干旱区生态环境知识资源中心(Arid): Automatic assessment of Alzheimer's disease diagnosis based on deep learning techniques

Arid

DOI	10.1016/j.compbiomed.2020.103764
	Automatic assessment of Alzheimer's disease diagnosis based on deep learning techniques
	Puente-Castro, Alejandro 1; Fernandez-Blanco, Enrique 1; Pazos, Alejandro 1,2; Munteanu, Cristian R.1,2
通讯作者	Puente-Castro, Alejandro
来源期刊	COMPUTERS IN BIOLOGY AND MEDICINE
ISSN	0010-4825
EISSN	1879-0534
出版年	2020
卷号	120
英文摘要	Early detection is crucial to prevent the progression of Alzheimer's disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precise assessment in the diagnosis of AD in the earliest and hardest to detect stages. The main objective of this work is to develop a system that automatically detects the presence of the disease in sagittal magnetic resonance images (MRI), which are not generally used. Sagittal MRIs from ADNI and OASIS data sets were employed. Experiments were conducted using Transfer Learning (TL) techniques in order to achieve more accurate results. There are two main conclusions to be drawn from this work: first, the damages related to AD and its stages can be distinguished in sagittal MRI and, second, the results obtained using DL models with sagittal MRIs are similar to the state-of-the-art, which uses the horizontal-plane MRI. Although sagittal-plane MRIs are not commonly used, this work proved that they were, at least, as effective as MRI from other planes at identifying AD in early stages. This could pave the way for further research. Finally, one should bear in mind that in certain fields, obtaining the examples for a data set can be very expensive. This study proved that DL models could be built in these fields, whereas TL is an essential tool for completing the task with fewer examples.
英文关键词	Alzheimer Deep learning MRI Sagittal ANN Transfer learning
类型	Article
语种	英语
国家	Spain
开放获取类型	Green Submitted
收录类别	SCI-E
WOS记录号	WOS:000532824300040
WOS类目	Biology ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Mathematical & Computational Biology
WOS研究方向	Life Sciences & Biomedicine - Other Topics ; Computer Science ; Engineering ; Mathematical & Computational Biology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/319041
作者单位	1.Univ A Coruna, Fac Comp Sci, CITIC, La Coruna 15007, Spain; 2.Univ Hosp Complex A Coruna CHUAC, Biomed Res Inst A Coruna INIBIC, La Coruna 15006, Spain
推荐引用方式 GB/T 7714	Puente-Castro, Alejandro,Fernandez-Blanco, Enrique,Pazos, Alejandro,et al. Automatic assessment of Alzheimer's disease diagnosis based on deep learning techniques[J],2020,120.
APA	Puente-Castro, Alejandro,Fernandez-Blanco, Enrique,Pazos, Alejandro,&Munteanu, Cristian R..(2020).Automatic assessment of Alzheimer's disease diagnosis based on deep learning techniques.COMPUTERS IN BIOLOGY AND MEDICINE,120.
MLA	Puente-Castro, Alejandro,et al."Automatic assessment of Alzheimer's disease diagnosis based on deep learning techniques".COMPUTERS IN BIOLOGY AND MEDICINE 120(2020).