To measure the epineurium thickness from phase-retardation images, a slightly different technique was used. An average depth-resolved phase-retardation profile from the middle 50% of a nerve in a phase-retardation image [Fig. 4(d)] is plotted in Fig. 4(e). With a similar assumption that the interior portions of the nerve will have uniform optical properties different from those of the outer sheath when averaged over this width, we can determine the epineurium thickness through differences in birefringence, or the slope of the depth-resolved phase retardation. We can therefore do a linear fit of the phase retardation within the axonal region [Fig. 4(e)]. Near a depth of 0.22 mm, a phase-wrapping artifact25 can be observed. Up to this point of our analysis, all phase-retardation calculation was done using Stokes method; the range of measurable phase was . To verify the homogeneity of the overall axonal region, we also used Jones matrix analysis, which can measure phase in range , of the same data. After unwrapping the phase, we found that a similar slope was maintained up to a depth of 0.3 mm [inset in Fig. 4(e)], and beyond that depth, the intensity became too low to reliably measure the phase retardation. (We found that minimum SNR required for reliable phase information is 25 dB in this study; hence, both intensity and phase-retardation curves are shown in broken lines where SNR becomes less than 25dB.) A linear fit was used to get the slope of the rising portion in the phase-retardation curve, and the slope was extrapolated for the entire plot. The residuals between the linear-fit and actual phase-retardation curve are plotted in Fig. 4(f). The posterior boundary of epineurium was determined as the depth at which the difference between linear fit and actual phase curve began to be smaller than the threshold value (mean standard deviations of residuals from linear portion). As before, the top surface of nerve was considered as the anterior boundary. Following this assumption, the thickness was calculated for all data sets.