Extracting dispersion information from Optical Coherence Tomography images

Abstract

Dispersion, resulting from wavelength-dependent index of refraction variations, could be used to detect changes associated with cancer for early and accurate diagnosis. Different techniques for estimating the dispersion from Optical Coherence Tomography (OCT) images were investigated to evaluate their accuracy and applicability to samples such as muscle and adipose tissue. The dispersion was estimated from (i) the point spread function (PSF) degradation, (ii) the shift (walk-off) between images taken at different center wavelengths and (iii) the second derivative of the spectral phase. A novel technique, which uses a Wiener-type deconvolution algorithm to calculate the PSF degradation from the image speckle and is, therefore, applicable in vivo and in situ is also presented. This method was applied to a set of normal and cancer gastrointestinal OCT images resulting in 93% sensitivity and 73% specificity. The success of these preliminary results indicates the potential of using dispersion measurements for disease diagnosis.