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SIIA Público
SISTEMA INTEGRAL DE INFORMACIÓN ACADÉMICA - PÚBLICO
Título del libro: 2021 Mexican International Conference On Computer Science, Enc 2021 Título del capítulo: Artery/Vein Classification of Retinal Vasculature based on Cellular Automata
The segmentation and classification of blood vessels in fundus images is
of great importance in the detection of cardiovascular diseases, where
their morphology can be a useful indicator. While the automatic
segmentation of blood vessels has been solved successfully, the
automatic classification between arteries and veins (A/V) remains an
unanswered question. There are some proposals that use artificial
intelligence such as neural networks or methods based on deep learning,
with very promising results. In this work we propose a novel method
based on cellular automata with a neural network as a transition
function, to classify artery and vein at the pixel level given the
segmentation mask. The preliminary evaluation of this new method was
carried out in a local database of 36 images, yielding an accuracy of
0.9650 and 0.9679 for arteries and veins classification, and a Dice
similarity index above 0.7891 in the test set. The presented
classification work paves the way for automated analysis of arteries and
veins, which is specifically valuable in large data sets like our
population-based sample.
Entidades citadas de la UNAM:
Fuente:
ISBN: 9781665426121 Editorial: Institute of Electrical and Electronics Engineers Inc.
