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Three-Dimensional Path Planning and Guidance of Leg Vascular Based on Improved Ant Colony Algorithm in Augmented Reality

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Abstract

Preoperative path planning plays a critical role in vascular access surgery. Vascular access surgery has superior difficulties and requires long training periods as well as precise operation. Yet doctors are on different leves, thus bulky size of blood vessels is usually chosen to undergo surgery and other possible optimal path is not considered. Moreover, patients and surgeons will suffer from X-ray radiation during the surgical procedure. The study proposed an improved ant colony algorithm to plan a vascular optimal three-dimensional path with overall consideration of factors such as catheter diameter, vascular length, diameter as well as the curvature and torsion. To protect the doctor and patient from exposing to X-ray long-term, the paper adopted augmented reality technology to register the reconstructed vascular model and physical model meanwhile, locate catheter by the electromagnetic tracking system and used Head Mounted Display to show the planning path in real time and monitor catheter push procedure. The experiment manifests reasonableness of preoperative path planning and proves the reliability of the algorithm. The augmented reality experiment real time and accurately displays the vascular phantom model, planning path and the catheter trajectory and proves the feasibility of this method. The paper presented a useful and feasible surgical scheme which was based on the improved ant colony algorithm to plan vascular three-dimensional path in augmented reality. The study possessed practical guiding significance in preoperative path planning, intraoperative catheter guiding and surgical training, which provided a theoretical method of path planning for vascular access surgery. It was a safe and reliable path planning approach and possessed practical reference value.

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Acknowledgments

This work was supported by Shanghai International Cooperation Fund Project of Shanghai Science and Technology Committee (No.12510708400).

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Authors and Affiliations

  1. School of Computer Engineering and Science, Shanghai University, No.99 Shangda Road, Baoshan District, Shanghai City, China

    Ming-ke Gao, Yi-min Chen, Quan Liu, Chen Huang, Ze-yu Li & Dian-hua Zhang

  2. School of Mathematics and Computing Science, Hunan University of Science and Technology, Taoyuan Road, Xiangtan City, Hunan Province, China

    Ming-ke Gao

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  1. Ming-ke Gao
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  2. Yi-min Chen
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  4. Chen Huang
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Correspondence to Yi-min Chen.

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This article is part of the Topical Collection on Education & Training

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Gao, Mk., Chen, Ym., Liu, Q. et al. Three-Dimensional Path Planning and Guidance of Leg Vascular Based on Improved Ant Colony Algorithm in Augmented Reality. J Med Syst 39, 133 (2015). https://doi.org/10.1007/s10916-015-0315-2

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