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Erschienen in:
Anti-occlusion Light-Field Optical Flow Estimation Using Light-Field Super-Pixels Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

Recent Developments of Retinal Image Analysis in Alzheimer’s Disease and Potential AI Applications

verfasst von : Delia Cabrera DeBuc, Edmund Arthur

Erschienen in: Computer Vision – ACCV 2018 Workshops

Verlag: Springer International Publishing

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Abstract

Alzheimers disease (AD) is the most common progressive neurodegenerative illness and cause of dementia in the elderly. The critical barriers for primary prevention in AD are the lack of rapid, non-invasive, sensitive and low-cost biomarkers. As the eye and brain share essential structural and pathogenic pathways, non-invasive eye biomarkers could be identified to obtain new insights into the onset and progression of AD and its complications in the eye. In this short review, recent developments of retinal image analysis in AD and potential artificial intelligence (AI) applications are presented. Some approaches are still very much novel research techniques, others are more established and transitioning into the clinical diagnostic arena. Together they provide us with the capability to move AD detection research forwards by using novel peripheral biomarkers.

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Vorheriges Kapitel Retinal Detachment Screening with Ensembles of Neural Network Models
Nächstes Kapitel Intermediate Goals in Deep Learning for Retinal Image Analysis
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Metadaten
Titel
Recent Developments of Retinal Image Analysis in Alzheimer’s Disease and Potential AI Applications
verfasst von
Delia Cabrera DeBuc
Edmund Arthur
Copyright-Jahr
2019
Buch
Computer Vision – ACCV 2018 Workshops

Print ISBN: 978-3-030-21073-1

Electronic ISBN: 978-3-030-21074-8

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-21074-8_21

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