Estimating skin blood saturation by selecting a subset of hyperspectral imaging data

Maria Ewerlöf; E. Göran Salerud; Tomas Strömberg; Marcus Larsson

doi:10.1117/12.2075292

2 March 2015 Estimating skin blood saturation by selecting a subset of hyperspectral imaging data

Maria Ewerlöf, E. Göran Salerud, Tomas Strömberg, Marcus Larsson

Proceedings Volume 9328, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XIII; 93280J (2015) https://doi.org/10.1117/12.2075292
Event: SPIE BiOS, 2015, San Francisco, California, United States

Abstract

Skin blood haemoglobin saturation (𝑠_b) can be estimated with hyperspectral imaging using the wavelength (λ) range of 450-700 nm where haemoglobin absorption displays distinct spectral characteristics. Depending on the image size and photon transport algorithm, computations may be demanding. Therefore, this work aims to evaluate subsets with a reduced number of wavelengths for 𝑠_b estimation. White Monte Carlo simulations are performed using a two-layered tissue model with discrete values for epidermal thickness (𝑇_epi) and the reduced scattering coefficient (μ'_s ), mimicking an imaging setup. A detected intensity look-up table is calculated for a range of model parameter values relevant to human skin, adding absorption effects in the post-processing. Skin model parameters, including absorbers, are; μ'_s (λ), 𝑇_epi, haemoglobin saturation (𝑠_b), tissue fraction blood (𝑐_b) and tissue fraction melanin (𝑐_mel). The skin model paired with the look-up table allow spectra to be calculated swiftly. Three inverse models with varying number of free parameters are evaluated: A(𝑠_b, 𝑐_b), B(𝑠_b, 𝑐_b, 𝑐_mel) and C(all parameters free). Fourteen wavelength candidates are selected by analysing the maximal spectral sensitivity to 𝑠_b and minimizing the sensitivity to 𝑐_b. All possible combinations of these candidates with three, four and 14 wavelengths, as well as the full spectral range, are evaluated for estimating 𝑠_b for 1000 randomly generated evaluation spectra. The results show that the simplified models A and B estimated 𝑠_b accurately using four wavelengths (mean error 2.2% for model B). If the number of wavelengths increased, the model complexity needed to be increased to avoid poor estimations.

Citation Download Citation

Maria Ewerlöf, E. Göran Salerud, Tomas Strömberg, and Marcus Larsson "Estimating skin blood saturation by selecting a subset of hyperspectral imaging data", Proc. SPIE 9328, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XIII, 93280J (2 March 2015); https://doi.org/10.1117/12.2075292

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