Please use this identifier to cite or link to this item: https://doi.org/10.1109/CVPR.2008.4587742
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dc.titleVolumetric reconstruction from multi-energy single-view radiography
dc.contributor.authorLe, S.N.
dc.contributor.authorMei, K.L.
dc.contributor.authorBanu, S.
dc.contributor.authorFang, A.C.
dc.date.accessioned2013-07-04T07:59:42Z
dc.date.available2013-07-04T07:59:42Z
dc.date.issued2008
dc.identifier.citationLe, S.N.,Mei, K.L.,Banu, S.,Fang, A.C. (2008). Volumetric reconstruction from multi-energy single-view radiography. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/CVPR.2008.4587742" target="_blank">https://doi.org/10.1109/CVPR.2008.4587742</a>
dc.identifier.isbn9781424422432
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40236
dc.description.abstractWe address the volumetric reconstruction problem that takes as input a series of orthographic multi-energy x-ray images, producing as output a reconstructed model space consisting of uniform-size mass density voxels. Our approach solves the nonlinear constrained optimization formulation problem by constructing a compliant estimate of volumetric distribution, subject to projective and domain constraints, and minimizes variational irregularities. To resolve the inherent ambiguities of single-view formulation, an optional shape model may be introduced to aid the reconstruction process. We demonstrate our method's practical usage as a new in-vivo method for estimating three-dimensional body segmental compositions, and compare its results with those of existing methods. ©2008 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/CVPR.2008.4587742
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/CVPR.2008.4587742
dc.description.sourcetitle26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
dc.identifier.isiutNOT_IN_WOS
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