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Identifying the left ventricle optimally in cardiac mr images by comparing state-of-the-art segmentation methods
Xiong JJ(熊晶晶); Yang YM(杨永明); Wang ZZ(王振洲)
作者部门机器人学研究室
会议名称14th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2017
会议日期July 26-28, 2017
会议地点Madrid, Spain
会议主办者Institute for Systems and Technologies of Information, Control and Communication (INSTICC)
会议录名称ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics
出版者SciTePress
出版地Setúbal, Portugal
2017
页码405-410
收录类别EI
EI收录号20173804169005
产权排序1
ISBN号978-9-89758-264-6
关键词Left Ventricle State-of-the-art Segmentation Methods Segmentation Thresholding
摘要In medical diagnosis, the movement of the left ventricle (LV) could be used to estimate the volume of the left ventricle and the dyssynchrony of the heart, which can provide the basis for diagnosis of heart diseases. Identification of the LV endocardium, especially the images with poor image quality and images in apical or basal slices, is still a very challenging problem. In this paper, an automatic segmentation method based on threshold is proposed. This method works well in image both with good quality and bad quality. We tested the proposed SDD method with other 15 state-of-the-art segmentation methods by 104 frames of testing Cardiac MR images from Computing and Computer Assisted Intervention (MICCAI) 2009 challenge. Finally, we assessed the deviation between the automatically segmented and benchmark manual contours. The proposed method achieved 0.9172 average Dice metric, 1.9817 mm average perpendicular distance (APD). These results compared with other methods indicate that the proposed SDD method is an effective and viable method to identify the boundary of left ventricle.
语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/20996
专题机器人学研究室
通讯作者Wang ZZ(王振洲)
作者单位State Key Labs for Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, No. 114 Nanta Street, Shenhe District, Shenyang, Liaoning Province, China
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Xiong JJ,Yang YM,Wang ZZ. Identifying the left ventricle optimally in cardiac mr images by comparing state-of-the-art segmentation methods[C]//Institute for Systems and Technologies of Information, Control and Communication (INSTICC). Setúbal, Portugal:SciTePress,2017:405-410.
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