Age-related Macular Degeneration (AMD) is the most important cause of irreversible blindness in the developed world. In AMD new blood

vessels grow underneath the retina in a process called choroidal neovascularisation (CNV). There is much interest in the quantification of the angiographic features of CNV, as these parameters are used as markers for monitoring a therapeutic response. To date, the techniques used in angiographic analysis are based on subjective interpretation by experienced clinicians. The objective of the present study was to develop a suitable algorithm for CNV denoising and segmentation using confocal laser imaging system . Materials and Methods: The algorithm includes adaptive wiener filtering technique, top-hat morphology method and a segmentation method. In which thresholding method based on modified Otsu was applied. The developed algorithm was used to analyze 12 patients with CNV . Results: We obtained area in millimeter for each lesion and compared with subjective interpretation evaluation of CNV. The performance of the algorithm is established through statistical analysis. The result was compared with an observer. This analysis indicates that the proposed algorithm have sensitivity , specificity, positive predictive value and negative protective value equal to 0.77 ± 0.12, 0.76 ± .0151, and 1 respectively . Discussion and conclusion: This study confirms that the proposed algorithm based on modified Otsu can be used to identify certain types of CNV in retinal images particularly those that are hyperfluorescent. Compared with subjective evaluations, this approach provides an advantage for evaluating responses to treatment that may increase the value of ICGA applications in clinical trials. The recent studies show that suitable methods for CNV segmentation have not been applied.