Identifying the left ventricle optimally in cardiac mr images by comparing state-of-the-art segmentation methods
文献类型：会议论文
| 作者 | Xiong JJ(熊晶晶); Yang YM(杨永明) ; Wang ZZ(王振洲)
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| 出版日期 | 2017 |
| 会议日期 | July 26-28, 2017 |
| 会议地点 | Madrid, Spain |
| 关键词 | Left Ventricle State-of-the-art Segmentation Methods Segmentation Thresholding |
| 页码 | 405-410 |
| 英文摘要 | 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. |
| 源文献作者 | Institute for Systems and Technologies of Information, Control and Communication (INSTICC) |
| 产权排序 | 1 |
| 会议录 | ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics
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| 会议录出版者 | SciTePress |
| 会议录出版地 | Setúbal, Portugal |
| 语种 | 英语 |
| ISBN号 | 978-989-7582-64-6 |
| 源URL | [http://ir.sia.cn/handle/173321/20996]  |
| 专题 | 沈阳自动化研究所_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 |
| 推荐引用方式 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]. 见:. Madrid, Spain. July 26-28, 2017. |
入库方式： OAI收割
来源：沈阳自动化研究所
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