Automatic cone photoreceptor segmentation using graph theory and dynamic programming

被引：64

作者：

Chiu, Stephanie J. ^{[1
]}

Lokhnygina, Yuliya ^{[2
]}

Dubis, Adam M. ^{[3
]}

Dubra, Alfredo ^{[4
,5
]}

Carroll, Joseph ^{[4
,5
]}

Izatt, Joseph A. ^{[1
,3
]}

Farsiu, Sina ^{[1
,3
,6
]}

机构：

[1] Duke Univ, Dept Biomed Engn, Durham, NC 27708 USA

[2] Duke Univ, Dept Biostat & Bioinformat, Durham, NC 27708 USA

[3] Duke Univ, Dept Ophthalmol, Med Ctr, Durham, NC 27710 USA

[4] Med Coll Wisconsin, Dept Ophthalmol, Milwaukee, WI 53226 USA

[5] Med Coll Wisconsin, Dept Biophys, Milwaukee, WI 53226 USA

[6] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27708 USA

来源：

BIOMEDICAL OPTICS EXPRESS | 2013年 / 4卷 / 06期

关键词：

OPTICAL COHERENCE TOMOGRAPHY; ADAPTIVE-OPTICS; HIGH-RESOLUTION; IN-VIVO; IMAGES; DISRUPTION; DENSITY; VISION; EYES;

D O I：

10.1364/BOE.4.000924

中图分类号：

Q5 [生物化学];

学科分类号：

070307 [化学生物学];

摘要：

Geometrical analysis of the photoreceptor mosaic can reveal subclinical ocular pathologies. In this paper, we describe a fully automatic algorithm to identify and segment photoreceptors in adaptive optics ophthalmoscope images of the photoreceptor mosaic. This method is an extension of our previously described closed contour segmentation framework based on graph theory and dynamic programming (GTDP). We validated the performance of the proposed algorithm by comparing it to the state-of-the-art technique on a large data set consisting of over 200,000 cones and posted the results online. We found that the GTDP method achieved a higher detection rate, decreasing the cone miss rate by over a factor of five. (C) 2013 Optical Society of America

引用

收藏

页码：924 / 937

页数：14

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