Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images

Abstract

Aim-To recognise automatically the main components of the fundus on digital colour images. Methods-The main features of a fundus retinal image were defined as the optic disc, fovea, and blood vessels. Methods are described for their automatic recognition and location. 112 retinal images were preprocessed via adaptive, local, contrast enhancement. The optic discs were located by identifying the area with the highest variation in intensity of adjacent pixels. Blood vessels were identified by means of a multilayer perceptron neural net, for which the inputs were derived from a principal component analysis (PCA) of the image and edge detection of the first component of PCA. The foveas were identified using matching correlation together with characteristics typical of a fovea-for example, darkest area in the neighbourhood of the optic disc. The main components of the image were identified by an experienced ophthalmologist for comparison with computerised methods. Results-The sensitivity and specificity of the recognition of each retinal main component was as follows: 99.1% and 99.1% for the optic disc; 83.3% and 91.0% for blood vessels; 80.4% and 99.1% for the fovea. Conclusions-In this study the optic disc, blood vessels, and fovea were accurately detected. The identification of the normal components of the retinal image will aid the future detection of diseases in these regions. In diabetic retinopathy, for example, an image could be analysed for retinopathy with reference to sight threatening complications such as disc neovascularisation, vascular changes, or foveal exudation. (Br J Ophthalmol 1999;83:902-910)

Screening and prevention of diabetic blindness

“…The future challenges within assessment of clinical data involve computer evaluation of pathological lesions in fundus photographs in order to obtain a full quantitative analysis of the retinopathy grade and the integration of relevant clinical parameters into decision models (Gardner et al 1996;Bek 1998;Sinthanayothin et al 1999;Ege et al 1999;Sivieri et al 1995).…”

Fovea and Optic Disc Detection in Retinal Images with Visible Lesions

“…Prior to this operation, the ROI image is normalized following the principle detailed in [4].The optic disk ROI is then quantized in 32 levels. Distinct intensity levels, which in some images are present within the optic disk, can causes artificial boundaries to be detected by the Sobel operator.…”

“…The ability to assess the location of lesions relative to the fovea is an additional important factor to diagnosis [2]. The proposed method uses some anatomic features to do the detection in field 1 (centered in optic disk) and field 2 (centered in fovea) color fundus photographs, namely: vertical orientation of vessels near the optic disc; optic disk being a bright region with a circular or slightly elliptical shape; location of vessels; darkness of the fovea and the fact that the fovea is located in an approximate distance of two and a half optic disk diameters from its center [4].…”

Bone Trabecular Analysis of Femur Radiographs for the Assessment of Osteoporosis Using DWT and DXA

“…Then, this process is applied independently to each individual After normalization, algorithm detailed by Sinthanayothin et al [11] for contrast enhancement was used to accelerate both the bone contrast attribute as well as total image intensity. The aim is to apply, a transformation of the values inside small windows in the image in a way that all values are distributed around the mean and shows all possible intensities.…”