*Study and Analysis of Fluid Filled Abnormalities in Retina Using OCT Images DOI: http://dx.doi.org/10.5772/intechopen.109646*

chosen. The overall number of features considered has been comparatively reduced with significant accuracy, thereby optimizing the features used for the process of classification. Based on the excess or deficit of fluids in the retinal layers, the overall features also varied accordingly, so as to enable the classifier to remain comparatively more accurate for the proposed system. Zernike moments are most commonly used shape descriptors and were hence used for the proposed application, in order to detect the shape-based changes that occur in retina due to accumulation or lack of fluid within the retinal layers. The classifier that has been used is a basic supervised classifier, yet more appropriate for the application proposed. The average Youden 's Index shows that the algorithm proposed is reliable in retinal analysis and could be used in automated analysis of OCT Image analysis. The proposed system could be further extended for other disorders in retina and integrated with OCT Device as an additional software for instantaneous evaluation of the retinal disorders and the therapeutic efficiencies. The developed system is promising for the selected application and has been evaluated with comparatively higher number of input samples, which restricted its evaluation until the process of segmentation and did not focus on classification further. The overall performance indices are also satisfactory and matchable with the existing results derived from similar works as evaluated by the Ophthalmologist. The developed system has also covered a significant number of fluid related disorders which are caused due to excessive or deficit fluids within the layers of retina. As OCT is an efficient tool for detection of prior stages of blindness, the proposed algorithm remains an expert system for earlier identification and accurate evaluation of the retinal fluid volumes.
