UPM Institutional Repository

A fast and accurate method for automatic coronary arterial tree extraction in angiograms


Tayebi, Rohollah Moosavi and Sulaiman, Puteri Suhaiza and O. K. Rahmat, Rahmita Wirza and Dimon, Mohd Zamrin and Kadiman, Suhaini and Khalid, Fatimah and Mazaheri, Samaneh (2014) A fast and accurate method for automatic coronary arterial tree extraction in angiograms. Journal of Computer Science, 10 (10). pp. 2060-2076. ISSN 1549-3636; ESSN: 1552-6607


Coronary arterial tree extraction in angiograms is an essential component of each cardiac image processing system. Once physicians decide to check up coronary arteries from x-ray angiograms, extraction must be done precisely, fast, automatically and including whole arterial tree to help diagnosis or treatment during the cardiac surgical operation. This application is very helpful for the surgeon on deciding the target vessels prior to coronary artery bypass graft surgery. Some techniques and algorithms are proposed for extracting coronary arteries in angiograms. However, most of them suffer from some disadvantages such as time complexity, low accuracy, extracting only parts of main arteries instead of the full coronary arterial tree, need manual segmentation, appearance of artifacts and so forth. This study presents a new method for extracting whole coronary arterial tree in angiography images using Starlet wavelet transform. To this end, firstly we remove noise from raw angiograms and then sharpen the coronary arteries. Then coronary arterial tree is extracted by applying a modified Starlet wavelet transform and afterwards the residual noises and artifacts are cleaned. For evaluation, we measure proposed method performance on our created data set from 4932 Left Coronary Artery (LCA) and Right Coronary Artery (RCA) angiograms and compared with some state-of-the-art approaches. The proposed method shows much higher accuracy 96% for LCA and 97% for RCA, higher sensitivity 86% for LCA and 89% for RCA, higher specificity 98% for LCA and 99% for RCA and also higher precision 87% for LCA and 93% for RCA angiograms.

Download File

[img] Text
Restricted to Repository staff only

Download (847kB)

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.3844/jcssp.2014.2060.2076
Publisher: Science Publications
Keywords: Medical image processing; Coronary artery extraction; Discrete wavelet transform; Starlet wavelet transform; Angiogram
Depositing User: Nabilah Mustapa
Date Deposited: 31 Jul 2015 10:42
Last Modified: 24 Oct 2018 03:43
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3844/jcssp.2014.2060.2076
URI: http://psasir.upm.edu.my/id/eprint/36160
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item