干旱区生态环境知识资源中心(Arid): Brain-on-Cloud for automatic diagnosis of Alzheimer?s disease from 3D structural magnetic resonance whole-brain scans

Arid

DOI	10.1016/j.cmpb.2022.107191
	Brain-on-Cloud for automatic diagnosis of Alzheimer?s disease from 3D structural magnetic resonance whole-brain scans
	Tomassini, Selene; Sbrollinia, Agnese; Covellaa, Giacomo; Sernani, Paolo; Falcionelli, Nicola; Millerb, Henning; Morettinia, Micaela; Burattinia, Laura; Dragonia, Aldo Franco
通讯作者	Morettinia, M
来源期刊	COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
ISSN	0169-2607
EISSN	1872-7565
出版年	2022
卷号	227
英文摘要	Background and objective: Alzheimer's disease accounts for approximately 70% of all dementia cases. Cortical and hippocampal atrophy caused by Alzheimer's disease can be appreciated easily from a T1-weighted structural magnetic resonance scan. Since a timely therapeutic intervention during the initial stages of the syndrome has a positive impact on both disease progression and quality of life of af-fected subjects, Alzheimer's disease diagnosis is crucial. Thus, this study relies on the development of a robust yet lightweight 3D framework, Brain-on-Cloud, dedicated to efficient learning of Alzheimer's disease-related features from 3D structural magnetic resonance whole-brain scans by improving our re-cent convolutional long short-term memory-based framework with the integration of a set of data han-dling techniques in addition to the tuning of the model hyper-parameters and the evaluation of its diag-nostic performance on independent test data. Methods: For this objective, four serial experiments were conducted on a scalable GPU cloud service. They were compared and the hyper-parameters of the best experiment were tuned until reaching the best-performing configuration. In parallel, two branches were designed. In the first branch of Brain-on-Cloud, training, validation and testing were performed on OASIS-3. In the second branch, unenhanced data from ADNI-2 were employed as independent test set, and the diagnostic performance of Brain-on-Cloud was evaluated to prove its robustness and generalization capability. The prediction scores were computed for each subject and stratified according to age, sex and mini mental state examination. Results: In its best guise, Brain-on-Cloud is able to discriminate Alzheimer's disease with an accuracy of 92% and 76%, sensitivity of 94% and 82%, and area under the curve of 96% and 92% on OASIS-3 and independent ADNI-2 test data, respectively. Conclusions: Brain-on-Cloud shows to be a reliable, lightweight and easily-reproducible framework for automatic diagnosis of Alzheimer's disease from 3D structural magnetic resonance whole-brain scans, performing well without segmenting the brain into its portions. Preserving the brain anatomy, its appli-cation and diagnostic ability can be extended to other cognitive disorders. Due to its cloud nature, com-putational lightness and fast execution, it can also be applied in real-time diagnostic scenarios providing prompt clinical decision support. (c) 2022 Elsevier B.V. All rights reserved.
英文关键词	Alzheimer?s disease Cloud computing Computer-aided diagnosis Convolutional LSTM 3D structural magnetic resonance Supervised deep learning
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000882529400005
WOS类目	Computer Science, Interdisciplinary Applications ; Computer Science, Theory & Methods ; Engineering, Biomedical ; Medical Informatics
WOS研究方向	Computer Science ; Engineering ; Medical Informatics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/392181
推荐引用方式 GB/T 7714	Tomassini, Selene,Sbrollinia, Agnese,Covellaa, Giacomo,et al. Brain-on-Cloud for automatic diagnosis of Alzheimer?s disease from 3D structural magnetic resonance whole-brain scans[J],2022,227.
APA	Tomassini, Selene.,Sbrollinia, Agnese.,Covellaa, Giacomo.,Sernani, Paolo.,Falcionelli, Nicola.,...&Dragonia, Aldo Franco.(2022).Brain-on-Cloud for automatic diagnosis of Alzheimer?s disease from 3D structural magnetic resonance whole-brain scans.COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE,227.
MLA	Tomassini, Selene,et al."Brain-on-Cloud for automatic diagnosis of Alzheimer?s disease from 3D structural magnetic resonance whole-brain scans".COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 227(2022).