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dc.contributor.authorWen, Tiancien_US
dc.contributor.authorMihail, Raduen_US
dc.contributor.authorAl-maliki, shathaen_US
dc.contributor.authorLetang, Jeanen_US
dc.contributor.authorVidal, Francken_US
dc.contributor.editorVidal, Franck P. and Tam, Gary K. L. and Roberts, Jonathan C.en_US
dc.date.accessioned2019-09-11T05:09:06Z
dc.date.available2019-09-11T05:09:06Z
dc.date.issued2019
dc.identifier.isbn978-3-03868-096-3
dc.identifier.urihttps://doi.org/10.2312/cgvc.20191265
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/cgvc20191265
dc.description.abstractRegistration has been studied extensively for the past few decades. In this paper we propose to solve the registration of 3D triangular models onto 2D X-ray projections. Our approach relies extensively on global optimisation methods and fast X-ray simulation on GPU. To evaluate our pipeline, each optimisation is repeated 15 times to gather statistically meaningful results, in particular to assess the reproducibility of the outputs.We demonstrate the validity of our approach on two registration problems: i) 3D kinematic configuration of a 3D hand model, i.e. the recovery of the original hand pose from a postero-anterior (PA) view radiograph. The performance is measured by Mean Absolute Error (MAE). ii) Automatic estimation of the position and rigid transformation of geometric shapes (cube and cylinders) to match an actual metallic sample made of Ti/SiC fibre composite with tungsten (W) cores. In this case the performance is measured in term of F-score (86%), accuracy (95%), precision (75%), recall (100%), and true negative rate (94%). Our registration framework is successful for both test-cases when using a suitable optimisation algorithm.en_US
dc.publisherThe Eurographics Associationen_US
dc.titleRegistration of 3D Triangular Models to 2D X-ray Projections Using Black-box Optimisation and X-ray Simulationen_US
dc.description.seriesinformationComputer Graphics and Visual Computing (CGVC)
dc.description.sectionheadersComputer Vision
dc.identifier.doi10.2312/cgvc.20191265
dc.identifier.pages105-113


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