BibTeX:

@article{IJIRSTV2I1047,
     title={A Segmentation Improved Statistical Model for Retinal Disease Identification},
     author={Parul and Mrs. Neetu Sharma},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={2},
     number={1},
     pages={151--157},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV2I1047.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Retinal images are analyzed to identify the glaucoma or the diabetic disease. The accuracy of disease detection depends on the extracted features. In this paper, segmentation and mathematical filters based statistical approach is presented to identify the retinal disease. At first stage of this statistical model, the features from retinal image are extracted using segmentation method. This segmentation model is able to separate the disc and cup features. Later on the ratio analysis between cup and disc is considered to identify the chances of retinal disease. The experimentation is applied on real time images. The results shows that the work has provided effective identification of retinal disease.

Glaucoma, retinal ganglion cells (RGC), optic nerve head (ONH), cupping