Towards Automatic Plan Selection for Radiotherapy of Cervical Cancer by Fast Automatic Segmentation of Cone Beam CT Scans
We propose a method to automatically select a treatment plan for radiotherapy of cervical cancer using a Plan-of-the-Day procedure, in which multiple treatment plans are constructed prior to treatment. The method comprises a multi-atlas based segmentation algorithm that uses the selected treatment plan to choose between two atlas sets. This segmentation only requires two registration procedures and can therefore be used in clinical practice without using excessive computation time. Our method is validated on a dataset of 224 treatment fractions for 10 patients. In 37 cases (16%), no recommendation was made by the algorithm due to poor image quality or registration results. In 93% of the remaining cases a correct recommendation for a treatment plan was given.
KeywordsCervical Cancer Treatment Plan Clinical Target Volume Helical Tomotherapy Bladder Volume
- 3.Bondar, M.L., Hoogeman, M.S., Mens, J.W., Quint, S., Ahmad, R., Dhawtal, G., Heijmen, B.J.: Individualized nonadaptive and online-adaptive IMRT treatment strategies for cervical cancer patients based on pre-treatment acquired variable bladder filling CT-scans. Int. J. Radiat. Oncol. Biol. Phys. 83(5), 1617–1623 (2012)CrossRefGoogle Scholar
- 7.Langerak, T.R., van der Heide, U.A., Kotte, A.N.T.J., van Vulpen, M., Viergever, M., Pluim, J.P.W.: Label fusion in atlas-based segmentation using a selective and iterative method for performance level estimation (SIMPLE). IEEE Transactions on Medical Imaging 29(12), 2000–2008 (2010)CrossRefGoogle Scholar
- 9.Langerak, T.R., Berendsen, F.F., van der Heide, U.A., Kotte, A.N.T.J., Pluim, J.P.W.: Multi-atlas-based segmentation with preregistration atlas selection. Med. Phys. 40(9), 091701 (2013)Google Scholar
- 11.Rohlfing, T., Brandt, R., Menzel, R., Russakoff, D.B., Maurer Jr., C.R.: Quo vadis, atlas-based segmentation? In: Suri, J.S., Wilson, D.L., Laxminarayan, S. (eds.) Handbook of Biomedical Image Analysis. Topics in Biomedical Engineering International Book Series, pp. 435–486 (2005)Google Scholar
- 13.Wu, G., Wang, Q., Zhang, D., Nie, F., Huang, H., Shen, D.: A generative probability model of joint label fusion for multi-atlas based brain segmentation. Med. Image Anal. (in press)Google Scholar