Detection of hard exudates from diabetic retinopathy images using fuzzy logic

Abstract

Diabetic retinopathy, that affects the blood vessels of the retina, is considered to be the most serious complication prevalent among diabetic patients. If detect successfully at an early stage, ophthalmologist would be able to treat the patients by advanced laser treatment to prevent total blindness. In this paper, we propose a technique based on morphological image processing and fuzzy logic to detect hard exudates from diabetic retinopathy retinal images. At the initial stage, the exudates are identified using mathematical morphology that includes elimination of the optic disc. Subsequently, hard exudates are extracted using an adaptive fuzzy logic algorithm that uses values in the RGB colour space of retinal image to form fuzzy sets and membership functions. The fuzzy output for all the pixels in every exudate is calculated for a given input set corresponding to red, green and blue channels of a pixel in an exudate. This fuzzy output is computed for hard exudates according to the proportion of the area of the hard exudates. By comparing the results with hand-drawn ground truths, we obtained sensitivity and specificity of detecting hard exudates as 75.43% and 99.99%, respectively.

Exudate and Blood Vessel Feature Extraction in Diabetic Retinopathy Patients using Morphology Operation

“…In another study [10], a technique based on morphological image processing and fuzzy logic to detect hard exudates from DR retinal images was proposed. At the initial stage, the exudates were identified using mathematical morphology that includes elimination of the optic disc.…”

Görsel Sözlük Ve Siniflandirma Yaklaşimlarindan Faydalanarak Di̇yabeti̇k Reti̇nopati̇li̇ Reti̇nal Görüntülerde Sert Eksudalarin Tespi̇ti̇

“…Also they introduced a new method to remove the optic disc in the post-processing stage based on variance calculation. A technique based on morphological image processing and fuzzy logic algorithms in order to detect hard exudates from DR retinal images was proposed in [9]. According this, at the initial stage, the exudates were identified, using mathematical morphology.…”

Extraction of Exudates from the Fundus Images A Review

“…Once the new model is obtained CLAHE is performed for better enhancement. [29], [18], [30], [31] also utilize CLAHE for image enhancement. This method is also comparable to the green channel extraction as discussed above.…”