A cortical-inspired multi-orientation geometry model for retinal image analysis

Cortical-inspired image reconstruction via sub-Riemannian geometry and hypoelliptic diffusion

In this paper we review several algorithms for image inpainting based on the hypoelliptic diffusion naturally associated with a mathematical model of the primary visual cortex. In particular, we present one algorithm that does not exploit the information of where the image is corrupted, and others that do it. While the first algorithm is able to reconstruct only images that our visual system is...

Drusen Detection in a Retinal Image Using Multi-level Analysis

This paper concerns a method to automatically detect drusen in a retinal image without human supervision or interaction. We use a multi-level approach, beginning with classification at the pixel level and proceeding to the region level, area level, and then image level. This allows the lowest levels of classification to be tuned to detect even the faintest and most difficult to discern drusen, ...

Projective Geometry for Image Analysis

Retinal Image Analysis: A Review

Images of the eye ground or retina not only provide an insight to important parts of the visual system but also reflect the general state of health of the entire human body. Automated retina image analysis is becoming an important screening tool for early detection of certain risks and diseases like diabetic retinopathy, hypertensive retinopathy, age related macular degeneration, glaucoma etc. ...

Observation Model for Retinal Image Normalization

Retinal images are often acquired to diagnose diseases like diabetes, hypertension, and glaucoma. In acquisition process images are non-uniformly illuminated and exhibit local luminosity and contrast drift. This may affect diagnostic process and results in deriving diagnostic parameters. We proposed method that estimates background of retinal images by sub sampling and interpolation. This metho...