SIA OpenIR  > 机器人学研究室
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)
Department机器人学研究室
Conference Name14th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2017
Conference DateJuly 26-28, 2017
Conference PlaceMadrid, Spain
Author of SourceInstitute for Systems and Technologies of Information, Control and Communication (INSTICC)
Source PublicationICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics
PublisherSciTePress
Publication PlaceSetúbal, Portugal
2017
Pages405-410
Indexed ByEI
EI Accession number20173804169005
Contribution Rank1
ISBN978-9-89758-264-6
KeywordLeft Ventricle State-of-the-art Segmentation Methods Segmentation Thresholding
AbstractIn 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.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/20996
Collection机器人学研究室
Corresponding AuthorWang ZZ(王振洲)
AffiliationState Key Labs for Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, No. 114 Nanta Street, Shenhe District, Shenyang, Liaoning Province, China
Recommended Citation
GB/T 7714
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.
Files in This Item: Download All
File Name/Size DocType Version Access License
Identifying the left(8113KB)会议论文 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xiong JJ(熊晶晶)]'s Articles
[Yang YM(杨永明)]'s Articles
[Wang ZZ(王振洲)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xiong JJ(熊晶晶)]'s Articles
[Yang YM(杨永明)]'s Articles
[Wang ZZ(王振洲)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xiong JJ(熊晶晶)]'s Articles
[Yang YM(杨永明)]'s Articles
[Wang ZZ(王振洲)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Identifying the left ventricle optimally in cardiac mr images by comparing state-of-the-art segmentation methods.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.