Advertisement

3D Shape Analysis for Liver-Gallbladder Anatomical Structure Retrieval

  • Weimin Huang
  • Wei Xiong
  • Jiayin Zhou
  • Jing Zhang
  • Tao Yang
  • Jiang Liu
  • Yi Su
  • Calvin Lim
  • Chee Kong Chui
  • Stephen Chang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7601)

Abstract

Anatomical structure is important for medical education and disease diagnosis. In the application of surgical simulation, different anatomical structures can be retrieved to create variety of surgical scenarios for training, while similar structures can also be retrieved to assist disease diagnosis. This paper presents an approach to liver-gallbladder anatomical structure retrieval with 3D shape comparison, where the direct shape comparison based on dense shape registration is applied to liver shape due to its shape complexity, and feature based comparison is applied to gallbladder shape with a semantic shape decomposition using the saliency area based on multi-scale curvatures and concavity. After the registration of liver models, the geometric structure of the gallbladder and liver can be combined for joint comparison. With the 3D models constructed from a set of liver-gallbladder CT data, experiments are conducted for joint liver-gallbladder retrieval. Encouraging result shows that it can reveal important topology based on similarity and variance of 3D shapes and has a similar performance compared to that of manual retrieval by human operators.

Keywords

Anatomical structure shape analysis shape comparison surgical simulation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Meilstrup, J.W., Hopper, K.D., Thieme, A.: Imaging of Gallbladder Variants. Am. J. Roentgenol. 157(6), 1205–1208 (1991)Google Scholar
  2. 2.
    Bodzioch, S.: Automated Detecting Symptoms of Selected Gallbladder Illness Based on A Static Ultrasound Images Analysis. Bio-Alg. and Med-Sys. 2, 35–44 (2006)Google Scholar
  3. 3.
    Kaiser, E.: Congenital and Acquired Changes in Gallbladder Form. Am. J. Dig. Dis. 6(7), 938–953 (1961)CrossRefGoogle Scholar
  4. 4.
    Prasad, M.N., Brown, M.S., Ni, C., Margolis, D.J., Douek, M., Raman, S., Lu, D., Goldin, J.: Three-Dimensional Mapping of Gallbladder Wall Thickness on Computed Tomography Using Laplace’s Equation. Acad. Radiol. 15, 1075–1081 (2008)CrossRefGoogle Scholar
  5. 5.
    Xiong, W., Ong, S.H., Tian, Q., Xu, G., Zhou, J., Liu, J., Venkatash, S.K.: Construction of a Linear Unbiased Diffeomorphic Probabilistic Liver Atlas from CT Images. In: IEEE International Conference on Image Processing, pp. 1773–1776. IEEE Press, New York (2009)Google Scholar
  6. 6.
    Okada, T., Shimada, R., Sato, Y., Hori, M., Yokota, K., Nakamoto, M., Chen, Y.-W., Nakamura, H., Tamura, S.: Automated Segmentation of the Liver from 3D CT Images Using Probabilistic Atlas and Multi-level Statistical Shape Model. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part I. LNCS, vol. 4791, pp. 86–93. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  7. 7.
    Chi, Y., Cashman, P., Bello, F., Kitney, R.I.: An Automatic Liver Segmentation Initialization Information Retrieval Strategy for a Content-Based Image Retrieval System Followed by a New Liver Volume Segmentation Method for CT and MRI Image Datasets. In: MICCAI 2007 Workshop on Content-Based Image Retrieval for Biomedical Image Archives (2007)Google Scholar
  8. 8.
    Zhang, J., Huang, W., Zhou, J., Yang, T., Liu, J., Su, Y., Chui, C.K., Chang, S.: Gallbladder Modeling and Simulation in Laparoscopic Cholecystectom. In: IEEE International Conference on Industrial Electronics and Applications, pp. 128–131. IEEE Press, New York (2011)Google Scholar
  9. 9.
    Huang, W., Zhou, J., Liu, J., Zhang, J., Yang, T., Su, Y., Law, G.H., Chui, C.K., Chang, S.: 3D Shape Decomposition and Comparison for Gallbladder Modeling. In: Proc. of SPIE Medical Imaging, vol. 7964, p. 79642K (2011)Google Scholar
  10. 10.
    Tangelder, J.W.H., Veltkamp, R.C.: A Survey of Content Based 3D Shape Retrieval Methods. Multimed. Tools Appl. 39, 441–471 (2008)CrossRefGoogle Scholar
  11. 11.
    Yamauchi, H., Gumhold, S., Zayer, R., Seidel, H.-P.: Mesh Segmentation Driven by Gaussian Curvature. Visual Comput. 2, 659–668 (2005)CrossRefGoogle Scholar
  12. 12.
    Au, O.K.-C., Tai, C.-L., Chu, H.-K., Cohen-Or, D., Lee, T.-Y.: Skeleton Extraction by Mesh Contraction. J. ACM Trans. on Graphics 27(3), no. 44 (2008)Google Scholar
  13. 13.
    Myronenko, A., Song, X.: Point Set Registration: Coherent Point Drift. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2262–2275 (2010)CrossRefGoogle Scholar
  14. 14.
    Besl, P.J., McKay, N.D.: A Method for Registration of 3-D Shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992)CrossRefGoogle Scholar
  15. 15.
    Shapira, L., Shamir, A., Cohen-Or, D.: Consistent Mesh Partitioning and Skeletonisation Using the Shape Diameter Function. Visual Comput. 24, 249–259 (2008)CrossRefGoogle Scholar
  16. 16.
    Banegas, F., Jaeger, M., Michelucci, D., Roelens, M.: The Ellipsoidal Skeleton in Medical Applications. In: ACM Symposium on Solid Modeling and Applications, pp. 30–38 (2001)Google Scholar
  17. 17.
    Zhou, J., Xiong, W., Ding, F., Huang, W., Qi, T., Wang, Z., Oo, T., Venkatesh, S.K.: Liver Workbench: A Tool Suite for Liver and Liver Tumor Segmentation and Modeling. In: Loménie, N., Racoceanu, D., Gouaillard, A. (eds.) Advances in Bio-imaging. AISC, vol. 120, pp. 193–207. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  18. 18.
    Su, Y., Chua, K.S., Chong, C.S.: Mesh Processing Using Virtual Geometry. WSEAS Transactions on Computers 5(4), 696–704 (2006)Google Scholar
  19. 19.
    Cohen-Steiner, D., Morvan, J.-M.: Restricted Delaunay Triangulations and Normal Cycle. In: ACM Symposium on Computational Geometry, pp. 237–246 (2003)Google Scholar
  20. 20.
    Vogel, J., Schiele, B.: Semantic Modeling of Natural Scenes for Content-Based Image Retrieval. Int. J. Comput. Vis. 72(2), 133–157 (2007)CrossRefGoogle Scholar
  21. 21.
    Chen, D.-Y., Tian, X.-P., Shen, Y.-T., Ouhyoung, M.: On Visual Similarity Based 3D Model Retrieval. In: Computer Graphics Forum (EUROGRAPHICS 2003), vol. 22(3) (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Weimin Huang
    • 1
  • Wei Xiong
    • 1
  • Jiayin Zhou
    • 1
  • Jing Zhang
    • 5
  • Tao Yang
    • 1
  • Jiang Liu
    • 1
  • Yi Su
    • 2
  • Calvin Lim
    • 2
  • Chee Kong Chui
    • 3
  • Stephen Chang
    • 4
  1. 1.Institute for Infocomm ResearchAgency for Science, Technology and ResearchSingaporeSingapore
  2. 2.Institute of High Performance ComputingAgency for Science, Technology and ResearchSingaporeSingapore
  3. 3.Department of Mechanical Engineering, Faculty of EngineeringNational University of Singapore, Centre for Biomedical Materials Application and TechnologySingaporeSingapore
  4. 4.Department of SurgeryNational University HospitalSingaporeSingapore
  5. 5.Department of Medical Information Engineering, School of Electrical Engineering and InformationSichuan UniversityP.R. China

Personalised recommendations