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In this paper, we propose an effective framework to automatically segment hard exudates (HEs) in fundus images. Our framework is based on a coarse-to-fine strategy, as we first get a coarse result allowed of some negative samples, then eliminate the negative samples step by step. In our framework, we make the most of the multi-channel information by employing a boosted soft segmentation algorithm...
An approach to classifying retinal images using a histogram based representation is described. More specifically, a two stage Case Based Reasoning (CBR) approach is proposed, to be applied to histogram represented retina images to identify Age-related Macular Degeneration (AMD). To measure the similarity between histograms, a time series analysis technique, Dynamic Time Warping (DTW), is employed...
The shape deformation within the optic disk (OD) is an important indicator for the detection of glaucoma. In this paper, relevant disk parameters are estimated using the OD and cup boundaries. A deformable model guided by regional statistics is used to detect the OD boundary. A cup boundary detection scheme is presented based on the appearance of pallor in Lab colour space and the expected cup symmetry...
This paper proposes a method to detect the macula in the retinal fundus image automatically. The method makes use of the optic disc height obtained from the ARGALI to define the region of interest. Regions of dark spots are then detected by finding the coordinates with the lowest pixel intensity and determining the average pixel neighbourhood intensities. These regions are ranked to determine the...
This paper proposes two efficient approaches for automatic detection and extraction of Exudates and Optic disk in ocular fundus images. The localization of optic disk is composed of three steps. First the centre of optic disk is estimated by finding a point that has maximum local variance. The color morphology in Lab space is used to have homogeneous optic disk region. The boundary of the optic disk...
This paper presents a novel method for identification of the position of the optic disc in retinal images. The method is based on the preliminary detection of the main edge detection of retinal image. The segmentation optic disc is estimated as a circular area. We searched for areas of optic disc using Hough transform which detected several straight lines and approximated them as a circular line....
The optic disc (OD) and exudates form the main features of fundus images for diagnosing eye disease such as diabetic retinopathy and glaucoma. In this paper, an algorithm for the extraction of OD and exudates from fundus images based on marker controlled watershed segmentation is presented. The proposed algorithm makes use of average filtering and contrast adjustment as preprocessing steps before...
The paper presents an extension of the gradient method for detection of red lesions on images of eye fundus, like a step in an automated system for recognition of diabetic retinopathy. Images of high resolution were corrected for shading and noise and the method was applied by calculating on every pixel the ldquoexpanding gradientrdquo of that pixel. This way, a map of the image was obtained and by...
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