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Estimating 3-D Respiratory Motion From Orbiting Views by Tomographic Image Registration

dc.contributor.authorZeng, Rongpingen_US
dc.contributor.authorFessler, Jeffrey A.en_US
dc.contributor.authorBalter, James M.en_US
dc.date.accessioned2011-08-18T18:21:19Z
dc.date.available2011-08-18T18:21:19Z
dc.date.issued2007-01-29en_US
dc.identifier.citationZeng, R.; Fessler, J. A.; Balter, J. M. (2007). "Estimating 3-D Respiratory Motion From Orbiting Views by Tomographic Image Registration. " IEEE Transactions on Medical Imaging 26(2): 153-163. <http://hdl.handle.net/2027.42/85995>en_US
dc.identifier.issn0278-0062en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/85995
dc.description.abstractRespiratory motion remains a significant source of errors in treatment planning for the thorax and upper abdomen. Recently, we proposed a method to estimate two-dimensional (2-D) object motion from a sequence of slowly rotating X-ray projection views, which we called deformation from orbiting views (DOVs). In this method, we model the motion as a time varying deformation of a static prior of the anatomy. We then optimize the parameters of the motion model by maximizing the similarity between the modeled and actual projection views. This paper extends the method to full three-dimensional (3-D) motion and cone-beam projection views. We address several practical issues for using a cone-beam computed tomography (CBCT) scanner that is integrated in a radiotherapy system, such as the effects of Compton scatter and the limited gantry rotation for one breathing cycle. We also present simulation and phantom results to illustrate the performance of this method.en_US
dc.publisherIEEEen_US
dc.titleEstimating 3-D Respiratory Motion From Orbiting Views by Tomographic Image Registrationen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelBiomedical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Electrical Engineering and Computer Science. Department of Radiation Oncology.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/85995/1/Fessler38.pdf
dc.identifier.doi10.1109/TMI.2006.889719en_US
dc.identifier.sourceIEEE Transactions on Medical Imagingen_US
dc.owningcollnameElectrical Engineering and Computer Science, Department of (EECS)


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