Current Result Document :
| 한글제목(Korean Title) |
딥러닝 기술을 이용한 복셀 분류에 관한 연구 |
| 영문제목(English Title) |
A Study of voxel classification using deep learning technology |
| 저자(Author) |
자빈 파라
김재일
Jabeen Farah
Jaeil Kim
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| 원문수록처(Citation) |
VOL 49 NO. 02 PP. 0767 ~ 0769 (2022. 12) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease that is the global leading cause of death. Coronary artery calcium scoring is one of the most common methods to detect calcified plaque in coronary arteries one of the major future causes of coronary artery disease risk. The cause of the Coronary artery is wasted, or calcium accumulated in the walls of the coronary artery. Recent development in deep learning exceedingly popular in medical images, however very few models have been developed to integrate both clinical and imaging date. In our work, we have used CT images and electronic health records also known as EMR Dataset of patients. The data consists of 500 patients in raw CT DICOM format has been collected from Asan Medical Center in South Korea has been annotated by cardiac radiologist labeled as CAC. And used CT-EMR model for classification of calcification in voxels. We have achieved accuracy of 0.94 by implemented our proposed methodology. And compared our experiments with other proposed CAC classification models. |
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