Knowledge Commons of Institute of Automation,CAS
BARNet: Bilinear Attention Network with Adaptive Receptive Fields for Surgical Instrument Segmentation | |
Zhen-Liang Ni1,2![]() ![]() ![]() ![]() ![]() ![]() ![]() | |
2021-01 | |
会议名称 | the Twenty-Ninth International Joint Conference on Artificial Intelligence |
会议日期 | 2021-1 |
会议地点 | Yokohama |
摘要 | Surgical instrument segmentation is crucial for computer-assisted surgery. Different from common object segmentation, it is more challenging due to the large illumination variation and scale variation in the surgical scenes. In this paper, we propose a bilinear attention network with adaptive receptive fields to address these two issues. To deal with the illumination variation, the bilinear attention module models global contexts and semantic dependencies between pixels by capturing second-order statistics. With them, semantic features in challenging areas can be inferred from their neighbors, and the distinction of various semantics can be boosted. To adapt to the scale variation, our adaptive receptive field module aggregates multi-scale features and selects receptive fields adaptively. Specifically, it models the semantic relationships between channels to choose feature maps with appropriate scales, changing the receptive field of subsequent convolutions. The proposed network achieves the best performance 97.47% mean IoU on Cata7. It also takes the first place on EndoVis 2017, exceeding the second place by 10.10% mean IoU. |
关键词 | Biomedical Image Understanding, Robotics and Vision |
DOI | https://doi.org/10.24963/ijcai.2020/116 |
收录类别 | EI |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48702 |
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.Institute of Automation, Chinese Academy of Sciences 2.The School of Artificial Intelligence, University of 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. BARNet: Bilinear Attention Network with Adaptive Receptive Fields for Surgical Instrument Segmentation[C],2021. |
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