| Summary: | Vessel Detection/segmentation based on computer vision and machine learning provides an efficient and economic benefit tool for retinal image analysis. Retinal vessel segmentation is an important part of computer-aided diagnosis of retinal diseases, like arteriosclerosis, vein occlusions, and diabetic retinopathy. A reliable assessment for these diseases can be achieved by regularly performing accurate measurement of the vessel width, tortuosity and proliferation. In this dissertation, We adopted the traditional CV method based on 2D-matched Filter and deep learning U-NET method, and achieved good segmentation effect.
Keywords: Retinal Vessel Segmentation, Deep Learning, Matched Filter, U-Net, Convolutional Neural Network
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