EVALUATION OF SEMI-SUPERVISED CLUSTERING IN THE OPTIC DISC SEGMENTATION FOR GLAUCOMA DETECTION PURPOSES - Teixeira dos Santos, Luis Guilherme (2015)
Glaucoma is a slowly progressive disease, asymptomatic and can cause irreversibly blindness. Among the main tests used by ophthalmologists for diagnosis the retinography is known for being the lowest cost and the least invasive. This exam consists of observe and record retinal photographs and the diagnosis is made taking into account the ratio between the radii outside the Optic Disc (OD) and the inner part, called cup. In order to segment these regions, this study evaluates the performance of six semi-supervised clustering algorithms and two supervised in 209 images of two public databases.  The results demonstrated that the K-meanski algorithm obtained respectively 99.59% and 97.71% of precision in segmenting the contour of cup and OD.