Automated Glaucoma Detection of Medical Image Using Biogeography Based Optimization

Gradual vision loss is an important challenging issue in medical imaging system. When optic nerve is damaged, vision loss and blindness introduced as a result known as glaucoma. So, eye pressure measurement is a crucial measure for optic nerve damage which causes gradual color blindness, vision loss known as open angle glaucoma, so pressure controlling inside eye is very significant for glaucoma detection. Glaucoma detection is basically measuring by CDR value. If CDR is greater than normal value then that is glaucomatous. Correct localization of optic disc and finding cup inside disc are the Objectives of paper. Disc and cup boundaries and cup to disc ratio are shown by resulting images. Sensitivity, specificity and accuracy are the three main parameters for evaluation purpose. In our proposed method we are using RIM-ONE dataset where 290 pictures are taken for testing which gives accuracy 97.58%, sensitivity 94.44%, and specificity 99.00%.