An approach to coronary vessels detection in X-ray rotational angiography

被引：0

作者：

Bravo, A. ^{[1
]}

Medina, R. ^{[2
]}

Garreau, M. ^{[3
,4
]}

Bedossa, M. ^{[5
]}

Toumoulin, C. ^{[3
,4
]}

Le Breton, H. ^{[3
,4
,5
]}

机构：

[1] Univ Nacl Expt Tachira, Grp Bioingn Decanto Invest, San Cristobal 5001, Venezuela

[2] Univ Los Andes, Grp Ingenieria Biomed, Merida 5110, Venezuela

[3] INSERM, U 642, F-35000 Rennes, France

[4] Univ Rennes 1, Lab Trateiment Signal lImage, F-35042 Rennes, France

[5] CHU, Ctr Cardio Pneum, F-35033 Rennes, France

来源：

IV LATIN AMERICAN CONGRESS ON BIOMEDICAL ENGINEERING 2007, BIOENGINEERING SOLUTIONS FOR LATIN AMERICA HEALTH, VOLS 1 AND 2 | 2008年 / 18卷 / 1,2期

关键词：

Cardiac images; rotational angiography equipment; coronary vessels; segmentation; unsupervised clustering;

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：

An unsupervised clustering framework for automatic detection of coronary vessels in bidimensional (2D) X-ray rotational angiography is reported. The proposed approach consists of three consecutive steps: 1) vessel enhancement; 2) initial segmentation based on a simple linkage region growing algorithm; 3) optimization of the initial segmentation using a multiple linkage region growing method. Results obtained after applying this method to monoplane rotational X-ray image sequences are presented.

引用

页码：254 / +

页数：3

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