A Depth Based Approach to Glaucoma Detection Using Retinal Fundus Images

Qualitative evaluation of stereo retinal fundus images by experts is a widely accepted method for optic nerve head evaluation (ONH) in glaucoma. The quantitative evaluation using stereo involves depth estimation of the ONH and thresholding of depth to extract optic cup. In this paper, we attempt the reverse, by estimating the disc depth using supervised and unsupervised techniques on a single optic disc image. Our depth estimation approach is evaluated on the INSPIRE-stereo dataset by using single images from the stereo pairs, and is compared with the OCT based depth ground truths. We extract spatial and intensity features from the depth maps, and perform classification of images into glaucomatous and normal. Our approach is evaluated on a dataset of 100 images and achieves an AUC of 0.888 with a sensitivity of 83% at specificity 83%. Experiments indicate that our approach can reliably estimate depth, and provide valuable information for glaucoma detection and for monitoring its progression

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

ELISA Based Immunoreactivity Reduction of Soy Allergens through Thermal Processing

Allergens are proteins and are, therefore, likely to be denatured when subjected to thermal treatment. Traditional cooking has so far been able to reduce allergen sensitivity by around 70–90%. This study was aimed at evaluating the effect of a broad range of thermal treatments on the reduction of soy immunoreactivity (IR) in a 5% slurry using a sandwich ELISA technique. Cooking at 100 °C (10–60 min) and different thermal processing conditions, such as in commercial sterilization (with a process lethality (Fo) between 3 and 5 min) and selected severe thermal processing conditions (Fo > 5 and up to 23 min) were used in the study to evaluate their influence on allergen IR. Based on an IR comparison with an internal soy allergen standard, the allergen concentration in the untreated soy sample was calculated to be equivalent to 333 mg/kg (ppm). Cooking conditions only reduced the IR sensitivity to about 10 mg/kg (~1.5 log reductions), while the thermal processing treatments lowered the allergen IR up to 23 × 10−3 mg/kg (or 23 ppb) (>4 log reductions). FTIR analysis indicated significant changes in protein structure resulting from the thermal processing treatments, with a higher degree of allergen reduction corresponding with a higher value of random coil percentages. The influence of process severity on color and rheological properties was, however, minimal