TRAMLINE AND NP WINDOWS ESTIMATION FOR ENHANCED UNSUPERVISED RETINAL VESSEL SEGMENTATION

被引：0
|
作者：
Allen, Katherine [1 ]
Joshi, Niranjan [1 ]
Noble, J. Alison [1 ]
机构：
[1] Univ Oxford, Inst Biomed Engn, Dept Engn Sci, Oxford OX1 2JD, England
来源：
2011 8TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO | 2011年
关键词：
Blood vessels; Image segmentation; IMAGES;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
This paper presents a novel unsupervised vascular segmentation algorithm which is applied to retinal fundus images, however could be generalised to any two-dimensional vascular image. The algorithm presents a new fully automatic framework for vessel segmentation and comprises the following features: novel application of the NPWindows method for intensity distribution estimation on localised 'image patches'; specialised treatment of small vessels by transformation to the one-dimensional domain to ensure enhanced detection; and excellent accuracy (93.42%) as compared with the recent active-contour based method by Al-Diri et al. [1] (92.58%) on the public DRIVE retinal image database [2].
引用
收藏
页码：1387 / 1390
页数：4
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