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Computer Assisted Surgery Volume 24, 2019 - Issue sup1: Advances in Minimally Invasive Surgery and Clinical Measurement. Guest Editors: Chengyu Liu & Lung-kwang Pan

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Research Article

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

Zijian ZhaoSchool of Control Science and Engineering, Shandong University, Jinan, China; Correspondence[email protected]
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Zhaorui ChenSchool of Control Science and Engineering, Shandong University, Jinan, China; View further author information

Sandrine VorosUniversity Grenoble-Alpes, CNRS, INSERM, TIMC-IMAG, Grenoble, France; View further author information

Xiaolin ChengLab of Laparoscopic Technique and Engineering, Qilu Hospital of Shandong University, Jinan, ChinaView further author information

Pages 20-29 | Published online: 14 Feb 2019

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https://doi.org/10.1080/24699322.2018.1560097
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Yaqing Hou, Wenkai Zhang, Qian Liu, Hongwei Ge, Jun Meng, Qiang Zhang & Xiaopeng Wei. (2021) Adaptive kernel selection network with attention constraint for surgical instrument classification. Neural Computing and Applications 34:2, pages 1577-1591.
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Pan Shi, Zijian Zhao, Sanyuan Hu & Faliang Chang. (2020) Real-Time Surgical Tool Detection in Minimally Invasive Surgery Based on Attention-Guided Convolutional Neural Network. IEEE Access 8, pages 228853-228862.
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Real-time tracking of surgical instruments based on spatio-temporal context and deep learning

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

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