Abstract
In this paper, we propose a novel method to convert segmentation of objects with quasi-periodic motion in 2D rotational cone beam projection images into an optimal 3D multiple interrelated surface detection problem, which can be solved by a graph search framework. The method is tested on lung tumor segmentation in projection images of mega-voltage cone beam CT (MVCBCT). A 4D directed graph is constructed based on an initialized tumor mesh model, where the cost value for this graph is computed from the point location of a silhouette outline of projected tumor mesh in 2D projection images. The method was first evaluated on four different sized phantom inserts (all above 1.9 cm in diameter) with a predefined motion of 3.0 cm to mimic the imaging of lung tumors. A dice coefficient of 0.87 ±0.03 and a centroid error of 1.94 ±1.31 mm were obtained. Results based on 12 MVCBCT scans from 3 patients obtained 0.91 ±0.03 for dice coefficient and 1.83 ±1.31 mm for centroid error, compared with a difference between two sets of independent manual contours of 0.89 ±0.03 and 1.61 ±1.19 mm, respectively.
Chapter PDF
References
Morin, O., Gillis, A., Chen, J., Aubin, M., Bucci, M., Roach III, M., Pouliot, J.: Megavoltage cone-beam CT: system description and clinical applications. Medical Dosimetry 31(1), 51–61 (2006)
Jaffray, D., Siewerdsen, J., Wong, J., Martinez, A.: Flat-panel cone-beam computed tomography for image-guided radiation therapy. International Journal of Radiation Oncology Biology Physics 53(5), 1337–1349 (2002)
Reitz, B., Gayou, O., Parda, D., Miften, M.: Monitoring tumor motion with on-line mega-voltage cone-beam computed tomography imaging in a cine mode. Physics in Medicine and Biology 53, 823–836 (2008)
Li, T., Xing, L., Munro, P., McGuinness, C., Chao, M., Yang, Y., Loo, B., Koong, A.: Four-dimensional cone-beam computed tomography using an on-board imager. Medical Physics 33, 3825–3833 (2006)
Siochi, R.: Deriving motion from megavoltage localization cone beam computed tomography scans. Physics in Medicine and Biology 54, 4195–4212 (2009)
Li, T., Koong, A., Xing, L.: Enhanced 4D cone-beam CT with inter-phase motion model. Medical Physics 34, 3688–3695 (2007)
Shimizu, S., Shirato, H., Ogura, S., Akita-Dosaka, H., Kitamura, K., Nishioka, T., Kagei, K., Nishimura, M., Miyasaka, K.: Detection of lung tumor movement in real-time tumor-tracking radiotherapy. International Journal of Radiation Oncology Biology Physics 51(2), 304–310 (2001)
Li, K., Millington, S., Wu, X., Chen, D.Z., Sonka, M.: Simultaneous Segmentation of Multiple Closed Surfaces Using Optimal Graph Searching. In: Christensen, G.E., Sonka, M. (eds.) IPMI 2005. LNCS, vol. 3565, pp. 406–417. Springer, Heidelberg (2005)
Lotjonen, J., Magnin, I., Nenonen, J., Katila, T.: Reconstruction of 3-D geometry using 2-D profiles and a geometric prior model. IEEE Trans. Medical Imaging 18(10), 992–1002 (1999)
Moriyama, M., Sato, Y., Naito, H., Hanayama, M., Ueguchi, T., Harada, T., Yoshimoto, F., Tamura, S.: Reconstruction of time-varying 3D left ventricular shape from multiview x-ray cineangiocardiograms. IEEE Trans. Medical Imaging, 773–785 (2002)
Chen, M., Zheng, Y., Mueller, K., Rohkohl, C., Lauritsch, G., Boese, J., Funka-Lea, G., Hornegger, J., Comaniciu, D.: Automatic Extraction of 3D Dynamic Left Ventricle Model from 2D Rotational Angiocardiogram. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011, Part III. LNCS, vol. 6893, pp. 471–478. Springer, Heidelberg (2011)
Chen, M., Siochi, R.: Diaphragm motion quantification in megavoltage cone-beam CT projection images. Medical Physics 37, 2312–2320 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, M., Bai, J., Zheng, Y., Siochi, R.A.C. (2012). 3D Lung Tumor Motion Model Extraction from 2D Projection Images of Mega-voltage Cone Beam CT via Optimal Graph Search. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33415-3_30
Download citation
DOI: https://doi.org/10.1007/978-3-642-33415-3_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33414-6
Online ISBN: 978-3-642-33415-3
eBook Packages: Computer ScienceComputer Science (R0)