Deep Learning Approach to Predict Alzheimer's Disease through Magnetic Resonance Images

Gilang Titah Ramadhan, Yori Pusparani, Isack Farady, Elvin Nur Furqon, Chih Yang Lin, Wen Hung Chao, John Sahaya Rani Alex, Jeetashree Aparajeeta, Chi Wen Lung

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

Alzheimer's disease is the most common type of dementia that causes many of the functions of the human brain to be severely weakened. To date, there has not been a cure for Alzheimer's disease. Therefore, early diagnosis is needed using MRI images with the help of a classification program. Deep learning using the Convolutional Neural Network (CNN) method is receiving increasing attention because of its excellent performance. Its architecture can be modified according to user needs based on the data to be processed and the approach for classifying, detecting, and segmenting visual objects. In this paper, we offer a classification of Alzheimer's disease using one of the architectures on CNN, namely Visual Geometry Group-19 (VGG-19), with a sagittal view of MRI images with an image size of 229 x 229 pixels. The classification accuracy of the described method is 94% for the validation set.

原文???core.languages.en_GB???
主出版物標題2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面845-846
頁數2
ISBN(電子)9798350324174
DOIs
出版狀態已出版 - 2023
事件2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Pingtung, Taiwan
持續時間: 17 7月 202319 7月 2023

出版系列

名字2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings

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???event.eventtypes.event.conference???2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023
國家/地區Taiwan
城市Pingtung
期間17/07/2319/07/23

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