Automated diagnosis of Alzheimer’s Disease using OCT and OCTA: a systematic review

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dc.authorid0000-0001-6309-4524
dc.authorid0000-0002-8649-6013
dc.authorid0009-0004-3598-4326
dc.authorid0000-0001-7013-5451
dc.authorid0000-0001-8619-8078
dc.authorid0000-0002-4364-934X
dc.contributor.authorTurkan, Yaseminen_US
dc.contributor.authorTek, Faik Borayen_US
dc.contributor.authorArpacı, Fatihen_US
dc.contributor.authorArslan, Ozanen_US
dc.contributor.authorToslak, Devrimen_US
dc.contributor.authorBulut, Mehmeten_US
dc.contributor.authorYaman, Aylinen_US
dc.date.accessioned2025-08-19T10:57:24Z
dc.date.available2025-08-19T10:57:24Z
dc.date.issued2024-08-06
dc.departmentIşık Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering and Natural Sciences, Department of Computer Engineeringen_US
dc.descriptionThis study was supported by Scientific and Technological Research Council of Turkey (TUBITAK) under the Grant Number 122E509. The authors thank to TUBITAK for their supports.en_US
dc.description.abstractRetinal optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) have emerged as promising, non-invasive, and cost-effective modalities for the early diagnosis of Alzheimer's disease (AD). However, a comprehensive review of automated deep learning techniques for diagnosing AD or mild cognitive impairment (MCI) using OCT/OCTA data is lacking. We addressed this gap by conducting a systematic review using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. We systematically searched databases, including Scopus, PubMed, and Web of Science, and identified 16 important studies from an initial set of 4006 references. We then analyzed these studies through a structured framework, focusing on the key aspects of deep learning workflows for AD/MCI diagnosis using OCT-OCTA. This included dataset curation, model training, and validation methodologies. Our findings indicate a shift towards employing end-to-end deep learning models to directly analyze OCT/OCTA images in diagnosing AD/MCI, moving away from traditional machine learning approaches. However, we identified inconsistencies in the data collection methods across studies, leading to varied outcomes. We emphasize the need for longitudinal studies on early AD and MCI diagnosis, along with further research on interpretability tools to enhance model accuracy and reliability for clinical translation.en_US
dc.description.sponsorshipTürkiye Bilimsel ve Teknolojik Araştırma Kurumuen_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationTurkan, Y., Tek, F. B., Arpacı, F., Arslan, O., Toslak, D., Bulut, M. & Yaman, A. (2024). Automated diagnosis of Alzheimer’s Disease using OCT and OCTA: a systematic review. IEEE Access, 12, 104031-104051. doi:10.1109/ACCESS.2024.3434670en_US
dc.identifier.doi10.1109/ACCESS.2024.3434670
dc.identifier.endpage104051
dc.identifier.issn2169-3536
dc.identifier.scopus2-s2.0-85200200309
dc.identifier.scopusqualityQ1
dc.identifier.startpage104031
dc.identifier.urihttps://hdl.handle.net/11729/6626
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2024.3434670
dc.identifier.volume12
dc.identifier.wosWOS:001286627200001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorTurkan, Yaseminen_US
dc.institutionauthorid0000-0001-6309-4524
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofIEEE Accessen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAlzheimer's diseaseen_US
dc.subjectCognitive impairmenten_US
dc.subjectDeep learningen_US
dc.subjectDementiaen_US
dc.subjectNeural networksen_US
dc.subjectOptical coherence tomographyen_US
dc.subjectOptical coherence tomography angiographyen_US
dc.subjectRetinal imagingen_US
dc.subjectAngiographyen_US
dc.subjectClinical researchen_US
dc.subjectCost effectivenessen_US
dc.subjectNeurodegenerative diseasesen_US
dc.subjectOphthalmologyen_US
dc.subjectAlzheimeren_US
dc.subjectBiomedical imagingen_US
dc.subjectCognitive neurosciencesen_US
dc.subjectRetinaen_US
dc.subjectSystematicen_US
dc.subjectOptical tomographyen_US
dc.subjectHealthy-subjectsen_US
dc.subjectSegmentationen_US
dc.subjectBiomarkersen_US
dc.subjectMRen_US
dc.titleAutomated diagnosis of Alzheimer’s Disease using OCT and OCTA: a systematic reviewen_US
dc.typeArticleen_US
dspace.entity.typePublicationen_US

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