Automated laser mark segmentation from colored retinal images

Medical Image Analysis is an ongoing field of research nowadays. Diabetic Retinopathy (DR) is one of the major diseases being workaround using different techniques of image analysis. Advanced stage of DR is commonly treated with laser at the present time which is a major tool to safe further vision loss which leaves marks on the surface of the retina. We present an automated system for detection of laser marks from colored retinal images to facilitate automated diagnosis of retinal diseases. The proposed system performs preprocessing on the image in order to extract all possible candidate laser mark regions. This is followed by a post processing stage to remove false pixels from candidate regions. The method extracts a number of features for proper representation of all candidate regions. These extracted features are used to facilitate the later classification stage for accurate detection of laser marks from all candidate regions. The validity of a proposed system is performed on a locally gathered retinal image database and results show the significance of proposed system.