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Computer Assisted Surgery Volume 22, 2017 - Issue sup1: Innovation in Biomedical Science and Engineering
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Innovation in Biomedical Science and Engineering

Tracking-by-detection of surgical instruments in minimally invasive surgery via the convolutional neural network deep learning-based method

Zijian ZhaoSchool of Control Science and Engineering, Shandong University, Jinan, China; Correspondence[email protected]
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,
Sandrine VorosCNRS, INSERM, TIMC-IMAG, University Grenoble-Alpes, Grenoble, France; View further author information
,
Ying WengSchool of Computer Science, Bangor University, Bangor, UK; View further author information
,
Faliang ChangSchool of Control Science and Engineering, Shandong University, Jinan, China; View further author information
&
Ruijian LiDepartment of cardiology, Qilu Hospital of Shandong University, Jinan, ChinaView further author information
Pages 26-35 | Published online: 22 Sep 2017

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