Cost Function Selection for a Graph-Based Segmentation in OCT Retinal Images

被引：0

作者：

Gonzalez, A. ^{[1
]}

Penedo, M. G. ^{[1
]}

Vazquez, S. G. ^{[1
]}

Novo, J. ^{[1
]}

Charlon, P. ^{[2
]}

机构：

[1] Univ A Coruna, Dept Comp Sci, VARPA Grp, La Coruna, Spain

[2] Inst Ophthalmol Gomez Ulla, Santiago De Compostela, Spain

来源：

COMPUTER AIDED SYSTEMS THEORY, PT II | 2013年 / 8112卷

关键词：

image segmentation; OCT retinal image; cost function; minimum closed set; graph;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is based on a methodology for segmentation of the main retinal layers in Optical Coherence Tomography (OCT) images. The input image is transformed into a geometric graph and the layers to be detected will be given by its minimum-cost closed set. The main problem in this method is the selection of the appropriate cost functions associated to the graph, because of the variety of anomalies that images from patients might have.

引用

页码：125 / 132

页数：8

共 5 条

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