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Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method
Joint Authors
Duan, Fu-qing
Tian, Yun
Wang, Wei
Pan, Yutong
Zhao, Shifeng
Wang, Qingjun
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-10-31
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
The segmentation of coronary arteries is a vital process that helps cardiovascular radiologists detect and quantify stenosis.
In this paper, we propose a fully automated coronary artery segmentation from cardiac data volume.
The method is built on a statistics region growing together with a heuristic decision.
First, the heart region is extracted using a multi-atlas-based approach.
Second, the vessel structures are enhanced via a 3D multiscale line filter.
Next, seed points are detected automatically through a threshold preprocessing and a subsequent morphological operation.
Based on the set of detected seed points, a statistics-based region growing is applied.
Finally, results are obtained by setting conservative parameters.
A heuristic decision method is then used to obtain the desired result automatically because parameters in region growing vary in different patients, and the segmentation requires full automation.
The experiments are carried out on a dataset that includes eight-patient multivendor cardiac computed tomography angiography (CTA) volume data.
The DICE similarity index, mean distance, and Hausdorff distance metrics are employed to compare the proposed algorithm with two state-of-the-art methods.
Experimental results indicate that the proposed algorithm is capable of performing complete, robust, and accurate extraction of coronary arteries.
American Psychological Association (APA)
Tian, Yun& Pan, Yutong& Duan, Fu-qing& Zhao, Shifeng& Wang, Qingjun& Wang, Wei. 2016. Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method. BioMed Research International،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1097362
Modern Language Association (MLA)
Tian, Yun…[et al.]. Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method. BioMed Research International No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1097362
American Medical Association (AMA)
Tian, Yun& Pan, Yutong& Duan, Fu-qing& Zhao, Shifeng& Wang, Qingjun& Wang, Wei. Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1097362
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1097362