when the number of photons per spectral band is very small. However, there are two key costs associated with multispectral data acquisition: (a) for a fixed data acquisition time, increasing the number of spectral bands means decreasing the number of photons (and hence SNR) per band, and (b) the optical system becomes more complex and expensive. These costs lead to important tradeoffs between the information content and the noise of the observations. This paper describes a mathematical framework for assessing this tradeoff and supporting experimental results.}
}