Standard plane localization in ultrasound by radial component
文献类型：会议论文
| 作者 | Yang, Xin; Ni, Dong; Qin, Jing; Li, Shengli; Wang, Tianfu; Chen, Siping; Heng, Pheng Ann |
| 出版日期 | 2014 |
| 会议名称 | 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, |
| 会议地点 | 中国 |
| 英文摘要 | The acquisition of standard planes is crucial for medical ultrasound (US) diagnosis. In this paper, we present a hierarchical supervised learning framework for automatically detecting standard plane in consecutive 2D US images. The technique is demonstrated by developing a system that localizes fetal abdominal standard plane (FASP) from US videos. We first propose a novel radial component-based model (RCM) to describe the geometric constrains of key anatomical structures (KAS). In order to enhance the detection accuracy, we further adopt random forests classifier for detection of KAS within the regions constrained by RCM. Finally, a second-level classifier combines the results of component detectors to identify a US image as a “FASP” or a “nonFASP”. Experimental results show that our method significantly outperforms both the full abdomen and the separate anatomy detection methods without geometric constrains. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/5586]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2014 |
| 推荐引用方式 GB/T 7714 | Yang, Xin,Ni, Dong,Qin, Jing,et al. Standard plane localization in ultrasound by radial component[C]. 见:2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014,. 中国. |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。