High-precision surgical navigation using speckle structured light-based thoracoabdominal puncture robot

Fuente: arXiv
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Autores principales: Guo, Zezhao, Guo, Yanzhong, Zhao, Zhanfang
Formato: Preprint
Publicado: 2024
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author Guo, Zezhao
Guo, Yanzhong
Zhao, Zhanfang
author_facet Guo, Zezhao
Guo, Yanzhong
Zhao, Zhanfang
contents Abstract Background During percutaneous puncture robotic surgical navigation, the needle insertion point is positioned on the patient's chest and abdomen body surface. By locating any point on the soft skin tissue, it is difficult to apply the traditional reflective ball tracking method. The patient's chest and abdomen body surface has fluctuations in breathing and appears irregular. The chest and abdomen are regular and smooth, lacking obvious features, and it is challenging to locate the needle insertion point on the body surface. Methods This paper designs and experiments a method that is different from previous reflective ball optical markers or magnetic positioning surgical navigation and tracking methods. It is based on a speckle structured light camera to identify the patient's body surface and fit it into a hollow ring with a diameter of 24mm. Results Experimental results show that this method of the system can be small, flexible, and high-precision positioning of any body surface point at multiple angles, achieving a positioning accuracy of 0.033-0.563mm and an image of 7-30 frames/s. Conclusions The positioning recognition ring material used in this method can be well imaged under CT, so the optical positioning of the body surface and the in vivo imaging positioning under CT can be combined to form a unified patient's internal and external positioning world coordinates to achieve internal and external registration. Positioning integration. The system senses motion with six degrees of freedom, up and down, front and back, left and right, and all rotations, with sub-millimeter accuracy, and has broad application prospects in future puncture surgeries.
format Preprint
id arxiv_https___arxiv_org_abs_2406_06478
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle High-precision surgical navigation using speckle structured light-based thoracoabdominal puncture robot
Guo, Zezhao
Guo, Yanzhong
Zhao, Zhanfang
Robotics
Artificial Intelligence
Abstract Background During percutaneous puncture robotic surgical navigation, the needle insertion point is positioned on the patient's chest and abdomen body surface. By locating any point on the soft skin tissue, it is difficult to apply the traditional reflective ball tracking method. The patient's chest and abdomen body surface has fluctuations in breathing and appears irregular. The chest and abdomen are regular and smooth, lacking obvious features, and it is challenging to locate the needle insertion point on the body surface. Methods This paper designs and experiments a method that is different from previous reflective ball optical markers or magnetic positioning surgical navigation and tracking methods. It is based on a speckle structured light camera to identify the patient's body surface and fit it into a hollow ring with a diameter of 24mm. Results Experimental results show that this method of the system can be small, flexible, and high-precision positioning of any body surface point at multiple angles, achieving a positioning accuracy of 0.033-0.563mm and an image of 7-30 frames/s. Conclusions The positioning recognition ring material used in this method can be well imaged under CT, so the optical positioning of the body surface and the in vivo imaging positioning under CT can be combined to form a unified patient's internal and external positioning world coordinates to achieve internal and external registration. Positioning integration. The system senses motion with six degrees of freedom, up and down, front and back, left and right, and all rotations, with sub-millimeter accuracy, and has broad application prospects in future puncture surgeries.
title High-precision surgical navigation using speckle structured light-based thoracoabdominal puncture robot
topic Robotics
Artificial Intelligence
url https://arxiv.org/abs/2406.06478