• DocumentCode
    1044325
  • Title

    A Statistical Approach to Inverting the Born Ratio

  • Author

    Hyde, Damon ; Miller, Eric ; Brooks, Dana H. ; Ntziachristos, Vasilis

  • Author_Institution
    Northeastern Univ., Boston
  • Volume
    26
  • Issue
    7
  • fYear
    2007
  • fDate
    7/1/2007 12:00:00 AM
  • Firstpage
    893
  • Lastpage
    905
  • Abstract
    We examine the problem of fluorescence molecular tomography using the normalized Born approximation, termed herein the Born ratio, from a statistical perspective. Experimentally verified noise models for received signals at the excitation and emission wavelengths are combined to generate a stochastic model for the Born ratio. This model is then utilized within a maximum likelihood framework to obtain an inverse solution based on a fixed point iteration. Results are presented for three experimental scenarios: phantom data with a homogeneous background, phantoms implanted within a small animal, and in vivo data using an exogenous probe.
  • Keywords
    biomedical optical imaging; fluorescence; inverse problems; maximum likelihood estimation; medical image processing; optical tomography; phantoms; Born ratio; exogenous probe; fixed point iteration; fluorescence molecular tomography; inverse problems; maximum likelihood estimation; noise model; normalized Born approximation; phantoms; Animals; Approximation methods; Fluorescence; Imaging phantoms; Noise generators; Scattering; Signal generators; Signal to noise ratio; Stochastic resonance; Tomography; Fluorescence; inverse problems; optical imaging; Algorithms; Animals; Computer Simulation; Data Interpretation, Statistical; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Mammary Neoplasms, Experimental; Mice; Mice, Transgenic; Microscopy, Fluorescence; Models, Biological; Models, Statistical; Reproducibility of Results; Sensitivity and Specificity; Tomography, Optical;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2007.895467
  • Filename
    4265749