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Radiation-Free 3D Navigation and Vascular Reconstruction for Aortic Stent Graft Deployment

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9805))

Abstract

We propose a radiation-free three dimensional (3D) navigation and vasculature reconstruction method to reduce aortic stent graft deployment time and repeated exposures to high doses of X-ray radiation. 2D intraoperative US images are fused with 3D preoperative magnetic resonance (MR) image to provide intuitive 3D navigation for deployment of the stent-graft in the proposed system. On the other hand, calibrated 2D US images track catheter’s tip and construct intraoperative 3D aortic model by combining segmented intravascular ultrasound (IVUS) images. The constructed 3D aortic models can quantitatively assess morphological characteristics of aortic to assist deployment of stent graft. This system was validated by using in vitro cardiac and aorta phantom. The mean target registration error of 2D US-3D MR registration was 2.70 mm and the average tracking error of position of IVUS catheter’s tip was 1.12 mm. Accurate contours detection results in IVUS images were acquired. Meanwhile, Hausdorff distances are 0.78 mm and 0.59 mm for outer and inner contours, respectively; Dice coefficients are 90.21 % and 89.96 %. Experiment results demonstrate that our radiation-free navigation and 3D vasculature reconstruction method is promising for deployment of stent graft in vivo studies.

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Acknowledgments

This study was supported in part by National Natural Science Foundation of China (Grant No. 81427803, 61361160417, 81271735), Grant-in-Aid of Project 985, and Beijing Municipal Science & Technology Commission (Z151100003915079). The Authors would like to thank Mr. Yigang Qiu from Department of Cardiology, Navy PLA General Hospital for assistance in acquiring IVUS data for this study.

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Correspondence to Hongen Liao .

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Chen, F., Liu, J., Liao, H. (2016). Radiation-Free 3D Navigation and Vascular Reconstruction for Aortic Stent Graft Deployment. In: Zheng, G., Liao, H., Jannin, P., Cattin, P., Lee, SL. (eds) Medical Imaging and Augmented Reality. MIAR 2016. Lecture Notes in Computer Science(), vol 9805. Springer, Cham. https://doi.org/10.1007/978-3-319-43775-0_6

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  • DOI: https://doi.org/10.1007/978-3-319-43775-0_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43774-3

  • Online ISBN: 978-3-319-43775-0

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