CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Guidewire Tip Segmentation with Atrous Convolution
Wu YD(吴玉东)1,3; Xie XL(谢晓亮)1; Bian GB(边桂斌)1; Hou ZG(侯增广)1,2,3; Liu SQ(刘市祺)1
Conference NameInternational Engineering in Medicine and Biology Conference
Conference Date2018
Conference Place美国夏威夷

Segmentation of the guidewire tip in 2D X-ray image of percutaneous coronary intervention is a prerequisite for clinic applications, but also challenging for the tiny structure, large deformations and few texture features of the tip. In this paper, tip segmentation based on encoder-decoder convolutional neural networks with different receptive fields is explored, and a median tip distance error of 0.491 pixels, F1 score of 0.982 is obtained by a modified structure with atrous convolution.

Funding ProjectNational Natural Science Foundation of China[61533016] ; National High-Tech Research and Development Plan[2015AA042306]
Document Type会议论文
Affiliation1.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation,Chinese Academy of Sciences
2.CAS Center for Excellence in Brain Science and Intelligence Technology
3.University of Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wu YD,Xie XL,Bian GB,et al. Guidewire Tip Segmentation with Atrous Convolution[C],2018.
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