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Theses

Framework for Ultrasonography-based Augmented Reality in Robotic Surgery: Application to Transoral Surgery and Gastrointestinal Surgery

Abstract : The medical context of this thesis is transoral robotic surgery for base of tongue cancer and robot-assisted laparoscopic surgery for low-rectal cancer. One of the main challenges for surgeons to perform these two surgical procedures is to identify the tumor resection margins accurately, because tumors are often concealed in base of tongues or rectal walls and there is lack of efficient intraoperative guidance systems. However, ultrasonography is widely used to image soft-tissue tumors, which motivates our proposition of an augmented reality framework based on intraoperative ultrasonography images for tumor resection guidance. The framework, proposed, with clinical partners, consists to adapt to the surgical workflow of robot-assisted surgery for treating base of tongue cancer and low-rectal cancer. For this purpose, we developed a fast and accurate 3D ultrasound probe calibration method to track the probe and facilitate its intraoperative use. Moreover, we evaluated the performance of the proposed framework augmenting an intraoperative endoscopic camera with ultrasound information, which shows less than 1mm error. Furthermore, we designed experimental protocols using a silicone rectum phantom and an ex-vivo lamb tongue, that simulate the integration of the implemented framework into the current surgical workflow. The experimental results show that, according to the augmented endoscopic views provided by the proposed framework, a surgeon is able to accurately identify the resection margins of the simulated tumors in these phantoms.
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https://tel.archives-ouvertes.fr/tel-02465199
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Submitted on : Monday, February 3, 2020 - 5:09:15 PM
Last modification on : Wednesday, September 14, 2022 - 10:20:04 AM
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  • HAL Id : tel-02465199, version 1

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Jun Shen. Framework for Ultrasonography-based Augmented Reality in Robotic Surgery: Application to Transoral Surgery and Gastrointestinal Surgery. Signal and Image processing. Université Rennes 1, 2019. English. ⟨tel-02465199⟩

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