Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network

Manual postprocessing of computed tomography angiography (CTA) images is extremely labor intensive and error prone. Here, the authors propose an artificial intelligence reconstruction system that can automatically achieve CTA reconstruction in healthcare services.

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Autores principales:	Fan Fu, Jianyong Wei, Miao Zhang, Fan Yu, Yueting Xiao, Dongdong Rong, Yi Shan, Yan Li, Cheng Zhao, Fangzhou Liao, Zhenghan Yang, Yuehua Li, Yingmin Chen, Ximing Wang, Jie Lu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/18ee8e0a573c47d28d028344572ab4f2
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spelling	oai:doaj.org-article:18ee8e0a573c47d28d028344572ab4f22021-12-02T18:14:16ZRapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network10.1038/s41467-020-18606-22041-1723https://doaj.org/article/18ee8e0a573c47d28d028344572ab4f22020-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-18606-2https://doaj.org/toc/2041-1723Manual postprocessing of computed tomography angiography (CTA) images is extremely labor intensive and error prone. Here, the authors propose an artificial intelligence reconstruction system that can automatically achieve CTA reconstruction in healthcare services.Fan FuJianyong WeiMiao ZhangFan YuYueting XiaoDongdong RongYi ShanYan LiCheng ZhaoFangzhou LiaoZhenghan YangYuehua LiYingmin ChenXiming WangJie LuNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-12 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Fan Fu Jianyong Wei Miao Zhang Fan Yu Yueting Xiao Dongdong Rong Yi Shan Yan Li Cheng Zhao Fangzhou Liao Zhenghan Yang Yuehua Li Yingmin Chen Ximing Wang Jie Lu Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network
description	Manual postprocessing of computed tomography angiography (CTA) images is extremely labor intensive and error prone. Here, the authors propose an artificial intelligence reconstruction system that can automatically achieve CTA reconstruction in healthcare services.
format	article
author	Fan Fu Jianyong Wei Miao Zhang Fan Yu Yueting Xiao Dongdong Rong Yi Shan Yan Li Cheng Zhao Fangzhou Liao Zhenghan Yang Yuehua Li Yingmin Chen Ximing Wang Jie Lu
author_facet	Fan Fu Jianyong Wei Miao Zhang Fan Yu Yueting Xiao Dongdong Rong Yi Shan Yan Li Cheng Zhao Fangzhou Liao Zhenghan Yang Yuehua Li Yingmin Chen Ximing Wang Jie Lu
author_sort	Fan Fu
title	Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network
title_short	Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network
title_full	Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network
title_fullStr	Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network
title_full_unstemmed	Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network
title_sort	rapid vessel segmentation and reconstruction of head and neck angiograms using 3d convolutional neural network
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/18ee8e0a573c47d28d028344572ab4f2
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Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network

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