Diagnosis of Glaucoma through Semivariance Fractal Dimension Method
نویسنده
چکیده
The present paper explores a state of art for to detection of glaucoma in human eye through cup-disk segmentation & fractal dimension using image analysis. Author extracted fractal dimension feature from glaucomatous eyes for the portion of segmented cup-disk through semi variance algorithm. In the first step authors adopted Chan-vese algorithm to extract the region of interest (ROI) for which fractal dimension is determined. The strong findings of the present paper are 1. Semivariance method found to be more efficient. 2. Fractal dimension feature could be used as a diagnostics parameter for detection of glaucoma 3. The visualization of segmentation reveals that decrease in area of signifies attacking glaucoma neuroretinal rim by glaucoma 4. Fractal Dimension (FD) found to be in the range of 1.50-1.690 for the glaucoma affected eye. 5. FD found to be in the range of 1.70 to 1.99 for non glaucoma neuroretinal rim. 6. sill point obtained for glaucoma neuroretinal rim for smaller lag distance (k=10) whereas for non glaucoma neuroretinal rim larger lag distance (k=30).
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