Max-min central vein detection in retinal fundus images

被引：12

作者：

Azegrouz, Hind ^{[1
]}

Trucco, Emanuele ^{[1
]}

机构：

[1] Heriot Watt Univ, Sch Engn & Phys Sci, Dept Elect Electron & Comp Engn, Edinburgh EH14 4AS, Midlothian, Scotland

来源：

2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS | 2006年

关键词：

retinal; central; vein; vessel; graph;

D O I：

10.1109/ICIP.2006.313145

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];

摘要：

This paper describes a new framework for the automated tracking of the central retinal vein in retinal images. The procedure first computes a binary image of the retinal vasculature, then obtains the skeleton (medial axis) of the vascular network. Terminal and branching points of the network are then located, and the network converted into a graph representation including length and thickness information for all vessels. Finally, a MaxMin approach is used to locate the central vein:The candidates central vein are the minimal paths from the optic disk to all terminal nodes found using Dijkstra algorithm. The actual central vein is selected among the all candidates by maximizing a merit function estimating the total vessel area in the image. Results are presented and compared with those provided by a manual classification on 20 images of the DRIVE set. An overall performance ratio of 92% is achieved.

引用

页码：1925 / +

页数：2

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