Time-resolved multi-distance measurements are studied to retrieve absorption and reduced scattering coefficients of
adult heads, which have enough depth sensitivity to determine the optical parameters in superficial tissues and brain
separately. Measurements were performed by putting the injection and collection fibers on the left semi-sphere of the
forehead, with the injection fiber placed toward the temporal region, and by moving the collection fiber between 10 and
60 mm from the central sulcus. It became clear that optical parameters of the forehead at all collection fibers were
reasonably determined by selecting the appropriate visibility length of the geometrical head models, which is related to
head surface curvature at each position.
The absorption and reduced scattering coefficients ( μa and μ's) of adult heads were determined by multidistance timeresolved reflectance measurements. The finite difference time domain analysis was used to calculate the time-resolved reflectance from adult head models. Invivo time-resolved reflectances of human heads was measured at wavelengths of 680 and 780 nm. By minimizing the objective functions that compare the theoretical and experimental time-resolved reflectances, μa and μ's of the brains were determined. The results show that the time shift tolerance of measured reflectance for reducing to less than 10% the deviations in μa and μ's due to their coupling from the values obtained by optimum time shifts is more than 20 ps at both wavelengths.
Finite difference time domain (FDTD) analysis has been formulated for predicting time-resolved reflectance from an adult head model with brain grooves containing a non-scattering layer. Mean delay (MD) dependences on source detector separation (d) and time-resolved reflectance calculated using the FDTD analysis were compared with in vivo experiments of human heads. It is shown that the theoretical and experimental MD dependences on d and the time-resolved reflectance are well predicted by FDTD analysis. These results have shown that tomographic imaging of brain activities is promising, which improves depth sensitivities by enhancing the contribution of late photons in time-resolved systems.
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