Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO)

被引:34
作者
Estrada, Rolando [1 ]
Tomasi, Carlo [1 ]
Cabrera, Michelle T. [4 ]
Wallace, David K. [2 ]
Freedman, Sharon F. [2 ]
Farsiu, Sina [2 ,3 ]
机构
[1] Duke Univ, Dept Comp Sci, Durham, NC 27708 USA
[2] Duke Univ, Dept Ophthalmol, Durham, NC 27708 USA
[3] Duke Univ, Dept Biomed Engn, Durham, NC 27708 USA
[4] Univ N Carolina, Dept Ophthalmol, Chapel Hill, NC 27599 USA
来源
BIOMEDICAL OPTICS EXPRESS | 2012年 / 3卷 / 02期
关键词
RETINAL IMAGES; PLUS DISEASE; RETINOPATHY; PREMATURITY; EXTRACTION; AGREEMENT;
D O I
10.1364/BOE.3.000327
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
We present a methodology for extracting the vascular network in the human retina using Dijkstra's shortest-path algorithm. Our method preserves vessel thickness, requires no manual intervention, and follows vessel branching naturally and efficiently. To test our method, we constructed a retinal video indirect ophthalmoscopy (VIO) image database from pediatric patients and compared the segmentations achieved by our method and state-of-the-art approaches to a human-drawn gold standard. Our experimental results show that our algorithm outperforms prior state-of-the-art methods, for both single VIO frames and automatically generated, large field-of-view enhanced mosaics. We have made the corresponding dataset and source code freely available online. (C) 2012 Optical Society of America
引用
收藏
页码:327 / 339
页数:13
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