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- W3112701227 abstract "Coronary atherosclerotic heart disease (CAD) refers to a heart disease caused by myocardial ischemia, hypoxia or necrosis due to narrowing or obstruction of the blood vessel cavity, which seriously endangers the life and health of people around the world. The precise extraction of coronary arteries has received extensive attention. The main work of this article is as follows: Image enhancement processing is performed by a multi-scale enhancement filter based on Hessian matrix to improve the contrast of the coronary artery area in the CTA image. By using the fast training of U-Net network and the accurate feature recognition method, the region of coronary artery of interest in CTA image of human body is located and roughly segmented, which solves the problem that the location and shape of coronary artery in CTA image are different, which easily leads to segmentation error. By designing a variety of conditionally constrained level set algorithms for contour evolution, the accurate segmentation and extraction of coronary arteries is finally achieved. A three-dimensional visualization system of coronary arteries is designed by moving cube algorithm. Compared with other typical algorithms, the segmentation algorithm designed in this paper can increase the average overlap rate by up to 12.41%." @default.
- W3112701227 created "2020-12-21" @default.
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- W3112701227 date "2020-09-11" @default.
- W3112701227 modified "2023-09-23" @default.
- W3112701227 title "Coronary artery CTA image segmentation and three-dimensional visualization Based on U-Net" @default.
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- W3112701227 doi "https://doi.org/10.1145/3429889.3429901" @default.
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