Knowledge Commons of Institute of Automation,CAS
Pyramid Attention Aggregation Network for Semantic Segmentation of Surgical Instruments | |
Zhen-Liang Ni1,2; Gui-Bin Bian1,2; Guan-An Wang1,2; Xiao-Hu Zhou2; Zeng-Guang Hou1,2,3; Hua-Bin Chen1,2; Xiao-Liang Xie2 | |
2020-04 | |
会议名称 | the AAAI Conference on Artificial Intelligence |
会议日期 | 2020.2.7-2020.2.12 |
会议地点 | NewYork USA |
摘要 | Semantic segmentation of surgical instruments plays a critical role in computer-assisted surgery. However, specular reflection and scale variation of instruments are likely to occur in the surgical environment, undesirably altering visual features of instruments, such as color and shape. These issues make semantic segmentation of surgical instruments more challenging. In this paper, a novel network, Pyramid Attention Aggregation Network, is proposed to aggregate multi-scale attentive features for surgical instruments. It contains two critical modules: Double Attention Module and Pyramid Upsampling Module. Specifically, the Double Attention Module includes two attention blocks (i.e., position attention block and channel attention block), which model semantic dependencies between positions and channels by capturing joint semantic information and global contexts, respectively. The attentive features generated by the Double Attention Module can distinguish target regions, contributing to solving the specular reflection issue. Moreover, the Pyramid Upsampling Module extracts local details and global contexts by aggregating multi-scale attentive features. It learns the shape and size features of surgical instruments in different receptive fields and thus addresses the scale variation issue. The proposed network achieves state-of-the-art performance on various datasets. It achieves a new record of 97.10% mean IOU on Cata7. Besides, it comes first in the MICCAI EndoVis Challenge 2017 with 9.90% increase on mean IOU. |
关键词 | surgical instrument segmentation |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48701 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
通讯作者 | Gui-Bin Bian |
作者单位 | 1.University of Chinese Academy of Sciences 2.the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences 3.CAS Center for Excellence in Brain Science and Intelligence Technology |
第一作者单位 | 中国科学院自动化研究所 |
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 | Zhen-Liang Ni,Gui-Bin Bian,Guan-An Wang,et al. Pyramid Attention Aggregation Network for Semantic Segmentation of Surgical Instruments[C],2020. |
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