Specle analysis for optical coherence tomography image segmentation

This paper presents basic principles of optical coherence tomography, review of applications and basic categorization of these systems. Paper also deals with the typical properties of images from optical coherence tomography, especially speckle pattern. This paper also provides an overview of the origin of speckle noise and utilization of its dependence on microstructure of probed tissue for image classification based on textural analysis. Experimental part of this paper consists of phantom preparation, data acquisition by OCT system, implementation of speckle analysis in MATLAB and of testing of its functionality on standard textural dataset and also on acquired image phantom data. Speckle analysis is used for phantom image data segmentation