Computer aided detection (CAD) systems are widely used in the analysis of biomedical images. In this paper, we present a novel CAD system to detect age-related macular degeneration (ARMD) on retinal fundus fluorescein angiography (FFA) images, and we provide an areal size calculation of pathogenic drusen regions. The purpose of this study is to enable identification and areal size calculation of ARMD-affected regions with the developed CAD system; hence, we aim to discover the condition of the disease as well as facilitate long-term patient follow-up treatment. With the aid of this system, assessing the marked regions will take less time for ophthalmologists and observing the progress of the treatment will be a simpler process. The CAD system consists of four stages, a) preprocessing, b) segmentation, c) region of interest detection and d)feature extraction and drusen area detection. Detection through CAD and calculation of drusen regions were performed with a dataset composed of 75 images. The results obtained from the developed CAD system were examined by a specialist ophthalmologist, and the performance criteria of the CAD system are reported as conclusions. As a result, with 66 correct detections and 9 incorrect detections, the developed CAD system achieved an accuracy rate of 88%.