1. Articles from Priyanka Roy

    1-3 of 3
    1. OCTID: Optical Coherence Tomography Image Database

      OCTID: Optical Coherence Tomography Image Database

      Optical coherence tomography (OCT) is a non-invasive imaging modality which is widely used in clinical ophthalmology. OCT images are capable of visualizing deep retinal layers which is crucial for the early diagnosis of retinal diseases. In this paper, we describe a comprehensive open-access database containing more than 500 high-resolution images categorized into different pathological conditions. The image classes include Normal (NO), Macular Hole (MH), Age-related Macular Degeneration (AMD), Central Serous Retinopathy, and Diabetic Retinopathy (DR). The images were obtained from a raster scan protocol with a 2mm scan length and 512x1024 pixels resolution. We have also included 25 normal OCT ...

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    2. Automated Segmentation of Retinal Optical Coherence Tomography Images (Thesis)

      Automated Segmentation of Retinal Optical Coherence Tomography Images (Thesis)

      Aim Optical Coherence Tomography (OCT) is a fast and non-invasive medical imaging technique which helps in the investigation of each individual retinal layer structure. For early detection of retinal diseases and the study of their progression, segmentation of the OCT images into the distinct layers of the retina plays a crucial role. However, segmentation done by the clinicians manually is extremely tedious, time-consuming and variable with respect to the expertise level. Hence, there is an utmost necessity to develop an automated segmentation algorithm for retinal OCT images which is fast, accurate, and eases clinical decision making. Methods Graph-theoretical methods have ...

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    3. Intra-retinal segmentation of optical coherence tomography images using active contours with a dynamic programming initialization and an adaptive weighting strategy

      Intra-retinal segmentation of optical coherence tomography images using active contours with a dynamic programming initialization and an adaptive weighting strategy

      Retinal layer shape and thickness are one of the main indicators in the diagnosis of ocular diseases. We present an active contour approach to localize intra-retinal boundaries of eight retinal layers from OCT images. The initial locations of the active contour curves are determined using a Viterbi dynamic programming method. The main energy function is a Chan-Vese active contour model without edges. A boundary term is added to the energy function using an adaptive weighting method to help curves converge to the retinal layer edges more precisely, after evolving of curves towards boundaries, in final iterations. A wavelet-based denoising method ...

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    1-3 of 3
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