Model-Based Image Reconstruction for Dual-Energy X-Ray CT with Fast KVP Switching
dc.contributor.author | Huh, Wonseok | en_US |
dc.contributor.author | Fessler, Jeffrey A. | en_US |
dc.date.accessioned | 2011-08-18T18:20:49Z | |
dc.date.available | 2011-08-18T18:20:49Z | |
dc.date.issued | 2009-06-28 | en_US |
dc.identifier.citation | Huh, W.; Fessler, J. A. (2009). "Model-Based Image Reconstruction for Dual-Energy X-Ray CT with Fast KVP Switching." IEEE International Symposium on Biomedical Imaging: From Nano to Macro: 326-329. <http://hdl.handle.net/2027.42/85826> | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85826 | |
dc.description.abstract | The most recent generation of X-ray CT systems can collect dual energy (DE) sinograms by rapidly switching the X-ray tube voltage between two levels for alternate projection views. This reduces motion artifacts in DE imaging, but yields sinograms that may be angularly under-sampled. This paper describes an iterative algorithm for statistical image reconstruction of material component images (e.g., soft tissue and bone) directly from such under-sampled DE data, without resorting to the interpolation operations required by conventional DE reconstruction methods. | en_US |
dc.publisher | IEEE | en_US |
dc.title | Model-Based Image Reconstruction for Dual-Energy X-Ray CT with Fast KVP Switching | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Biomedical Engineering | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Electrical Engineering and Computer Science. | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/85826/1/Fessler241.pdf | |
dc.identifier.doi | 10.1109/ISBI.2009.5193050 | en_US |
dc.identifier.source | IEEE International Symposium on Biomedical Imaging: From Nano to Macro | en_US |
dc.owningcollname | Electrical Engineering and Computer Science, Department of (EECS) |
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