Automatic Classification of Retinal Vessels Using Structural and Intensity Information

• Type: Article in International Conference Proceedings Book
• Date: 2013

Authors

Behdad Dashtbozorg (Author) Other; Ana Maria Mendonca (Author) FEUP; Aurelio Campilho (Author) FEUP

Conference proceedings International

Title: PATTERN RECOGNITION AND IMAGE ANALYSIS, IBPRIA 2013

Pages: 584-591

6th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)

Funchal, PORTUGAL, JUN 05-07, 2013

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 7 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-008-DFQ

DOI: 10.1007/978-3-642-38628-2_71

Abstract (EN): This paper presents an automatic approach for artery/vein (A/V) classification based on the analysis of a graph representing the structure of the retinal vasculature. The entire vascular tree is classified by deciding on the type of each intersection point (graph node) and assigning one of two classes to each vessel segment (graph link). The final label for each vessel segment is accomplished by a combination of structural information taken from the graph (link class) with intensity features measured in the original color image. An accuracy of 88.0% was achieved for the 40 images of the INSPIRE-AVR dataset, thus demonstrating that our method outperforms state-of-the-art approaches for A/V classification.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8