Multi-Frame Feature Aggregation for Real-Time Instrument Segmentation in Endoscopic Video
文献类型：期刊论文
| 作者 | Lin, Shan1; Qin, Fangbo2 ; Peng, Haonan1; Bly, Randall A.3; Moe, Kris S.3; Hannaford, Blake1
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| 刊名 | IEEE ROBOTICS AND AUTOMATION LETTERS
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| 出版日期 | 2021-10-01 |
| 卷号 | 6期号:4页码:6773-6780 |
| 关键词 | Computer vision for medical robotics deep learning for visual perception object detection segmentation and categorization |
| ISSN号 | 2377-3766 |
| DOI | 10.1109/LRA.2021.3096156 |
| 通讯作者 | Lin, Shan(shanlin0331@gmail.com) |
| 英文摘要 | Deep learning-based methods have achieved promising results on surgical instrument segmentation. However, the high computation cost may limit the application of deep models to time-sensitive tasks such as online surgical video analysis for robotic-assisted surgery. Moreover, current methods may still suffer from challenging conditions in surgical images such as various lighting conditions and the presence of blood. We propose a novel Multi-frame Feature Aggregation (MFFA) module to aggregate video frame features temporally and spatially in a recurrent mode. By distributing the computation load of deep feature extraction over sequential frames, we can use a lightweight encoder to reduce the computation costs at each time step. Moreover, public surgical videos usually are not labeled frame by frame, so we develop a method that can randomly synthesize a surgical frame sequence from a single labeled frame to assist network training. We demonstrate that our approach achieves superior performance to corresponding deeper segmentation models on two public surgery datasets. |
| 资助项目 | National Science Foundation[IIS-2036255] |
| WOS研究方向 | Robotics |
| 语种 | 英语 |
| WOS记录号 | WOS:000678343900013 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/45640]  |
| 专题 | 精密感知与控制研究中心_精密感知与控制 |
| 通讯作者 | Lin, Shan |
| 作者单位 | 1.Univ Washington, Dept Elect & Comp Engn, Seattle, WA 98195 USA 2.Chinese Acad Sci, Res Ctr Precis Sensing & Control, Inst Automat, Beijing 100190, Peoples R China 3.UW, Dept Otolaryngol Head & Neck Surg, Seattle, WA 98105 USA |
| 推荐引用方式 GB/T 7714 | Lin, Shan,Qin, Fangbo,Peng, Haonan,et al. Multi-Frame Feature Aggregation for Real-Time Instrument Segmentation in Endoscopic Video[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2021,6(4):6773-6780. |
| APA | Lin, Shan,Qin, Fangbo,Peng, Haonan,Bly, Randall A.,Moe, Kris S.,&Hannaford, Blake.(2021).Multi-Frame Feature Aggregation for Real-Time Instrument Segmentation in Endoscopic Video.IEEE ROBOTICS AND AUTOMATION LETTERS,6(4),6773-6780. |
| MLA | Lin, Shan,et al."Multi-Frame Feature Aggregation for Real-Time Instrument Segmentation in Endoscopic Video".IEEE ROBOTICS AND AUTOMATION LETTERS 6.4(2021):6773-6780. |
入库方式： OAI收割
来源：自动化研究所
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