Deep Convolutional Artery/Vein Classification of Retinal Vessels
Authors: Meyer, M.I., Galdran, A., Costa, P., Mendonça, A.M. and Campilho, A.
Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume: 10882 LNCS
Pages: 622-630
eISSN: 1611-3349
ISBN: 9783319929996
ISSN: 0302-9743
DOI: 10.1007/978-3-319-93000-8_71
Abstract:The classification of retinal vessels into arteries and veins in eye fundus images is a relevant task for the automatic assessment of vascular changes. This paper presents a new approach to solve this problem by means of a Fully-Connected Convolutional Neural Network that is specifically adapted for artery/vein classification. For this, a loss function that focuses only on pixels belonging to the retinal vessel tree is built. The relevance of providing the model with different chromatic components of the source images is also analyzed. The performance of the proposed method is evaluated on the RITE dataset of retinal images, achieving promising results, with an accuracy of 96 % on large caliber vessels, and an overall accuracy of 84 %.
Source: Scopus
Deep Convolutional Artery/Vein Classification of Retinal Vessels
Authors: Meyer, M.I., Galdran, A., Costa, P., Mendonca, A.M. and Campilho, A.
Journal: IMAGE ANALYSIS AND RECOGNITION (ICIAR 2018)
Volume: 10882
Pages: 622-630
eISSN: 1611-3349
ISBN: 978-3-319-92999-6
ISSN: 0302-9743
DOI: 10.1007/978-3-319-93000-8_71
Source: Web of Science (Lite)
Deep Convolutional Artery/Vein Classification of Retinal Vessels.
Authors: Meyer, M.I., Galdran, A., Costa, P., Mendonça, A.M. and Campilho, A.
Editors: Karray, F. and Romeny, B.M.T.H.
Journal: ICIAR
Volume: 10882
Pages: 622-630
Publisher: Springer
ISBN: 978-3-319-92999-6
https://doi.org/10.1007/978-3-319-93000-8
Source: DBLP