Fractal Dimension as Diagnostic Parameter to Detect Glaucoma

The present paper explores a state of art for earlier diagnosis using image analysis. Authors attempted to show that fractal dimension (FD) of image feature could be adopted as alternative diagnostic parameter to detect glaucoma using state of art. At presents conventional approach to detect glaucoma ophthalmologist are using clinical parameter cup to disk ratio (CDR) which involves with lot human involvement to take decision. Authors extracted FD feature from eyes images using two algorithms Semi-variance and Box counting for a set of 80 images including male, female patients with age variations of 30 -70 years. The strong findings of the paper are: (1) Authors found that CDR linearly increasing with age of patient with FD also linearly increasing with age of patient (2) Obtained FD values are consistency with scalability of images. (3)Semi-variance algorithm merits the Box counting. (4)FD can be used as diagnostic parameters instead of CDR. Authors positively conclude that in future; FD would be very well used as diagnostic parameter for earlier detection of glaucoma.