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Proceedings Paper

Free-breathing intra- and intersubject respiratory motion capturing, modeling, and prediction
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Paper Abstract

Respiration-induced organ motion can limit the accuracy required for many clinical applications working on the thorax or upper abdomen. One approach to reduce the uncertainty of organ location caused by respiration is to use prior knowledge of breathing motion. In this work, we deal with the extraction and modeling of lung motion fields based on free-breathing 4D-CT data sets of 36 patients. Since data was acquired for radiotherapy planning, images of the same patient were available over different weeks of treatment. Motion field extraction is performed using an iterative shape-constrained deformable model approach. From the extracted motion fields, intra- and inter-subject motion models are built and adapted in a leave-one-out test. The created models capture the motion of corresponding landmarks over the breathing cycle. Model adaptation is then performed by examplarily assuming the diaphragm motion to be known. Although, respiratory motion shows a repetitive character, it is known that patients' variability in breathing pattern impedes motion estimation. However, with the created motion models, we obtained a mean error between the phases of maximal distance of 3.4 mm for the intra-patient and 4.2 mm for the inter-patient study when assuming the diaphragm motion to be known.

Paper Details

Date Published: 27 March 2009
PDF: 11 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72590T (27 March 2009); doi: 10.1117/12.811990
Show Author Affiliations
Tobias Klinder, Leibniz Univ. Hannover (Germany)
Philips Research Europe (Germany)
Cristian Lorenz, Philips Research Europe (Germany)
Jörn Ostermann, Leibniz Univ. Hannover (Germany)


Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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