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dc.contributor.authorBelloso, Alvaro
dc.contributor.authorZhang, Xirang
dc.contributor.authorYang, Yongyi
dc.contributor.authorWernick, Miles N.
dc.contributor.authorPretorius, P. Hendrik
dc.contributor.authorKing, Michael A.
dc.date.accessioned2023-01-24T15:19:00Z
dc.date.available2023-01-24T15:19:00Z
dc.date.issued2022-03-28
dc.identifier.citationÁ. Belloso, X. Zhang, Y. Yang, M. N. Wernick, P. Hendrik Pretorius and M. A. King, "A Feasibility Study of Motion Compensation for Cardiac Gated Spect Images Using a Cascaded Network," 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), Kolkata, India, 2022, pp. 1-4, doi: 10.1109/ISBI52829.2022.9761571.en_US
dc.identifier.issn19457928
dc.identifier.eissn19458452
dc.identifier.doi10.1109/ISBI52829.2022.9761571en_US
dc.identifier.eid2-s2.0-85129629969
dc.identifier.scopusidSCOPUS_ID:85129629969
dc.identifier.urihttp://hdl.handle.net/20.500.14038/51588
dc.description.abstractMotion-compensated reconstruction has shown to be effective for suppressing imaging noise and reducing motion blur in cardiac-gated SPECT imaging. In this work we investigate the feasibility of using a cascaded learning network for motion correction in a sequence of gated images acquired at different phases of the cardiac cycle, which are known to suffer from both imaging degradation and large-extent motion deformation. To be realistic, we make use of a set of consecutive clinical acquisitions (from 130 subjects) which includes both normal and abnormal subjects. The quantitative results in the experiments indicate that the learning network can yield consistently more accurate compensation results than the classical optical flow equation (OFE) method both on standard dose and half dose studies. In particular, the learning network achieved a relative MSE of 0.021 (full dose) and 0.037 (half dose), compared to 0.035 (full dose) and 0.053 (half dose) for OFE.en_US
dc.description.sponsorshipNational Institutes of Healthen_US
dc.language.isoen_USen_US
dc.relation.ispartof2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)en_US
dc.relation.urlhttps://doi.org/10.1109/ISBI52829.2022.9761571en_US
dc.subjectCardiac gated imagesen_US
dc.subjectcascaded VTNen_US
dc.subjectmotion compensationen_US
dc.titleA Feasibility Study of Motion Compensation for Cardiac Gated Spect Images Using a Cascaded Networken_US
dc.typeConference Paperen_US
dc.source.journaltitleProceedings - International Symposium on Biomedical Imaging
dc.source.volume2022-March
dc.identifier.journalProceedings - International Symposium on Biomedical Imaging
dc.contributor.departmentRadiologyen_US


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