Abstract
Aortic dissection (AD) is a dangerous disease usually diagnosed by computed tomography angiography. Segmentation of true and false lumens of aortic trunk and major branches is very important for the diagnosis and treatment of this disease. In this paper, we proposed a fully automatic vessel analysis algorithm for dissected aorta, which can output centerlines, true lumen, and false lumen of trunk and major branches, and perfusion source of branches. In our experiment, the mean dice similarity coefficient (DSC) of true lumen segmentation was 0.939 for trunk and 0.912 for branch while the mean DSC of whole lumen segmentation was 0.974 for trunk and 0.937 for branch, and the classification accuracy of branch perfusion source was 0.863.
This work was supported in part by the National Natural Science Foundation of China under Grants 61976121 and 82071921.
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Fang, H. et al. (2022). Vessel Extraction and Analysis of Aortic Dissection. In: Puyol Antón, E., et al. Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science(), vol 13131. Springer, Cham. https://doi.org/10.1007/978-3-030-93722-5_6
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DOI: https://doi.org/10.1007/978-3-030-93722-5_6
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