Retinal Blood Vessel Segmentation using Random Forest with Gabor and Canny Edge Features

P. Kuppusamy, Mehfooza Munavar Basha, Che Lun Hung

研究成果: Conference contribution同行評審

摘要

Recent developments in machine learning increases the researcher's interest in processing the medical images in diagnosis. The medical field requires precise diagnosis to detect the disease. This paper proposed a fusion of features that are extracted from canny edge detector and Gabor feature extractors. These features dimension is huge while combining the features of canny edge detector and Gabor extractor. The Principal Component Analysis applied on the extracted features to reduce the dimension to increase the computational speed. The ensemble method Random Forest is applied on the features to classify the vessel's existence in fundus image. The results have been compared with Decision Tree algorithm. The experiments have proved the Random Forest performed better result with 99.86% accuracy and F1 score 0.997.

原文English
主出版物標題1st IEEE International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2022
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781665421119
DOIs
出版狀態Published - 2022
事件1st IEEE International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2022 - Villupuram, India
持續時間: 25 3月 202226 3月 2022

出版系列

名字1st IEEE International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2022

Conference

Conference1st IEEE International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2022
國家/地區India
城市Villupuram
期間25/03/2226/03/22

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