Detection of Microaneurysms and Hemorrhages in Fundus Image for Glaucoma Diagnosis - Shanthi, R; Prabakaran, S (International Journal of Engineering and Technology, 2018)
Eye is the most sensitive and valuable organ of vision which helps us to visualize the world around us. Due to the high pressure in the eye, the optic nerve fails to transmit the signal to the brain; such a disorder is called Glaucoma. Detection of Microaneurysms and Hemorrhages are validated from the fundus image. To extract the shape features Morphological image flooding is used. In this approach, candidate regions are first segmented, Feature Extraction is done by Dynamic Shape Features. Further the classification process is carried out using Random Forest (RF) classifier method. The process of screening is evaluated on publicly available database Diaretdb1 with the resolution of 1152 x 1500 pixels for both healthy and abnormal images. The performance of segmentation in this method is evaluated in terms of sensitivity, specificity, and segmentation accuracy. In future, this methodology can be applied to larger clinical dataset in order to detect the disease at the maximum level.Â Â