Automatic diagnosis of macular diseases from OCT volume based on its two-dimensional feature map and convolutional neural network with attention mechanism Article Swipe
Related Concepts
Artificial intelligence
Computer science
Optical coherence tomography
Convolutional neural network
Pattern recognition (psychology)
Support vector machine
Feature extraction
Feature (linguistics)
Classifier (UML)
Volume (thermodynamics)
Deep learning
Computer vision
Medicine
Ophthalmology
Philosophy
Quantum mechanics
Linguistics
Physics
Yankui Sun
,
Haoran Zhang
,
Xianlin Yao
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1117/1.jbo.25.9.096004
· OA: W3087413301
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1117/1.jbo.25.9.096004
· OA: W3087413301
We present a general framework of OCT volume classification based on its 2-D feature map and CNN with attention mechanism and describe its implementation schemes. Our proposed methods could classify OCT volumes automatically and effectively with high accuracy, and they are a potential practical tool for screening of ophthalmic diseases from OCT volume.
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