Application of Artificial Intelligence techniques for the detection of Alzheimer’s disease using structural MRI images

• Autorzy: Zhao Xinxing , Ang Candice Ke En , Acharya U. Rajendra , Cheong Kang Hao

Identyfikatory

DOI

10.1016/j.bbe.2021.02.006

• Języki publikacji: EN

Abstrakty

EN

Alzheimer’s disease (AD) is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills. It is one of the leading types of dementia for persons aged above 65 worldwide. In order to achieve accurate and timely diagnosis, and for detection of AD in its early stages, numerous Artificial Intelligence (AI) based Computer-aided Diagnostic (CAD) approaches have been proposed using data from brain imaging. In this paper, we review the recent application of AI based CAD systems on AD and its stages, with a particular focus on the use of structural MRI due to its cost effectiveness and lack of ionizing radiation. We will review important factors of different AI techniques pertinent to AD, summarize contributions from different research groups, critically discuss challenges involved and propose directions for future research. Ultimately, it would be ideal for development of a diagnostic framework that could be applicable to not only AD, but to different types of dementia as well in the future.

Słowa kluczowe

EN

artificial intelligence; Alzheimer’s disease; machine learning; deep learning; computer aided diagnosis; structural MRI

PL

sztuczna inteligencja; choroba Alzheimera; uczenie maszynowe; uczenie głębokie; diagnoza wspomagana komputerowo

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2021
• Tom: Vol. 41, no. 2
• Strony: 456--473
• Opis fizyczny: Bibliogr. 126 poz., rys., tab.

Twórcy

autor

Zhao Xinxing

• Science, Mathematics and Technology Cluster, Singapore University of Technology and Design, 8 Somapah Road, S487372, Singapore

autor

Ang Candice Ke En

• MOH Holdings Pte Ltd, 1 Maritime Square, S099253, Singapore

autor

Acharya U. Rajendra

• Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi 599489, Singapore; Department of Biomedical Engineering, School of Science and Technology, SUSS University, Clementi 599491, Singapore; International Research Organization for Advanced Science and Technology (IROAST), Kumamoto University, Kumamoto, Japan

autor

Cheong Kang Hao

• Science, Mathematics and Technology Cluster, Singapore University of Technology and Design, Block 1, Level 4, Room 08, 8 Somapah Road, S487372, Singapore

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).