A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification
نویسندگان
چکیده
• Recent vessel segmentation using machine and deep learning methods are reviewed. Performance of non-deep evaluated. An artery/vein classification Summary tables presented, reporting key algorithms, validation databases, challenges addressed. The eye affords a unique opportunity to inspect rich part the human microvasculature non-invasively via retinal imaging. Retinal blood prime steps for diagnosis risk assessment microvascular systemic diseases. A high volume techniques based on have been published in recent years. In this context, we review 158 papers between 2012 2020, focussing (DL) automatic fundus camera images. We divide into various classes by task (segmentation or artery-vein classification), technique (supervised unsupervised, learning, hand-crafted methods) more specific algorithms (e.g. multiscale, morphology). discuss advantages limitations, include summarising results at-a-glance. Finally, attempt assess quantitative merit DL terms accuracy improvement compared other methods. allow us offer our views outlook
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ژورنال
عنوان ژورنال: Medical Image Analysis
سال: 2021
ISSN: ['1361-8423', '1361-8431', '1361-8415']
DOI: https://doi.org/10.1016/j.media.2020.101905