Luis de Sisternes

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Spectral domain optical coherence tomography (SD-OCT) is a useful tool for the visualization of drusen, a retinal abnormality seen in patients with age-related macular degeneration (AMD); however, objective assessment of drusen is thwarted by the lack of a method to robustly quantify these lesions on serial OCT images. Here, we describe an automatic drusen(More)
Geographic atrophy (GA) is a condition that is associated with retinal thinning and loss of the retinal pigment epithelium (RPE) layer. It appears in advanced stages of non-exudative age-related macular degeneration (AMD) and can lead to vision loss. We present a semi-automated GA segmentation algorithm for spectral-domain optical coherence tomography(More)
Age-related macular degeneration (AMD) is the leading cause of blindness among elderly individuals. Geographic atrophy (GA) is a phenotypic manifestation of the advanced stages of non-exudative AMD. Determination of GA extent in SD-OCT scans allows the quantification of GA-related features, such as radius or area, which could be of important value to(More)
Image denoising is a fundamental preprocessing step of image processing in many applications developed for optical coherence tomography (OCT) retinal imaging--a high-resolution modality for evaluating disease in the eye. To make a homogeneity similarity-based image denoising method more suitable for OCT image removal, we improve it by considering the noise(More)
Glaucoma is one of the most common causes of blindness worldwide. Early detection of glaucoma is traditionally based on assessment of the cup-to-disc (C/D) ratio, an important indicator of structural changes to the optic nerve head. Here, we present an automated optic disc segmentation algorithm in 3-D spectral domain optical coherence tomography (SD-OCT)(More)
Automatic segmentation of retinal layers in spectral domain optical coherence tomography (SD-OCT) images plays a vital role in the quantitative assessment of retinal disease, because it provides detailed information which is hard to process manually. A number of algorithms to automatically segment retinal layers have been developed; however, accurate edge(More)
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