AUTOMATIC DETECTION OF GLAUCOMA THROUGH CHANNEL EXTRACTION ADAPTIVE THRESHOLD METHOD

The diagnosis of any disease is an invasive technique performed by image processing system. Glaucoma is a chronic disease which if not detected in early stages can lead to permanent blindness. The medical techniques used by ophthalmologists like HRT and OCT is costly and time consuming. Hence there is a need to develop automatic computer aided system which can detect glaucoma efficiently and takes less time. Optic disk and optic cup are prime features which help in diagnosing glaucoma. Thus proper segmentation of optic disk and optic cup plays an important role in detecting the disorder. For developing an automatic computer aided system which can detect glaucoma efficiently in less time, we propose a method using ocular parameters, cup- disc ratio and rim-disc ratio. Our proposed Channel Extraction Adaptive Threshold (CEAT) method is independent of image quality. This method is also invariant to noise and is used to segment optic disk, optic cup. Neuro retinal rim and cup to disk ratio is calculated to screen glaucoma. We have considered the ocular parameter, rim to disk ratio in combination with CDR which gives more reliability in determining glaucoma and makes the