direction due to stretching or shrinking because the zero point offset position is now detectable a software algorithm can be used to isolate the pet ring by taking advantage of its bright reflection known thickness and expected straight line representation in memory the basic steps of the algorithm are shown in fig5 the oct image is obtained step 1 and first analyzed on a statistical basis this analysis calculates the number of pixels for each given intensity value the histogram is then used to generate a u201c global threshold u201d value to separate the foreground tissue from background noise step 2 because the image intensity will eventually fall to the background noise level the intensity at large radial distances can be used to estimate the overall u2018 noise floor u2019 of the system this value is then be used to produce a binary image step 3 intensity values above the threshold are set to one those below the threshold are set to zero by analyzing the binary image and not the input oct image the dependence on the absolute level of the doped pet reflection is minimized once the binary image is available it is filtered with a one dimensional spatial filter step 4 that is designed to have peak response for a signal with thickness similar to the known pet layer thickness and adjacent black space as shown in the figure the influence of the tissue is greatly minimized by the spatial filter while the pet ring is preserved the next step in the process step.