Knowledge Commons of Institute of Automation,CAS
Real-Time Iris Tracking Using Deep Regression Networks for Robotic Ophthalmic Surgery | |
Qiu, Huaiyu1; Li, Zhen2; Yang, Yu2,3; Xin, Chen4; Bian, Gui-Bin2,5 | |
发表期刊 | IEEE ACCESS |
ISSN | 2169-3536 |
2020 | |
卷号 | 8页码:50648-50658 |
通讯作者 | Yang, Yu(2120170273@bit.edu.cn) |
摘要 | Robotic-assisted platforms are expected to guarantee the accuracy of surgical operation and accelerate its learning curve. Iris tracking can guide the robotic manipulator during the operation. However, few researches focused on it during surgery. It is a big challenge due to the deformation of the iris and occlusion caused by instruments. A novel real-time iris tracking method based on a regression network are proposed to meet the speed and accuracy requirements of the ophthalmic robotic system. It utilizes the low-level visual features and high-level semantic meanings from different layers to capture the discriminative representation of the iris target. Then the bottleneck layers are added to improve computation efficiency. Furthermore, a multi-loss function is designed by jointly learning Absolute loss and Euclidean loss. Finally, the experimental results under the typical surgical scene demonstrate that iris tracker achieves an accuracy of 89.16 & x0025; and a real-time speed of 134fps with GPU, which is suitable for the ophthalmic robotic system to perform real-time robotic manipulation. |
关键词 | Robots Target tracking Iris recognition Surgery Iris Cataracts Robotic surgery deep learning cataract surgery iris tracking real-time tracking |
DOI | 10.1109/ACCESS.2020.2980005 |
关键词[WOS] | CATARACT ; PREVALENCE |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2017YFB1302704] ; National Natural Science Foundation of China[U1713220] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China |
WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
WOS类目 | Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications |
WOS记录号 | WOS:000524898800002 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 机器人感知与决策 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/38816 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
通讯作者 | Yang, Yu |
作者单位 | 1.Capital Med Univ, Beijing Chaoyang Hosp, Dept Ophthalmol, Beijing 100020, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Beijing Inst Technol, Sch Mechatron Engn, Beijing 100081, Peoples R China 4.Beijing Tongren Hosp, Beijing Tongren Eye Ctr, Beijing 100730, Peoples R China 5.Zhengzhou Univ, Sch Elect Engn, Zhengzhou 450001, Peoples R China |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Qiu, Huaiyu,Li, Zhen,Yang, Yu,et al. Real-Time Iris Tracking Using Deep Regression Networks for Robotic Ophthalmic Surgery[J]. IEEE ACCESS,2020,8:50648-50658. |
APA | Qiu, Huaiyu,Li, Zhen,Yang, Yu,Xin, Chen,&Bian, Gui-Bin.(2020).Real-Time Iris Tracking Using Deep Regression Networks for Robotic Ophthalmic Surgery.IEEE ACCESS,8,50648-50658. |
MLA | Qiu, Huaiyu,et al."Real-Time Iris Tracking Using Deep Regression Networks for Robotic Ophthalmic Surgery".IEEE ACCESS 8(2020):50648-50658. |
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