Multiloss Function Based Deep Convolutional Neural Network for Segmentation of Retinal Vasculature into Arterioles and Venules
Joint Authors
Badawi, Sufian A.
Fraz, Muhammad Moazam
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-14
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
The arterioles and venules (AV) classification of retinal vasculature is considered as the first step in the development of an automated system for analysing the vasculature biomarker association with disease prognosis.
Most of the existing AV classification methods depend on the accurate segmentation of retinal blood vessels.
Moreover, the unavailability of large-scale annotated data is a major hindrance in the application of deep learning techniques for AV classification.
This paper presents an encoder-decoder based fully convolutional neural network for classification of retinal vasculature into arterioles and venules, without requiring the preliminary step of vessel segmentation.
An optimized multiloss function is used to learn the pixel-wise and segment-wise retinal vessel labels.
The proposed method is trained and evaluated on DRIVE, AVRDB, and a newly created AV classification dataset; and it attains 96%, 98%, and 97% accuracy, respectively.
The new AV classification dataset is comprised of 700 annotated retinal images, which will offer the researchers a benchmark to compare their AV classification results.
American Psychological Association (APA)
Badawi, Sufian A.& Fraz, Muhammad Moazam. 2019. Multiloss Function Based Deep Convolutional Neural Network for Segmentation of Retinal Vasculature into Arterioles and Venules. BioMed Research International،Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1125564
Modern Language Association (MLA)
Badawi, Sufian A.& Fraz, Muhammad Moazam. Multiloss Function Based Deep Convolutional Neural Network for Segmentation of Retinal Vasculature into Arterioles and Venules. BioMed Research International No. 2019 (2019), pp.1-17.
https://search.emarefa.net/detail/BIM-1125564
American Medical Association (AMA)
Badawi, Sufian A.& Fraz, Muhammad Moazam. Multiloss Function Based Deep Convolutional Neural Network for Segmentation of Retinal Vasculature into Arterioles and Venules. BioMed Research International. 2019. Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1125564
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1125564