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27 March 2009 Free-breathing intra- and intersubject respiratory motion capturing, modeling, and prediction
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Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 72590T (2009) https://doi.org/10.1117/12.811990
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tobias Klinder, Cristian Lorenz, and Jörn Ostermann "Free-breathing intra- and intersubject respiratory motion capturing, modeling, and prediction", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72590T (27 March 2009); https://doi.org/10.1117/12.811990
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