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An implicit skeleton-based method for the geometry reconstruction of vasculatures

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Abstract

Due to the high complexity of vascular system network, the geometry reconstruction of vasculatures from raw medical datasets remains a very challenging task. In this paper, we present a novel skeleton-based method for the geometry reconstruction of vascular structures from standard 3D medical datasets. With the proposed techniques, the geometry of vascular structures with high level of smoothness and accuracy can be reconstructed from the raw medical datasets. The experimental results and comparison with other techniques demonstrate that our method can achieve faithful and smooth vascular structures. In addition, quantitative validation has been conducted to evaluate the accuracy and smoothness of the reconstructed vessel geometry based on the proposed method.

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References

  1. Schumann, C., Oeltze, S., Bade, R., Preim, B., Peitgen, H.: Model-free surface visualization of vascular trees. In: IEEE/Eurographics Symposium on Visualization, pp. 283–290 (2007)

  2. Joshi, A., Qian, X., Dione, D., Bulsara, K., Breuer, C., Sinusas, A., Papademetris, X.: Effective visualization of complex vascular structures using a non-parametric vessel detection method. IEEE Trans. Vis. Comput. Graph. 14(6), 1603–1610 (2008)

    Article  Google Scholar 

  3. Bartz, D., Skalej, M., Welte, D., Straßer, W., Duffner, F.: A virtual endoscopy system for the planning of endoscopic interventions in the ventricle system of the human brain. In: BiOS’99 International Biomedical Optics Symposium, pp. 1–10 (1999)

  4. Luboz, V., Blazewski, R., Gould, D., Bello, F.: Real-time guidewire simulation in complex vascular models. Vis. Comput. 25(9), 827–834 (2009)

    Article  Google Scholar 

  5. Luboz, V., Kyaw-Tun, J., Sen, S., Kneebone, R., Dickinson, R., Kitney, R., Bello, F.: Real-time stent and balloon simulation for stenosis treatment. Vis. Comput. 30(3), 341–349 (2014)

    Article  Google Scholar 

  6. Tang, W., Lagadec, P., Gould, D., Wan, T., Zhai, J., How, T.: A realistic elastic rod model for real-time simulation of minimally invasive vascular interventions. Vis. Comput. 26(9), 1157–1165 (2010)

    Article  Google Scholar 

  7. Gobbetti, E., Pili, P., Zorcolo, A., Tuveri, M.: Interactive virtual angioscopy. In: Proceedings of IEEE Visualization 1998 (VIS ’98), pp. 435–438 (1998)

  8. Oeltze, S., Preim, B.: Visualization of vascular structures with convolution surfaces: method, validation and evaluation. IEEE Trans. Med. Imaging 25(3), 540–549 (2005)

    Article  Google Scholar 

  9. Hahn, H., Preim, B., Selle, D., Peitgen, H.: Visualization and interaction techniques for the exploration of vascular structures. In: Proceedings of IEEE Visualization 2001 (VIS’01), pp. 395–402 (2001)

  10. Pommert, A., Bomans, M., Höhne, K.H.: Volume visualization in magnetic resonance angiography. IEEE Comput. Graph. Appl. 12(5), 12–13 (1992)

    Google Scholar 

  11. Gerig, G., Koller, T., Székely, G., Brechbühler, C., Kübler, O.: Symbolic description of 3d structures applied to cerebral vessel tree obtained from mr angiography volume data. In: Information processing in medical imaging, pp. 94–111 (1993)

  12. Boskamp, T., Hahn, H., Hindennach, M., Zidowitz, S., Oeltze, S., Preim, B., Peitgen, H.: Geometrical and structural analysis of vessel systems in 3d medical image datasets. Med. Imaging Syst. Technol. 5, 1–60 (2005)

    Article  Google Scholar 

  13. Schumann, C., Neugebauer, M., Bade, R., Peitgen, H., Preim, B.: Implicit vessel surface reconstruction for visualization and cfd simulation. Int. J. Comput. Assist. Radiol. Surg. 2(5), 275–286 (2008)

    Article  Google Scholar 

  14. Pekkan, K., Whited, B., Kanter, K.: Patient-specific surgical planning and hemodynamic computational fluid dynamics optimization through free-form haptic anatomy editing tool (surgem). Med. Biol. Eng. Comput. 46(11), 1139–1152 (2008)

    Article  Google Scholar 

  15. Preim, B., Oeltze, S.: 3d visualization of vasculature: an overview. Visualization in Medicine and Life Science, pp. 39–59 (2007)

  16. Hong, Q., Li, Q., Tian, J.: Local hybrid level-set method for mra image segmentation. In: 10th IEEE International Conference on Computer and Information Technology, pp. 1397–1402 (2010)

  17. Hong, Q.: A skeleton-based technique for modelling implicit surfaces. In: 6th International Congress on Image and Signal Processing, pp. 686–691 (2013)

  18. Hong, Q., Chen, L., Wang, B., Wu, Q.: The extraction of vascular axis based on signed distance function. In: Fifth International Conference on Graphic and Image Processing, p. 90690D (2014)

  19. Masutani, Y., Masamune, K., Dohi, T.: Region-growing based feature extraction algorithm for tree-like objects. In: Proceedings of Visualization in Biomedical Computing, pp. 161–171 (1996)

  20. Höhne, K., Pesser, B., Pommert, A.: A realistic model of the inner organs from the visible human data. In: Proceedings of Medical Image Computing and Computer-Assisted Intervention, pp. 776–785. Springer (2000)

  21. Bornik, A., Reitinger, B., Beichel, R.: Reconstruction and representation of tubular structures using simplex meshes. In: Proceedings of Winter School of Computer Graphics (WSCG), pp. 61–65 (2005)

  22. Felkel, P., Fuhrmann, A., Kanitsar, A., Wegenkittl, R.: Surface reconstruction of the branching vessels for augmented reality aided surger. BIOSIGNAL 16, 252–254 (2002)

    Google Scholar 

  23. Felkel, P., Wegenkittl, R., Bühler, K.: Surface models of tube trees. In: Proceedings of Computer Graphics International, pp. 70–77 (2004)

  24. Wu, X., Luboz, V., Krissian, K., Cotin, S., Dawson, S.: Segmentation and reconstruction of vascular structures for 3d real-time simulation. Med. Image Anal. 15(1), 22–34 (2011)

    Article  Google Scholar 

  25. Bloomenthal, J.: Skeletal design of natural forms. Ph.D. thesis, University of Calgary (1995)

  26. Bloomenthal, J. (ed.): Introduction to Implicit Surfaces. Morgan Kaufmann Publishers Inc, San Francisco, California (1997)

    MATH  Google Scholar 

  27. Jin, X., Tai, C.L., Zhang, H.: Implicit modeling from polygon soup using convolution. Vis. Comput. 25(3), 279–288 (2009)

    Article  Google Scholar 

  28. Hong, Q., Li, Q., Tian, J.: Implicit reconstruction of vasculatures using bivariate piecewise algebraic splines. IEEE Trans. Med. Imaging 31(3), 543–553 (2012)

    Article  Google Scholar 

  29. Kretschmer, J., Godenschwager, C., Preim, B., Stamminger, M.: Interactive patient-specific vascular modeling with sweep surfaces. IEEE Trans. Vis. Comput. Graph. 19(12), 2828–2837 (2013)

    Article  Google Scholar 

  30. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. Int. J. Comput. Vis. 1, 321–331 (1988)

    Article  MATH  Google Scholar 

  31. Li, C., Kao, C., Gore, J., Ding, Z.: Implicit active contours driven by local binary tting energy. In: 2007 IEEE Conf. Computer Vision and Pattern Recognition, pp. 1–7 (2007)

  32. Zhang, Y., Matuszewski, B., Shark, L., Moore, C.: Medical image segmentation using new hybrid level-set method. In: Proceedings of Fifth International Conference BioMedical Visualization: Information Visualization in Medical and Biomedical Informatics, pp. 71–76 (2008)

  33. Abeysinghe, S., Ju, T.: Interactive skeletonization of intensity volumes. Vis. Comput. 25(5–7), 627–635 (2009)

    Article  Google Scholar 

  34. Osher, S., Fedkiw, R.: Level Set Methods and Dynamic Implicit Surfaces. Springer, New York (2002)

    MATH  Google Scholar 

  35. Sethian, J.A.: Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science. Cambridge University Press, Cambridge (1999)

  36. Li, Q., Tian, J.: Partial shape-preserving splines. Comput. Aided Des. 43, 394–409 (2011)

    Article  Google Scholar 

  37. Li, Q.: Smooth piecewise polynomial blending operations for implicit shapes. Comput. Graph. Forum. 26(2), 157–171 (2007)

    Article  Google Scholar 

  38. Orkisz, M., Bresson, C., Magnin, I., Champin, O., Douek, P.: Improved vessel visualization in mr angiography by nonlinear anisotropic ltering. Magnet. Reson. Med. 37(6), 914–919 (1997)

    Article  Google Scholar 

  39. Dong, C., Wang, G.: Curvatures estimation on triangular mesh. J. Zhejiang Univ. SCI. 6(1), 128–136 (2005)

    Article  MATH  Google Scholar 

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Acknowledgments

The authors would like to thank all the anonymous reviewers for their constructive comments. This work is supported by the National Natural Science Foundation of China (Grant No. 61502402),the Natural Science Foundation of Fujian Province of China (No. 2015J05129), the Scientific Research Foundation for the Returned Overseas Chinese Scholars, China Postdoctoral Science Foundation (Project No. 2015M57191), and MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Grant No. 11YJC870027). The author would also acknowledge the supports of the Special and Major Subject Project of the Industrial Science and Technology in Fujian Province 2013 (the Special Subject Project No. is 2013HZ0004-1), and the 2014 Key Project of Anhui Science and Technology BureauCDevelopment and Application of Energy Efficiency Monitoring, Evaluating and Optimizing Control System for Flash Copper Smelting Enterprises (Number: 1301021018).

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Authors and Affiliations

  1. Software School, Xiamen University, Xiamen, China

    Qingqi Hong, Beizhan Wang, Junfeng Yao, Qingqiang Wu & Yingying She

  2. Management School, Xiamen University, Xiamen, China

    Yan Li

  3. Department of Computer Science, University of Hull, Hull, HU6 7RX, UK

    Qingde Li

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  1. Qingqi Hong
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  2. Yan Li
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  3. Qingde Li
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  4. Beizhan Wang
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Correspondence to Yan Li.

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Hong, Q., Li, Y., Li, Q. et al. An implicit skeleton-based method for the geometry reconstruction of vasculatures. Vis Comput 32, 1251–1262 (2016). https://doi.org/10.1007/s00371-015-1160-5

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