DWT-Based Segmentation Method for Coronary Arteries

被引：0
|
作者：
Shuo-Tsung Chen
Pei-Kai Hung
Muh-Shi Lin
Chao-Yu Huang
Chung-Ming Chen
Tzung-Dau Wang
Wen-Jeng Lee
机构：
[1] National Taiwan University,Institute of Biomedical Engineering
[2] Tunghai University,Department of Applied Mathematics
[3] Taipei City Hospital,Department of Neurosurgery
[4] New Taipei City Hospital,Division of Neurosurgery, Department of Surgery
[5] National Yang-Ming University,Department of Surgery, Faculty of Medicine, School of Medicine
[6] National Taiwan University Hospital,Cardiovascular Center and Division of Cardiology, Department of Internal Medicine
[7] National Taiwan University Hospital,Department of Medical Imaging
来源：
Journal of Medical Systems | 2014年 / 38卷
关键词：
Coronary arteries; Computed tomography angiography; Automatically; Region growing; Discrete wavelet transformation; -mean operation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This work presents a new method for segmenting coronary arteries automatically in computed tomography angiography (CTA) data sets. The method automatically isolates heart and coronary arteries from surrounding structures and search for the probable location of coronary arteries by 3D region growing. Based on the dilation of the probable location, discrete wavelet transformation (DWT) and λ – mean operation complete accurate detection of coronary arties. Finally, the proposed method is tested on clinical CTA data-sets. The results on clinical datasets show that the proposed method is able to extract each branch of arteries when comparing to commercial software GE Healthcare and delineated ground truth.
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