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	Deep Learning Based Binary Classification for Alzheimer's Disease Detection using Brain MRI Images
	Hussain, Emtiaz; Hasan, Mahmudul; Hassan, Syed Zafrul; Azmi, Tanzina Hassan; Rahman, Md Anisur; Parvez, Mohammad Zavid
通讯作者	Hussain, E (corresponding author), BRAC Univ, Dept Comp Sci & Engn, Software Engn & HCI Res Grp, Dhaka, Bangladesh.
会议名称	15th IEEE Conference on Industrial Electronics and Applications (ICIEA)
会议日期	NOV 09-13, 2020
会议地点	ELECTR NETWORK
英文摘要	Alzheimer's disease is an irremediable, continuous brain disorder that gradually destroys memory and thinking skills and, eventually, the ability to carry out the simplest tasks. It has become one of the critical diseases throughout the world. Moreover, there is no remedy for Alzheimer's disease. Machine learning techniques, especially deep learning-based Convolutional Neural Network (CNN), are used to improve the process for the detection of Alzheimer's disease. In recent days, CNN has achieved major success in MRI image analysis and biomedical research. A lot of research has been carried out for the detection of Alzheimer's disease based on brain MRI images using CNN. However, one of the fundamental limitations is that proper comparison between a proposed CNN model and pre-trained CNN models (InceplionV3, Xception, MobilenetV2, VGG) was not established. Therefore, in this paper, we present a model based on 12-layer CNN for binary classification and detection of Alzheimer's disease using brain MRI data. The performance of the proposed model is compared with some existing CNN models in terms of accuracy, precision, recall, F1 score, and ROC curve on the Open Access Series of Imaging Studies (OASIS) dataset. The main contribution of the paper is a 12-layer CNN model with an accuracy of 97.75%, which is higher than any other existing CNN models published on this dataset. The paper also shows side by side comparison between our proposed model and pre-trained CNN models (InceptioV3, Xception, MobilenetV2, VGG). The experimental results show the superiority of the proposed model over the existing models.
英文关键词	Alzheimer Machine Learning Deep Learning CNN MRI OASIS-1 Confusion Matrix Accuracy ROC Curve
来源出版物	PROCEEDINGS OF THE 15TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2020)
ISSN	2156-2318
出版年	2020
页码	1115-1120
ISBN	978-1-7281-5169-4
出版者	IEEE
类型	Proceedings Paper
语种	英语
收录类别	CPCI-S
WOS记录号	WOS:000646627000191
WOS类目	Engineering, Electrical & Electronic
WOS研究方向	Engineering
资源类型	会议论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/353165
作者单位	[Rahman, Md Anisur] Charles Sturt Univ, Sch Comp & Math, Bathurst, NSW, Australia; [Hussain, Emtiaz; Hasan, Mahmudul; Hassan, Syed Zafrul; Azmi, Tanzina Hassan; Parvez, Mohammad Zavid] BRAC Univ, Dept Comp Sci & Engn, Software Engn & HCI Res Grp, Dhaka, Bangladesh
推荐引用方式 GB/T 7714	Hussain, Emtiaz,Hasan, Mahmudul,Hassan, Syed Zafrul,et al. Deep Learning Based Binary Classification for Alzheimer's Disease Detection using Brain MRI Images[C]:IEEE,2020:1115-1120.