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