3D Registration of the Point Cloud Data Using Parameter Adaptive Super4PCS Algorithm in Medical Image Analysis
文献类型：会议论文
| 作者 | Su S(苏顺)1,2; Song GL(宋国立)1,3 ; Zhao YW(赵忆文)1,3
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| 出版日期 | 2021 |
| 会议日期 | November 12-15, 2021 |
| 会议地点 | Virtual, Online, Japan |
| 关键词 | Medical image registration point cloud registration |
| 页码 | 1-6 |
| 英文摘要 | In this article, we use the parameter-adaptive Super4PCS algorithm to achieve high-precision registration of medical point clouds. First, generate the corresponding point cloud from the biological data (CT, MRI) to be registered. Then analyze the characteristics of the point cloud to be registered, and use it to adaptively set the parameters of Super4PCS, and finally perform point cloud registration. We compare the performance of six different algorithms with their accuracy and robustness. The accuracy, robustness of our method are the best. At the same time, no parameter input is required which is very convenient for medical workers. Experiments on medical models demonstrate the efficiency and robustness of our algorithm. |
| 产权排序 | 1 |
| 会议录 | Proceedings of 2021 4th International Conference on Digital Medicine and Image Processing, DMIP 2021
 |
| 会议录出版者 | ACM |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-4503-8408-7 |
| 源URL | [http://ir.sia.cn/handle/173321/30576]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Song GL(宋国立) |
| 作者单位 | 1.The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, China 2.School of Computer Science and Technology, University of Chinese Academy of Sciences, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, China |
| 推荐引用方式 GB/T 7714 | Su S,Song GL,Zhao YW. 3D Registration of the Point Cloud Data Using Parameter Adaptive Super4PCS Algorithm in Medical Image Analysis[C]. 见:. Virtual, Online, Japan. November 12-15, 2021. |
入库方式： OAI收割
来源：沈阳自动化研究所
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