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Titlebook: Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic V; First Challenge, SEG Antonio Pepe,Gia

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發(fā)表于 2025-3-21 19:26:43 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic V
副標(biāo)題First Challenge, SEG
編輯Antonio Pepe,Gian Marco Melito,Jan Egger
視頻videohttp://file.papertrans.cn/864/863804/863804.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic V; First Challenge, SEG Antonio Pepe,Gia
描述This book constitutes the First Segmentation of the Aorta Challenge, SEG.A. 2023, which was held in conjunction with the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, on October 8, 2023.?.The 8 full and 3 short papers presented have been carefully reviewed and selected for inclusion in the book. They focus specifically on robustness, visual quality and meshing of automatically generated segmentations of aortic vessel trees from CT imaging.?The challenge was organized?as a ”container submission” challenge, where participants had to upload their?algorithms to Grand Challenge in the form of Docker containers. Three tasks?were created for SEG.A. 2023..
出版日期Conference proceedings 2024
關(guān)鍵詞multicenter; segmentation; shape modelling; visualization; meshing aorta; CTA; artificial intelligence; sen
版次1
doihttps://doi.org/10.1007/978-3-031-53241-2
isbn_softcover978-3-031-53240-5
isbn_ebook978-3-031-53241-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書目名稱Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic V影響因子(影響力)




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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/s/image/863804.jpg
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https://doi.org/10.1007/978-3-031-53241-2multicenter; segmentation; shape modelling; visualization; meshing aorta; CTA; artificial intelligence; sen
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