Glaucoma is a chronic eye disease that leads to irreversible vision loss. The cup to disc ratio (CDR) plays an important role in the screening and diagnosis of glaucoma. Thus, the accurate and automatic segmentation of optic disc (OD) and optic cup (...
IEEE journal of biomedical and health informatics
May 1, 2018
In this paper, the automatic detection of neovascularization in the optic disc region (NVD) for color fundus retinal image is presented. NV is the indicator for the onset of proliferative diabetic retinopathy and it is featured by the presence of new...
Investigative ophthalmology & visual science
Oct 1, 2016
PURPOSE: To compare performance of a deep-learning enhanced algorithm for automated detection of diabetic retinopathy (DR), to the previously published performance of that algorithm, the Iowa Detection Program (IDP)-without deep learning components-o...
PURPOSE: To evaluate the performance of a support vector machine algorithm that automatically and objectively identifies corneal patterns based on a combination of 22 parameters obtained from Pentacam measurements and to compare this method with othe...
Journal of cataract and refractive surgery
Feb 1, 2016
PURPOSE: To describe the topographic and tomographic characteristics of normal fellow eyes of unilateral keratoconus cases and to evaluate the accuracy of machine learning classifiers in discriminating healthy corneas from the normal fellow corneas.
Investigative ophthalmology & visual science
Jun 1, 2015
PURPOSE: To increase the effectiveness of treating open-angle glaucoma (OAG), we tried to find a screening method of differentiating OAG from glaucoma suspect (GS) without a visual field (VF) test.