Respiratory Motion Estimation from Cone-Beam Projections Using a Prior Model

Published on Oct 1, 2009 in MICCAI (Medical Image Computing and Computer-Assisted Intervention)
· DOI :10.1007/978-3-642-04271-3_45
Jef Vandemeulebroucke14
Estimated H-index: 14
(University of Lyon),
Jan Kybic26
Estimated H-index: 26
(CTU: Czech Technical University in Prague)
+ 1 AuthorsDavid Sarrut28
Estimated H-index: 28
(University of Lyon)
Respiratory motion introduces uncertainties when planning and delivering radiotherapy for lung cancer patients. Cone-beam projections acquired in the treatment room could provide valuable information for building motion models, useful for gated treatment delivery or motion compensated reconstruction. We propose a method for estimating 3D+T respiratory motion from the 2D+T cone-beam projection sequence by including prior knowledge about the patient's breathing motion. Motion estimation is accomplished by maximizing the similarity of the projected view of a patient specific model to observed projections of the cone-beam sequence. This is done semi-globally, considering entire breathing cycles. Using realistic patient data, we show that the method is capable of good prediction of the internal patient motion from cone-beam data, even when confronted with interfractional changes in the breathing motion.
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