research-article
Authors: Xue Shi, Lijun Tang, Xiaoping Yang, ShaoxiangZhang, Chunming Li
ISICDM 2018: Proceedings of the 2nd International Symposium on Image Computing and Digital Medicine
Pages 51 - 54
Published: 13 October 2018 Publication History
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Abstract
In this paper, anatomical characteristic of convexity of left ventricles (LV) is incorporated in the level set segmentation framework to improve the accuracy of the algorithm. In order to maintain the convexity of endocardial and epicardial contour, we use the two-layer level set model combined with periodical convexification of the level sets, which eliminates the troublesome interference caused by the papillary muscle and the trabeculae. We use the MICCAI 2009 left ventricle segmentation challenge data to test and validate our method. Qualitative experiments demonstrate the effectiveness of our algorithm.
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Cited By
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- Sivakumar KLavanya SHimanandini KKeerthana V(2020)A Unified Automated Segmentation Technique for the Left Ventricle Segmentation in Cardiac MRIIOP Conference Series: Materials Science and Engineering10.1088/1757-899X/993/1/012068993(012068)Online publication date: 31-Dec-2020
Index Terms
A Fast Convexity Preserving Level Set Method for Segmentation of Cardiac Left Ventricle
Computing methodologies
Artificial intelligence
Computer vision
Computer vision problems
Image segmentation
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Published In
ISICDM 2018: Proceedings of the 2nd International Symposium on Image Computing and Digital Medicine
October 2018
166 pages
ISBN:9781450365338
DOI:10.1145/3285996
Copyright © 2018 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [emailprotected]
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- University of Electronic Science and Technology of China: University of Electronic Science and Technology of China
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 13 October 2018
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Author Tags
- Cardiac Magnetic Resonance Image
- Convexity
- Left Ventricle
- Level Set
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
ISICDM 2018
ISICDM 2018: The 2nd International Symposium on Image Computing and Digital Medicine 2018
October 13 - 14, 2018
Chengdu, China
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- Sivakumar KLavanya SHimanandini KKeerthana V(2020)A Unified Automated Segmentation Technique for the Left Ventricle Segmentation in Cardiac MRIIOP Conference Series: Materials Science and Engineering10.1088/1757-899X/993/1/012068993(012068)Online publication date: 31-Dec-2020
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