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Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images.

, , , , и . SASHIMI@MICCAI, том 11037 из Lecture Notes in Computer Science, стр. 100-110. Springer, (2018)

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Seonghye Jeon

Jinseong Jeon

Nadja Jeon

Donghwan Jeon

Jeongho Jeon

 

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A fast seed detection using local geometrical feature for automatic tracking of coronary arteries in CTA., , , , , , и . Comput. Methods Programs Biomed., 117 (2): 179-188 (2014)Core-Shell Detection in Images of Polymer Microbeads., , и . FGIT-MulGraB/BSBT/IUrC, том 353 из Communications in Computer and Information Science, стр. 9-15. Springer, (2012)Fully Automatic Segmentation of Coronary Arteries Based on Deep Neural Network in Intravascular Ultrasound Images., , , , , и . CVII-STENT/LABELS@MICCAI, том 11043 из Lecture Notes in Computer Science, стр. 161-168. Springer, (2018)Coronary luminal and wall mask prediction using convolutional neural network., , , , , , , , , и . ISBI, стр. 1049-1052. IEEE, (2017)Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images., , , , и . SASHIMI@MICCAI, том 11037 из Lecture Notes in Computer Science, стр. 100-110. Springer, (2018)Maximum a posteriori estimation method for aorta localization and coronary seed identification., , , , , , , , и . Pattern Recognit., (2017)