Skip to main content
SpringerLink
Log in

Medical Data Point Clouds Reconstruction Algorithm Based on Tensor Product B-Spline Approximation in Virtual Surgery

  • Original Article
  • Published:
Journal of Medical and Biological Engineering Aims and scope Submit manuscript

Abstract

A complete 3D visualization method for virtual liver lesion model was proposed by taking patients’ abdomen CT slices as data source. Firstly, Gradient Vector Flow-Snake algorithm that combines with region force was adopted to fast and accurately extract the contour points in patients’ CT slices. Then 3D cloud data of these contour points was simplified uniformly, and a distance-field-based method of distribution field fitting for B-spline surface was presented to fast establish the lesion model roughly. Then, an interactive node fine tuning method Interactive Marching Nodes was proposed, so the model can be optimized according to requirements of users. Finally, realistic lesion model was generated through texture mapping. Experiments suggest that this approach is suitable for various kinds of lesions with the whole process taking only a few minutes, and the generated model has high precision, which is of some significance in the study of virtual surgeries.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Bénard, P., Lu, J., Cole, F., Finkelstei, A., & Thollot, J. (2012). Active strokes: Coherent line stylization for animated 3D models. In Proceedings of the symposium on non-photorealistic animation and rendering (pp. 37–46).

  2. Zhang, X., Cai, K., Zhang, F., & Li, R. (2013). Contour segmentation based on GVF snake model and contourlet transform. In: Proceedings of the 9th international conference on intelligent computing theories and technology (pp. 503–508).

  3. Seo, J., Cho, Y., Kim, D., Kim, & D.-S. (2007). An efficient algorithm for three-dimensional β-complex and β-shape via a quasi-triangulation. In Proceedings of the 2007 ACM symposium on solid and physical modeling. ACM (pp. 323–328).

  4. Cazals, F., Kanhere, H., & Loriot, S. (2011). Computing the volume of a union of balls: A certified algorithm. ACM Transactions on Mathematical Software, 38(1), 734–747.

    Article  MathSciNet  Google Scholar 

  5. Vaněček, P. (2010). Delaunay space division for RBF image reconstruction. In Proceedings of the 26th Spring conference on computer graphics. ACM (pp. 109–116).

  6. Wang, J., Yang, Z., Jin, L., Deng, J., & Chen, F. (2010). Adaptive surface reconstruction based on implicit PHT-splines. In Proceedings of the 14th ACM symposium on solid and physical modeling. ACM (pp. 101–110).

  7. Saunders, B. V., Antonishek, B., Wang, Q., & Miller, B. R. (2015). Dynamic 3D visualizations of complex function surfaces using X3DOM and WebGL. In Proceedings of the 20th international conference on 3D web technology. ACM (pp. 219–225).

  8. Jiexiong, W., Guodong, C., & Yi, C. (2015). Improved B-snake segmentation method for liver CT images. Computer Engineering and Applications, 51(9), 152–157.

    Google Scholar 

  9. Ng, P., & Pun, C.-M. (2012). Skin segmentation based on human face illumination feature. IEEE Computer Society, 3, 373–377.

    Google Scholar 

  10. Xu, T., Mandal, M., Long, R., Cheng, I., & Basu, A. (2012). An edge-region force guided active shape approach for automatic lung field detection in chest radiographs. Computerized Medical Imaging and Graphics, 36(6), 452–463.

    Article  Google Scholar 

  11. Alexa, M., & Adamson, A. (2009). Interpolatory point set surfaces-convexity and hermite data. ACM Transactions on Graphics, 28(2), 307–308.

    Article  Google Scholar 

  12. Ackermann, M. R., Märtens, M., Raupach, C., Swierkot, K., Lammersen, C., & Sohler, C. (2012). StreamKM++: A clustering algorithm for data streams. Journal of Experimental Algorithmics, 17, 254–257.

    Article  MathSciNet  MATH  Google Scholar 

  13. Gálvez, A., & Iglesias, A. (2012). Particle Swarm optimization for non-uniform rational B-spline surface reconstruction from clouds of 3D data points. Information Sciences, 192, 174–192.

    Article  Google Scholar 

  14. Patane, G., Li, X. S., & Gu, D. X. (2013). Surface- and volume-based techniques for shape modeling and analysis. SIGGRAPH Asia Courses. ACM (pp. 65–67).

  15. Praun, E., Finkelstein, A., & Hoppe, H. (2000). Lapped textures. In Proceedings of the 27th annual conference on computer graphics and interactive techniques. ACM (pp. 465–470).

  16. Chen, K., Johan, H., & Mueller-Wittig, W. (2013). Simple and efficient example-based texture synthesis using tiling and deformation. In: Proceedings of the ACM SIGGRAPH symposium on interactive 3D graphics and games. ACM (pp. 145–152).

  17. Yoo, D. J., & Kwon, H. H. (2009). Shape reconstruction, shape manipulation, and direct generation of input data from point clouds for rapid prototyping. International Journal of Precision Engineering, 10(1), 103–113.

    Article  Google Scholar 

  18. Nagai, Y., Ohtake, Y., & Suzuki, H. (2015). Tomographic surface reconstruction from point cloud. Computers and Graphics., 46, 55–63.

    Article  Google Scholar 

  19. Liu, W., Cheung, Y. Sabouri, Po., Arai, T. J., Sawant, A., & Ruan, D. (2015). A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system. Medical Physics, 42, 238–240.

    Google Scholar 

Download references

Acknowledgements

We would like to thank our team in the institution of digital image processing in Fuzhou University for help. Our research was supported by the Natural Science Foundation of China (61471124), the Provincial Science Foundation of Fujian (2013J05090) and the Provincial Science and Technology Major Project of Fujian (2011H0027).

Author information

Authors and Affiliations

  1. Department of Physics and Information Engineering, Fuzhou University, Fuzhou, 350108, China

    Guo-Dong Chen & Fei-Fei Wang

Authors
  1. Guo-Dong Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fei-Fei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fei-Fei Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, GD., Wang, FF. Medical Data Point Clouds Reconstruction Algorithm Based on Tensor Product B-Spline Approximation in Virtual Surgery. J. Med. Biol. Eng. 37, 162–170 (2017). https://doi.org/10.1007/s40846-016-0211-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40846-016-0211-3

Keywords

Search

Navigation