Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/138513
Title: Retinal vessel segmentation for medical diagnosis
Authors: Khin Moet Moet Hlaing
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Publisher: Nanyang Technological University
Project: A3045-182
Abstract: This paper proposes the color fusion method, a supervised method for segmenting the retinal vessels. This method uses the feature fusion with dimensionality reduction, FFdr. The feature vectors are extracted from RGB channels using five feature extraction methods. The classification is done by a support vector machine (SVM) applying both linear and non-linear functions. The DRIVE database which holds colored retinal images together with precisely segmented vessel images by experts is used to evaluate the proposed method. Comparing to the existing methods in literature, it performs the second best in terms of accuracy and sensitivity with the best average accuracy of 0.9506. It has the desirable minimum false positive rate. Its effectiveness and performance are demonstrated via receiver operating characteristic analysis.
URI: https://hdl.handle.net/10356/138513
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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