Advertisement

Prone to Supine CT Colonography Registration Using a Landmark and Intensity Composite Method

  • Thomas E. Hampshire
  • Holger R. Roth
  • Darren J. Boone
  • Greg Slabaugh
  • Steve Halligan
  • David J. Hawkes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7601)

Abstract

Matching corresponding location between prone and supine acquisitions for CT colonography (CTC) is essential to verify the existence of a polyp, which can be a difficult task due to the considerable deformations that will often occur to the colon during repositioning of the patient. This can induce error and increase interpretation time. We propose a novel method to automatically establish correspondence between the two acquisitions. A first step segments a set of haustral folds in each view and determines correspondence via a labelling process using a Markov Random Field (MRF) model. We show how the landmark correspondences can be used to non-rigidly transform a 2D source image derived from a conformal mapping process on the 3D endoluminal surface mesh to achieve full surface correspondence between prone and supine views. This can be used to initialise an intensity-based non-rigid B-spline registration method which further increases the accuracy. We demonstrate a statistically significant improvement over the intensity based non-rigid B-spline registration by using the composite method.

Keywords

CT colonography image registration 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Fukano, E., Oda, M., Kitasaka, T., Suenaga, Y., Takayama, T., Takabatake, H., Mori, M., Natori, H., Nawano, S., Mori, K.: Haustral fold registration in CT colonography and its application to registration of virtual stretched view of the colon. In: Proceedings of SPIE, vol. 7624, p. 762420 (2010)Google Scholar
  2. 2.
    Hampshire, T., Roth, H., Hu, M., Boone, D., Slabaugh, G., Punwani, S., Halligan, S., Hawkes, D.: Automatic Prone to Supine Haustral Fold Matching in CT Colonography Using a Markov Random Field Model. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011, Part I. LNCS, vol. 6891, pp. 508–515. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  3. 3.
    Jin, M., Kim, J., Luo, F., Gu, X.: Discrete surface ricci flow. IEEE Transactions on Visualization and Computer Graphics 14(5), 1030–1043 (2008)CrossRefGoogle Scholar
  4. 4.
    Koenderink, J.J.: Solid shape. MIT Press, Cambridge (1990)Google Scholar
  5. 5.
    Lee, S., Wolberg, G., Shin, S.Y.: Scattered data interpolation with multilevel B-splines. IEEE Transactions on Visualization and Computer Graphics 3(3), 228–244 (1997)CrossRefGoogle Scholar
  6. 6.
    Näppi, J., Okamura, A., Frimmel, H., Dachman, A., Yoshida, H.: Region-based supine-prone correspondence for the reduction of false-positive CAD polyp candidates in CT colonography. Academic Radiology 12(6), 695–707 (2005)CrossRefGoogle Scholar
  7. 7.
    Roth, H., McClelland, J., Boone, B., Modat, M., Cardoso, M., Hampshire, T., Hu, M., Punwani, S., Ourselin, S., Slabaugh, G., Halligan, S., Hawkes, D.: Registration of the endoluminal surfaces of the colon derived from prone and supine CT colonography. Medical Physics 38(6), 3077–3089 (2011), http://link.aip.org/link/?MPH/38/3077/1 CrossRefGoogle Scholar
  8. 8.
    Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L.G., Leach, M.O., Hawkes, D.J.: Nonrigid registration using free-form deformations: application to breast MR images. IEEE Transactions on Medical Imaging 18(8), 712–721 (1999)CrossRefGoogle Scholar
  9. 9.
    Suh, J.W., Wyatt, C.L.: Deformable registration of supine and prone colons for computed tomographic colonography. Journal of Computer Assisted Tomography 33(6), 902 (2009)CrossRefGoogle Scholar
  10. 10.
    Taylor, S.A., Halligan, S., Goh, V., Morley, S., Bassett, P., Atkin, W., Bartram, C.I.: Optimizing colonic distention for multi–detector row CT colonography: Effect of hyoscine butylbromide and rectal balloon catheter. Radiology 229(1), 99 (2003)CrossRefGoogle Scholar
  11. 11.
    Taylor, S.A., Laghi, A., Lefere, P., Halligan, S., Stoker, J.: European society of gastrointestinal and abdominal radiology (esgar): consensus statement on CT colonography. European Radiology 17(2), 575–579 (2007)CrossRefGoogle Scholar
  12. 12.
    Wang, S., Yao, J., Liu, J., Petrick, N., Van Uitert, R.L., Periaswamy, S., Summers, R.M.: Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis. Medical Physics 36, 5595 (2009)CrossRefGoogle Scholar
  13. 13.
    Weiss, Y., Freeman, W.T.: On the optimality of solutions of the max-product belief-propagation algorithm in arbitrary graphs. IEEE Transactions on Information Theory 47(2), 736–744 (2002)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Zeng, W., Marino, J., Gurijala, K.C., Gu, X., Kaufman, A.: Supine and prone colon registration using quasi-conformal mapping. IEEE Transactions on Visualization and Computer Graphics 16, 1348–1357 (2010)CrossRefGoogle Scholar
  15. 15.
    Zeng, W., Samaras, D., Gu, D.: Ricci flow for 3D shape analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(4), 662–677 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Thomas E. Hampshire
    • 1
  • Holger R. Roth
    • 1
  • Darren J. Boone
    • 2
  • Greg Slabaugh
    • 3
  • Steve Halligan
    • 2
  • David J. Hawkes
    • 1
  1. 1.Centre for Medical Image ComputingUniversity College LondonLondonUK
  2. 2.Centre for Medical ImagingUniversity College HospitalLondonUK
  3. 3.Department of ComputingCity UniversityLondonUK

Personalised recommendations