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With the introduction of spectral-domain optical coherence tomography (OCT),much larger image datasets are routinely acquired compared to what was possibleusing the previous generation of time-domain OCT. Thus, the need for 3-Dsegmentation methods for processing such data is becoming increasinglyimportant. We present a new 3D segmentation method for retinal OCT volume data,which generates an enhanced volume data by using pixel intensity, boundaryposition information, intensity changes on both sides of the bordersimultaneously, and preliminary discrete boundary points are found from allA-Scans and then the smoothed boundary surface can be obtained after removing asmall quantity of error points. Our experiments show that this method isefficient, accurate and robust.

A 3D Segmentation Method for Retinal Optical Coherence Tomography Volume Data