Retinal vessel segmentation for medical diagnosis

• 主要作者: Khin Moet Moet Hlaing
• 其他作者: Jiang Xudong
• 格式: Final Year Project
• 語言: English
• 出版: Nanyang Technological University 2020
• 主題: Engineering::Electrical and electronic engineering
• 在線閱讀: https://hdl.handle.net/10356/138513
• 機構: Nanyang Technological University

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.