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Wavelength Optimization for Quantitative Spectral Imaging of Breast Tumor Margins

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  • Justin Y Lo
  • J Quincy Brown
  • Sulochana Dhar
  • Bing Yu
  • Gregory M Palmer
  • Nan M Jokerst
  • Nirmala Ramanujam

Abstract

A wavelength selection method that combines an inverse Monte Carlo model of reflectance and a genetic algorithm for global optimization was developed for the application of spectral imaging of breast tumor margins. The selection of wavelengths impacts system design in cost, size, and accuracy of tissue quantitation. The minimum number of wavelengths required for the accurate quantitation of tissue optical properties is 8, with diminishing gains for additional wavelengths. The resulting wavelength choices for the specific probe geometry used for the breast tumor margin spectral imaging application were tested in an independent pathology-confirmed ex vivo breast tissue data set and in tissue-mimicking phantoms. In breast tissue, the optical endpoints (hemoglobin, β-carotene, and scattering) that provide the contrast between normal and malignant tissue specimens are extracted with the optimized 8-wavelength set with

Suggested Citation

  • Justin Y Lo & J Quincy Brown & Sulochana Dhar & Bing Yu & Gregory M Palmer & Nan M Jokerst & Nirmala Ramanujam, 2013. "Wavelength Optimization for Quantitative Spectral Imaging of Breast Tumor Margins," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-13, April.
    • Handle: RePEc:plo:pone00:0061767
    DOI: 10.1371/journal.pone.0061767
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