3D Deformable Registration for Monitoring Radiotherapy Treatment in Prostate Cancer
Abstract
Two deformable registration methods, the Demons and the Morphon algorithms, have been used for registration of CT datasets to evaluate their usability in radiotherapy planning for prostate cancer. These methods were chosen because they can perform deformable registration in a fully automated way. The experiments show that for intrapatient registration both of the methods give useful results, although some differences exist in the way they deform the template. The Morphon method has, however, some advantageous compared to the Demons method. It is invariant to the image intensity and it does not distort the deformed data. The conclusion is therefore to recommend the Morphon method as a registration tool for this application. A more flexible regularization model is needed, though, in order to be able to catch the full range of deformations required to match the datasets.
Keywords
Prostate Cancer Normal Tissue Complication Probability Template Image Displacement Estimate Deformable RegistrationReferences
- 1.Antolak, J.A., Rosen, I.I., Childress, C.H., Zagars, G.K., Pollack, A.: Prostate target volume variations during a course of radiotherapy. Int. Journal of Radiation Oncology Biol. Phys. 42(3), 661–672 (1998)CrossRefGoogle Scholar
- 2.Cheung, R., Tucker, S.L., Ye, J.S., Dong, L., Liu, H., Huang, E., Mohan, R., Kuban, D.: Characterization of rectal normal tissue complication probability after high-dose external beam radiotherapy for prostate cancer. Int. Journal of Radiation Oncology Biol. Phys. 58(5), 1513–1519 (2004)CrossRefGoogle Scholar
- 3.Granlund, G.H., Knutsson, H.: Signal Processing for Computer Vision. Kluwer Academic Publishers, Dordrecht (1995)Google Scholar
- 4.Hill, D., Batchelor, P., Holden, M., Hawkes, D.: Medical image registration. Physics in Medicine and Biology 46(3), 1–45 (2001)CrossRefGoogle Scholar
- 5.Thirion, J.-P.: Fast non-rigid matching of 3d medical images. Technical Report 2547, INRIA (May 1995)Google Scholar
- 6.Knutsson, H., Andersson, M.: Morphons: Paint on Priors and Elastic Canvas for Segmentation and Registration. In: Kalviainen, H., Parkkinen, J., Kaarna, A. (eds.) SCIA 2005. LNCS, vol. 3540, pp. 292–301. Springer, Heidelberg (2005)Google Scholar
- 7.Martinez, A.A., Yan, D., Lockman, D., Brabbins, D., Kota, K., Sharpe, M., Jaffray, D.A., Vicini, F., Wong, J.: Improvement in dose escalation using the process of adaptive radiotherapy combined with three-dimensional conformal or intensity-modulated beams for prostate cancer. Int. Journal of Radiation Oncology Biol. Phys. 50(5), 1226–1234 (2001)CrossRefGoogle Scholar
- 8.National Library of Medicine. Medlineplus health information on prostate cancer (November 2006), http://www.nlm.nih.gov/medlineplus/ency/article/000380.htm
- 9.Pettersson, J.: Automatic generation of patient specific models for hip surgery simulation. Lic. Thesis LiU-Tek-Lic-2006:24, Linköping University, Sweden, Thesis No. 1243 (April 2006)Google Scholar
- 10.Wang, H., Dong, L., Lii, M.F., Lee, A.L., de Crevoisier, R., Mohan, R., Cox, J.D., Kuban, D.A., Cheung, R.: Implementation and validation of a three-dimensional deformable registration algorithm for targeted prostate cancer radiotherapy. Int. Journal of Radiation Oncology Biol. Phys. 61(3), 725–735 (2005)CrossRefGoogle Scholar
- 11.Wrangsjö, A., Pettersson, J., Knutsson, H.: Non-rigid Registration Using Morphons. In: Kalviainen, H., Parkkinen, J., Kaarna, A. (eds.) SCIA 2005. LNCS, vol. 3540, pp. 501–510. Springer, Heidelberg (2005)Google Scholar