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Improved local morphology fitting active contour with weighted data term for vessel segmentation

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成果类型:
期刊论文、会议论文
作者:
Xuan Wang;Kaiqiong Sun
通讯作者:
Sun, K.
作者机构:
[Wang X.; Sun K.] School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, China
通讯机构:
[Sun, K.] S
School of Mathematics and Computer Science, China
语种:
英文
关键词:
Inhomogeneous image;Level set method;Local image information;Vessel segmentation
期刊:
Advances in Intelligent Systems and Computing
ISSN:
2194-5357
年:
2020
卷:
1006
页码:
55-62
会议名称:
4th International Conference on Intelligent Computing, Communication and Devices, ICCD 2018
会议论文集名称:
Recent Trends in Intelligent Computing, Communication and Devices
会议时间:
7 December 2018 through 9 December 2018
主编:
Vipul Jain<&wdkj&>Srikanta Patnaik<&wdkj&>Florin Popențiu Vlădicescu<&wdkj&>Ishwar K. Sethi
出版者:
Springer, Singapore
ISBN:
978-981-13-9405-8
机构署名:
本校为第一机构
院系归属:
数学与计算机学院
摘要:
An improved local morphology fitting active contour model with weighted data term is proposed in this paper for automated segmentation of the vascular tree on 2-D angiogram. In the original local morphology fitting model, morphological fuzzy minimum and maximum opening are adopted to approach the background and vessel object, separately. The structuring elements used in the morphology operator are linear ones, and their scale and orientation are computed from the image. The energy of the active contour model is minimized through a level set fra...

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