1. Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms

    Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms

    This paper presents a fully automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography (OCT) retina images of subjects with diabetic macular edema. The OCT image is segmented using a novel neutrosophic transformation and a graph-based shortest path method. In neutrosophic domain, an image g is transformed into three sets: T (true), I (indeterminate) that represents noise, and F (false). This paper makes four key contributions. First, a new method is introduced to compute the indeterminacy set I , and a new λ -correction operation is introduced to compute the set T in neutrosophic domain. Second, a graph ...

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