2005
DOI: 10.1109/tmi.2005.848655
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Delineating fluid-filled region boundaries in optical coherence tomography images of the retina

Abstract: We evaluate the ability of a deformable model to yield accurate shape descriptions of fluid-filled regions associated with age-related macular degeneration. Calculation of retinal thickness and volume by the current optical coherence tomography (OCT) system includes fluid-filled regions or lesions along with actual retinal tissue. In order to quantify these lesions independently from the retinal tissue, they must be outlined. A deformable model was applied to OCT images of retinas demonstrating cystoids and su… Show more

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Cited by 115 publications
(71 citation statements)
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“…The first attempt was semi-automatic [1], where a deformable model was manually initialized and grown within a SEAD. Later, a fully automated approach was proposed in [2], where they combined a k-nearest neighbor (k-NN) classification and a graph cut segmentation.…”
Section: Introductionmentioning
confidence: 99%
“…The first attempt was semi-automatic [1], where a deformable model was manually initialized and grown within a SEAD. Later, a fully automated approach was proposed in [2], where they combined a k-nearest neighbor (k-NN) classification and a graph cut segmentation.…”
Section: Introductionmentioning
confidence: 99%
“…Anisotropic diffusion has been demonstrated previously in the removal of speckle from retinal OCT scans [30,31]. The present implementation [32] performs diffusion with a 2D kernel that adapts the degree of smoothing, based on the location and direction of intensity gradients in the image.…”
Section: Noise Reductionmentioning
confidence: 99%
“…By using the essence of machine learning and AI, DIP can be increased its performance and efficiency. AS are also introducing as a new technique to improve its performance by using basic low level image segmentation via boundary detection methods [32], [33], [34], & [35] and via clustering methods [36] & [37]. Novel approach of boundary detection methods deploy the pheromone aspects of AS , here the ants are considered as pixels within the image and move within the image in a discretised pixel-wise fashion whose aim is to extract and map boundary"s within the image .…”
Section: Development In Antalgorithmsmentioning
confidence: 99%