Parallel Multiscale Feature Extraction and Region Growing: Application in Retinal Blood Vessel Detection

被引：118

作者：

Palomera-Perez, Miguel A. ^{[1
]}

Elena Martinez-Perez, M. ^{[2
]}

Benitez-Perez, Hector ^{[1
]}

Luis Ortega-Arjona, Jorge ^{[3
]}

机构：

[1] Univ Nacl Autonoma Mexico, Inst Invest Matemat Aplicadas & Sistemas, Dept Comp Syst Engn & Automatizat, Mexico City 01600, DF, Mexico

[2] Univ Nacl Autonoma Mexico, Inst Invest Matemat Aplicadas & Sistemas, Dept Comp Sci, Mexico City 01000, DF, Mexico

[3] Univ Nacl Autonoma Mexico, Dept Math, Fac Sci, Mexico City 01000, DF, Mexico

来源：

IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE | 2010年 / 14卷 / 02期

关键词：

Data processing; distributed algorithms; image analysis; image processing; image segmentation; parallel programming; SEGMENTATION; ABNORMALITIES; DISEASE; IMAGES;

D O I：

10.1109/TITB.2009.2036604

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a parallel implementation based on insight segmentation and registration toolkit for a multiscale feature extraction and region growing algorithm, applied to retinal blood vessels segmentation. This implementation is capable of achieving an accuracy (Ac) comparable to its serial counterpart ( about 92%), but 8 to 10 times faster. In this paper, the Ac of this parallel implementation is evaluated by comparison with expert manual segmentation ( obtained from public databases). On the other hand, its performance is compared with previous published serial implementations. Both these characteristics make this parallel implementation feasible for the analysis of a larger amount of high-resolution retinal images, achieving a faster and high-quality segmentation of retinal blood vessels.

引用

页码：500 / 506

页数：7

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