基于区域建议网络和残差结构的导丝跟踪

doi:10.16451/j.cnki.issn1003-6059.201901005

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Abstract X-ray image navigation is a breakthrough of improving the accuracy and safety of robotic interventional surgery. A method based on region proposal network, residual structure and canny edge detection is proposed in this paper. It is specifically designed for guidewire segmentation framework. In the image calibration, multi-scale marking strategies are adopted to enable detection networks to learn accurate features. In the image augmentation, a multi-filter fusion strategy is employed to increase the recognizability of the guidewire and improve the tracking accuracy and the system robustness. The experiment is conducted on 22 sets of X-ray video sequences. Experimental results demonstrate the superiority of the proposed algorithm in terms of speed, accuracy and robustness.

Received: 27 September 2018

ZTFLH:

TP 183

Fund:Supported by National Natural Science Foundation of China(No.61533016,U1613210)

Corresponding Authors: HOU Zengguang, Ph.D., professor. His research interests include rehabilitation robot and minimal invasive interventional robot.

About author:: LIU Shiqi, master student. His research interests include minimal invasive interventional robot.SUN Xiaobo, master, professor. His research interests include control system and control engineering.XIE Xiaoliang, Ph.D., associate profe-ssor. His research interests include surgical robot modeling and control, medical image processing.

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	LIU Shiqi
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	XIE Xiaoliang
	HOU Zengguang

Cite this article:

LIU Shiqi,SUN Xiaobo,XIE Xiaoliang等. Guidewire Tracking Based on Regional Proposal Network and Residual Structure[J]. , 2019, 32(1): 36-42.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201901005 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2019/V32/I1/36

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