Kenneth W. Tobin

TL;DR: A new methodology for diagnosis of DME using a novel set of features based on colour, wavelet decomposition and automatic lesion segmentation is introduced, able to achieve diagnosis performance comparable to retina experts on the MESSIDOR with cross-dataset testing.

TL;DR: This paper reports results for the automatic detection of the optic nerve and localization of the macula using digital red-free fundus photography and relies on the accurate segmentation of the vasculature of the retina followed by the determination of spatial features describing the density, average thickness, and average orientation of the Vasculature in relation to the position of the fibre optic nerve.

TL;DR: Three-wavelength digital holography is applied to obtain surface height measurements over several microns of range, while simultaneously maintaining the low noise precision of the single wavelength phase measurement.

TL;DR: In this paper, a method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps, which include two data reductions, the first performed based upon a query vector extracted from a query image, and the second level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to query vector.

TL;DR: A novel computer-based image analysis method that is being developed to assist and automate the diagnosis of retinal disease is described and statistically relevant predictions regarding the presence, severity, and manifestations of common retinal diseases from digital images in an automated and deterministic manner are made.