Real-time tracking of surgical instruments based on spatio-temporal context and deep learning-Reference-Cited by-同舟云学术

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Real-time tracking of surgical instruments based on spatio-temporal context and deep learning

Published:2019-02-14 Issue:sup1 Volume:24 Page:20-29
ISSN:2469-9322
Container-title:Computer Assisted Surgery
language:en
Short-container-title:Computer Assisted Surgery

Author:

Zhao Zijian¹,Chen Zhaorui¹,Voros Sandrine²,Cheng Xiaolin³

Affiliation:

1. School of Control Science and Engineering, Shandong University, Jinan, China;

2. University Grenoble-Alpes, CNRS, INSERM, TIMC-IMAG, Grenoble, France;

3. Lab of Laparoscopic Technique and Engineering, Qilu Hospital of Shandong University, Jinan, China

Funder

Specialized Research Fund for the Doctoral Program of Higher Education of China

Promotive Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province

Publisher

Informa UK Limited

Subject

Family Practice,Computer Science Applications,Surgery

Link

https://www.tandfonline.com/doi/pdf/10.1080/24699322.2018.1560097

Reference24 articles.

1. Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery

2. Austin R, Peter KA, Zhao T. Feature classification for tracking articulated surgical tools. Proceedings of the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention-MICCAI; 2012 Oct 1–5; Nice, France. p. 592–600.

3. Wesierski D, Wojdyga G, Jezierska A. Instrument tracking with rigid part mixtures model. Proceedings of the International Workshop on Computer-Assisted and Robotic Endoscopy; 2015 Oct; Munich. p. 22–34.

4. Object Detection with Discriminatively Trained Part-Based Models

5. Appearance learning for 3D tracking of robotic surgical tools

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