Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151186
Title: Machine learning based retinal vessel detection
Authors: Li, Hongru
Keywords: Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Li, H. (2021). Machine learning based retinal vessel detection. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/151186
Abstract: 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
URI: https://hdl.handle.net/10356/151186
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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