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http://dx.doi.org/10.9718/JBER.2017.38.6.295

Comparison of Blooming Artifact Reduction Using Image Segmentation Method in CT Image  

Kim, Jung-Hun (School of Electronics Engineering, Kyungpook National University)
Park, Ji-Eun (Department of Biomedical Engineering, Kyungpook National University)
Park, Yu-Jin (Department of Biomedical Engineering, Kyungpook National University)
Ji, In-Hee (Department of Nursing, School of Medicine, Kyungpook National University)
Lee, Jong-Min (Department of Radiology, School of Medicine, Kyungpook National University)
Cho, Jin-Ho (School of Electronics Engineering, Kyungpook National University)
Publication Information
Journal of Biomedical Engineering Research / v.38, no.6, 2017 , pp. 295-301 More about this Journal
Abstract
In this study, We subtracted the calcification blooming artifact from MDCT images of coronary atherosclerosis patients and verified their accuracy and usefulness. We performed coronary artery calcification stenosis phantom and a program to subtract calcification blooming artifact by applying 8 different image segmentation method (Otsu, Sobel, Prewitt, Canny, DoG, Region Growing, Gaussian+K-mean clustering, Otsu+DoG). As a result, In the coronary artery calcification stenosis phantom with the lumen region 5 mm the calcification blooming artifact was subtracted in the application of the mixture of Gaussian filtering and K- Clustering algorithm, and the value was close to the actual calcification region. These results may help to accurately diagnose coronary artery calcification stenosis.
Keywords
Calcification; Blooming Artifact; Coronary artery; Sclerosis;
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Times Cited By KSCI : 4  (Citation Analysis)
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