Estimation of organ motion from 4D CT for 4D radiation therapy planning of lung cancer

Michael R. Kaus, Thomas Netsch, Sven Kabus, Vladimir Pekar, Todd McNutt, Bernd Fischer

Research output: Contribution to journalConference articlepeer-review


The goal of this paper is to automatically estimate the motion of the tumor and the internal organs from 4D CT and to extract the organ surfaces. Motion induced by breathing and heart beating is an important uncertainty in conformal external beam radiotherapy (RT) of lung tumors. 4D RT aims at compensating the geometry changes during irradiation by incorporating the motion into the treatment plan using 4D CT imagery. We establish two different methods to propagate organ models through the image time series, one based on deformable surface meshes, and the other based on volumetric B-spline registration. The methods are quantitatively evaluated on 8 3D CT images of the full breathing cycle of a patient with manually segmented lungs and heart. Both methods achieve good overall results, with mean errors of 1.02-1.33 mm and 0.78-2.05 mm for deformable surfaces and B-splines respectively. The deformable mesh is fast (40 seconds vs. 50 minutes), but accommodation of the heart and the tumor is currently not possible. B-spline registration estimates the motion of all structures in the image and their interior, but is susceptible to motion artifacts in CT.

Original languageEnglish (US)
Pages (from-to)1017-1024
Number of pages8
JournalLecture Notes in Computer Science
Issue number1 PART 2
StatePublished - 2004
EventMedical Image Computing and Computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings - Saint-Malo, France
Duration: Sep 26 2004Sep 29 2004


  • 4D CT
  • B-splines
  • Deformable registration
  • Deformable surface models
  • Lung cancer
  • Radiation therapy

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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