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- W2802988847 abstract "Optical Coherence Tomography (OCT) is an imaging technique used to localize the intra-retinal boundaries for the diagnostics of macular diseases. Due to speckle noise, low image contrast and accurate segmentation of individual retinal layers is difficult. Due to this, a method for retinal layer segmentation from OCT images is presented. This paper proposes a pre-processing filtering approach for denoising and segmentation methods for segmenting retinal layers OCT images using graph based segmentation technique. These techniques are used for segmentation of retinal layers for normal as well as patients with Diabetic Macular Edema. The algorithm based on gradient information and shortest path search is applied to optimize the edge selection. In this paper the four main layers of the retina are segmented namely Internal limiting membrane (ILM), Retinal pigment epithelium (RPE), Inner nuclear layer (INL) and Outer nuclear layer (ONL). The proposed method is applied on a database of OCT images of both ten normal and twenty DME affected patients and the results are found to be promising." @default.
- W2802988847 created "2018-05-17" @default.
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- W2802988847 date "2018-01-01" @default.
- W2802988847 modified "2023-09-24" @default.
- W2802988847 title "Denoising and segmentation of retinal layers in optical coherence tomography images" @default.
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- W2802988847 doi "https://doi.org/10.1063/1.5032034" @default.
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