DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Science, Engineering and Technology(IJASEAT)-IJASEAT |
 Journal Home Volume Issue |
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Issue |
Volume-6, Issue-4 ( Oct, 2018 ) | |||||||||
Paper Title |
Study of MRI-based Aortic Arch to Left Subclavian Artery In-Stent Restenosis | |||||||||
Author Name |
Yung-Kuan Chan, Lin Hui Han, Wan-Ting Hu | |||||||||
Affilition |
Department of Management Information Systems, National Chung Hsing University, Taiwan, ROC Division of cardiovascular surgery, China medical university hospital | |||||||||
Pages |
53-59 | |||||||||
Abstract |
Stent implantation is a common treatment for Left subclavian artery occlusion. Unfortunately, it is possible that causes In-Stent Restenosis. The most comment of In-Stent Restenosis is excessive thrombus that squeeze the stent and cause vascular occlusion, so that "Drug-Eluting Stent" and "Assurance" were produced. Besides, Stent’s size is an important factor for preventing In-Stent Restenosis. Therefore, doctors could use previous medical records to select which Stents is suitable for patient. However, due to the enormous medical records, it often takes a lot of time when the results are calculated by healthcare professionals. To solve those problems, in this paper a system of stent segmentation and vascular occlusion identification is provided. Experimental results show that the system obtains the Precision 98.6%of Left Subclavian Artery Stent segmentation, Recall 89.2% and F-measure 93.6%. In addition, the recognition rate of vascular occlusion is 100%. Index Terms – Subclavian steal syndrome, In-Stent Restenosis, Image segmentation, Image recognition. | |||||||||
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