A Polar Map Based Approach Using Retinal Fundus Images for Glaucoma Detection

Cup-to-disc ratio is commonly used as an important parameter for glaucoma screening, involving segmentation of the optic cup on fundus images. We propose a novel polar map representation of the optic disc, using a combination of supervised and unsupervised cup segmentation techniques, for detection of glaucoma. Instead of performing hard thresholding on the segmentation output to extract the cup, we consider the cup confidence scores inside the disc to construct a polar map, and extract sector-wise features for learning a glaucoma risk probability (GRP) for the image. We compare the performance of GRP vis-à-vis the cup-to-disc ratio (CDR). On an evaluation dataset of 100 images from the publicly available RIM-ONE database, our method achieves 82% sensitivity at 84% specificity, and 96% sensitivity at 60% specificity (AUC of 0.8964). Experiments indicate that the polar map based method can provide a more discriminatory glaucoma risk probability score compared to CDR

Modeling the Structure-Function Relationship between Retinal Ganglion Cells and Visual Field Sensitivity and the Changes Due to Glaucomatous Neuropathy

Relatively new technology called optical coherence tomography allows direct and non invasive in vivo imaging of retinal anatomy in human subjects. There are several interesting applications of this technique, including testing models relating retinal anatomy (structural measures) to behavioral thresholds of light sensitivity (functional measures). In addition to potentially improving our understanding of this relationship and how it changes during the course of neurodegenerative diseases of the eye such as glaucoma, analyses of these data may allow for early identification of glaucomatous neural damage in the retina, which has considerable clinical relevance. Here, the underlying assumptions and generalization of a previously developed model of the structure function relationship in glaucoma was tested by applying this model to a novel dataset. This model has been influential in the literature because it purports to accurately estimate the number of retinal ganglion cells; however, it was found to have several questionable assumptions and did not generalize well. Next, a new method of estimating the number of retinal ganglion cells from optical coherence tomography was developed. This method uses fewer and more defensible assumptions and demonstrated good agreement with independent histological estimates. Finally, a new method, using computer simulations, was developed for analyzing data from optical coherence tomography in order to distinguish early signs of glaucomatous changes in retinal anatomy from variability in structure among healthy retinas, and this method performed better than previously published techniques

Actas de las XXXIV Jornadas de Automática

Postprint (published version