Research Article | OPEN ACCESS
3D Coronary Artery Reconstruction using SVM
P. Mirunalini and S.M. Jaisakthi
SSN College of Engineering, Chennai-603110, Tamilnadu, India
Research Journal of Applied Sciences, Engineering and Technology 2015 7:685-691
Received: January 31, 2015 | Accepted: March 1, 2015 | Published: November 05, 2015
Abstract
Coronary arteries are the vascular structures that supply blood to the heart muscle. Identification of anomalies in the coronary arteries from the 2D slices is a challenging and time consuming process. Segmenting the coronary arteries from the 2D slices and reconstructing into 3D images help in analyzing abnormalities and enable easy diagnosis for medical experts. Hence in this research work, we propose an automated system that extracts coronary arteries from 2D slices of Computed Tomography Angiography (CTA) images using machine learning techniques and reconstruct them into 3D coronary artery tree. Our proposed method extracts statistical features from the arteries and classifies them as coronary and non-coronary arteries using Support Vector Machine (SVM). Classified coronary arteries from 2D slices are reconstructed into 3D coronary artery tree using Maximum Intensity Projection (MIP) algorithm. The performance of our proposed technique is evaluated using Structure Similarity Index Metric (SSIM).
Keywords:
Classification, coronary artery segmentation, machine learning technique, MIP, reconstruction, SVM,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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