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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaoxiao Liu Saboo, R.R. Pizer, S.M. Mageras, G.S. |
| Copyright Year | 2009 |
| Description | Author affiliation: Computer Science Department, The University of North Carolina at Chapel Hill, USA (Xiaoxiao Liu; Saboo, R.R.; Pizer, S.M.) || Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, USA (Mageras, G.S.) |
| Abstract | Intensity modulated radiation therapy (IMRT) for cancers in the lung remains challenging due to the complicated respiratory dynamics. We propose a shape-navigated dense image deformation model to estimate the patient-specific breathing motion using 4D respiratory correlated CT (RCCT) images. The idea is to use the shape change of the lungs, the major motion feature in the thorax image, as a surrogate to predict the corresponding dense image deformation from training. |
| Starting Page | 875 |
| Ending Page | 878 |
| File Size | 315455 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424439317 |
| ISSN | 19457928 |
| DOI | 10.1109/ISBI.2009.5193192 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-06-28 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Deformable models Lungs Motion estimation Shape Intensity modulation Biomedical applications of radiation Cancer Computed tomography Thorax Statistics statistical shape analysis respiratory motion model diffeomorphic image registration |
| Content Type | Text |
| Resource Type | Article |
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