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This paper proposes a CNN (Convolutional neural network) based blood vessel segmentation algorithm. Each pixel with its neighbors of the fundus image is checked by the CNN. The preliminary segmentation results of fundus images were refined by a two stages binarization and a morphological operation successively. The algorithm was tested on DRIVE dataset. While the specificity is 0.9603, sensitivity...
Fundus image is important for the medical screening and diagnosis of variety ophthalmopathy. The effectiveness of such a process, however, depends very much on the quality of the fundus image captured. This paper aims to asses in real-time the quality of a fundus image by first extracting a multitude of generic features, including statistical characteristics, entropy, texture, symmetry, frequency...
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