Skip to main content
Log in

Three-dimensional organ modeling based on deformable surfaces applied to radio-oncology

  • Published:
Journal of Zhejiang University SCIENCE C Aims and scope Submit manuscript

Abstract

This paper describes a method based on an energy minimizing deformable model applied to the 3D biomechanical modeling of a set of organs considered as regions of interest (ROI) for radiotherapy. The initial model consists of a quadratic surface that is deformed to the exact contour of the ROI by means of the physical properties of a mass-spring system. The exact contour of each ROI is first obtained using a geodesic active contour model. The ROI is then parameterized by the vibration modes resulting from the deformation process. Once each structure has been defined, the method provides a 3D global model including the whole set of ROIs. This model allows one to describe statistically the most significant variations among its structures. Statistical ROI variations among a set of patients or through time can be analyzed. Experimental results are presented using the pelvic zone to simulate anatomical variations among structures and its application in radiotherapy treatment planning.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Banik, S., Rangayyan, R., Boag, G., 2009. Landmarking and Segmentation of 3D CT Images. Springer Berlin Heidelberg. [doi:10.1007/s11548-009-0289-y]

  • Bueno, G., 2008. Fuzzy Systems and Deformable Models. In: Haas, O.C.L., Burnham, K.J. (Eds.), Intelligent and Adaptive Systems in Medicine, Chapter 10. Series in Medical Physics and Biomedical Engineering. Taylor & Francis Group, London, p.305–329.

    Google Scholar 

  • Bueno, G., Fisher, M., Burnham, K., 2001. Automatic Segmentation of Clinical Structures for RTP: Evaluation of a Morphological Approach. Proc. Medical Image Understanding and Analysis, p.73–76.

  • Bueno, G., Martínez, A., Adán, A., 2004. Fuzzy snake segmentation of anatomical structures applied to CT images. LNCS, 3212:33–42.

    Google Scholar 

  • Bueno, G., Déniz, O., Carrascosa, C., Delgado, J., Brualla, L., 2009. Fast Monte Carlo simulation on a voxelized human phantom deformed to a patient. Med. Phys., 36(11):5162–5174. [doi:10.1118/1.3245877]

    Article  Google Scholar 

  • Camapum, J., Silva, A., Freitas, A., Bassani, H., 2004. Segmentation of Clinical Structures from Images of the Human Pelvic Area. Proc. 17th Brazilian Symp. on Computer Graphics and Image Processing, p.10–16. [doi:10.1109/SIBGRA.2004.1352937]

  • Caselles, V., Kimmel, R., Sapiro, G., 1997. Geodesic active contours. Int. J. Comput. Vis., 22(1):61–79. [doi:10.1023/A:1007979827043]

    Article  MATH  Google Scholar 

  • Collier, D., Burnett, S., Amin, M., 2003. Assessment of consistency in contouring of normal-tissue anatomic structures. J. Appl. Clin. Med. Phys., 4(1):17–24. [doi:10.1120/1.1521271]

    Article  Google Scholar 

  • Costa, M., Delingette, H., Ayache, N., 2007. Automatic Segmentation of the Bladder Using Deformable Models. 4th IEEE Int. Symp on Biomedical Imaging: from Nano to Macro, p.904–907. [doi:10.1109/ISBI.2007.356999]

  • Déniz, O., Castrillón, M., Lorenzo, J., Antón, L., Hernandez, M., Bueno, G., 2010. Computer vision based eyewear selector. J. Zheijang Univ.-Sci. C (Comput. & Eletron.), 11(2):79–91. [doi:10.1631/jzus.C0910377]

    Article  Google Scholar 

  • Fisher, M., Su, Y., Aldridge, R., 2008. Some Applications of Intelligent Systems in Cancer Treatment: a Review. In: Haas, O.C.L., Burnham, K.J. (Eds.), Intelligent and Adaptive Systems in Medicine, Chapter 9. Series in Medical Physics and Biomedical Engineering. Taylor & Francis Group, London, p.283–303.

    Google Scholar 

  • Foskey, M., Davis, B., Goyal, L., Chang, S., Chaney, E., Strehl, N., Tomei, S., Rosenman, J., Joshi, S., 2005. Large deformation three-dimensional image registration in image-guided radiation therapy. Phys. Med. Biol., 50(24):5869–5892. [doi:10.1088/0031-9155/50/24/008]

    Article  Google Scholar 

  • Gibou, F., Levy, D., Cádenas, C., 2005. Partial differential equations based segmentation for radiotherapy treatment planning. Math. Biosci. Eng., 2(2):209–226.

    MathSciNet  Google Scholar 

  • Haas, B., Coradi, T., Scholz, M., Kunz, P., Huber, M., Oppitz, U., André, L., Lengkeek, V., Huyskens, D., van Esch, A., et al., 2008. Assessment of consistency in contouring of normal-tissue anatomic structures. Phys. Med. Biol., 53(6):1751–1771. [doi:10.1088/0031-9155/53/6/017]

    Article  Google Scholar 

  • Kass, M., Witkin, A., Terzopoulos, D., 1988. Snakes: active contour models. Int. J. Comput. Vis., 1(4):321–331. [doi:10.1007/BF00133570]

    Article  Google Scholar 

  • Lee, C., Chung, P., 2004. Identifying Abdominal Organs Using Robust Fuzzy Inference Model. IEEE Int. Conf. on Networking, Sensing and Control, 2:1289–1294. [doi:10.1109/ICNSC.2004.1297133]

    Article  Google Scholar 

  • Lee, M., Park, S., Cho, W., Kim, S., Jeong, C., 2008. Segmentation of medical images using a geometric deformable model and its visualization. Can. J. Electr. Comput. Eng., 33(1):15–19. [doi:10. 1109/CJECE.2008.4621790]

    Article  Google Scholar 

  • Malladi, R., Sethian, J., Vemuri, B., 1995. Shape modeling with front propagation: a level set approach. IEEE Trans. PAMI, 17(4):158–175.

    Google Scholar 

  • Mazonakis, M., Damilakis, J., Varveris, H., Prassopoulos, P., Gourtsoyiannis, N., 2001. Image segmentation in treatment planning for prostate cancer using the region growing technique. Br. J. Radiol., 74:243–249.

    Google Scholar 

  • Nastar, C., Ayache, N., 1996. Frequency-based nonrigid motion analysis. IEEE Trans. PAMI, 18(11):1069–1079. [doi:10.1109/34.544076]

    Google Scholar 

  • Nikou, C., Bueno, G., Heitz, F., Armspach, J., 2001. A joint physics-based statistical deformable model for multimodal brain image analysis. IEEE Trans. Med. Imag., 20(10):1026–1037. [doi:10.1109/42.959300]

    Article  Google Scholar 

  • Osher, S., Paragios, N., 2003. Geometric Level Set Methods in Imaging, Vision and Graphics. Springer-Verlag New York.

  • Paragios, N., 2002. A level set approach for shape driven segmentation and tracking of the left ventricle. IEEE Trans. Nucl. Sci., 21(3):21–43.

    Google Scholar 

  • Pentland, A., Sclaroff, S., 1991. A closed-form solutions for physically-based shape modelling and recognition. IEEE Trans. PAMI, 13(7):730–742.

    Google Scholar 

  • Ripoche, X., Atif, J., Osorio, A., 2004. A 3D Discrete Deformable Model Guided by Mutual Information for Medical Image Segmentation. Proc. Medical Imaging Conf., p.1–3.

  • Rousson, M., Khamene, A., Diallo, M., 2005. Constrained surface evolutions for prostate and bladder segmentation in CT images. LNCS, 3765:251–260. [doi:10.1007/11569541_26]

    Google Scholar 

  • Shepp, L., Logan, B., 1974. The Fourier reconstruction of a head section. IEEE Trans. Med. Imag., 22(6):773–776.

    Google Scholar 

  • Shi, F., Yang, J., Zhu, Y., 2009. Automatic segmentation of bladder in CT images. J. Zhejiang Univ.-Sci. A, 10(2):239–246. [doi:10.1631/jzus.A0820157]

    Article  MATH  Google Scholar 

  • Su, Y., Fisher, M., Rowland, R.S., 2007. Markerless intra-fraction organ motion tracking using hybrid ASM. Int. J. Comput. Assist. Radiol. Surg., 2(3–4):231–243. [doi:10.1007/s11548-007-0133-1]

    Article  Google Scholar 

  • Terzopoulos, D., Fleischer, K., 1988. Deformable models. The Vis. Comput., 4(6):306–331. [doi:10.1007/BF01908877]

    Article  Google Scholar 

  • Webb, S., 2006. Does elastic tissue intrafraction motion with density changes forbid motion-compensated radiotherapy? Phys. Med. Biol., 51(6):1449–1462. [doi:10.1088/0031-9155/51/6/006]

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gloria Bueno.

Additional information

Project partially supported by the VI FP and VII FP of the European Commission through MAESTRO and ENVISION projects (Nos. IP CE503564 and SP CE241851) and Spanish Junta de Comunidades de Castilla-La Mancha (Nos. PBC06-0019 and PI-2006/01.1)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bueno, G., Déniz, O., salido, J. et al. Three-dimensional organ modeling based on deformable surfaces applied to radio-oncology. J. Zhejiang Univ. - Sci. C 11, 407–417 (2010). https://doi.org/10.1631/jzus.C0910402

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1631/jzus.C0910402

Key words

CLC number

Navigation