Many diseases like diabetic retinopathy, glaucoma, hypertension, diabetes, and coronary heart disease can be detected from the changes in the vascular system of the fundus image. Manually inspecting the vessels in the fundus image takes a long time for an ophthalmologist. They can spot anomalies in vascular structure more readily with improved automated vessel segmentation. A framework is created in which thick and thin vessels are segmented separately and then combined to provide an Improved binary segmented image.
Keywords: Machine Learning , Deep neural network,UNET,Medical image segmentation,artifical intelligence,Andriod app development
Tools: Python,Jupyter notebook,matlab,keras ,tensorflow,pytorch ,kotlin,andriod studio
Department: Department of Electrical Engineering
Tools: Python,Jupyter notebook,matlab,keras ,tensorflow,pytorch ,kotlin,andriod studio
Department: Department of Electrical Engineering
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