This work is part a new design platform for lower limb prosthesis centered on the patient’s digital model and based on the integrated use of virtual prototyping tools. In particular, 3D detailed model of residual limb, that includes not only the external skin but also bones and soft tissues, is needed for socket design and finite element analysis to study the socket-residual limb interaction. In this paper, we present a procedure for 3D automatic reconstruction of the residual starting from MRI images. The output is a 3D geometric model, in a neutral format (IGES), which permits CAD information exchange among the modules composing the design platform. The reconstruction procedure consists of three different phases: image pre-processing, voxel segmentation, 3D models generation. Results have been considered promising and future activities to enhance the algorithm performance have been planned.
(2013). Automatic 3D Reconstruction of Transfemoral Residual Limb from MRI Images [conference presentation - intervento a convegno]. Retrieved from http://hdl.handle.net/10446/30012
Automatic 3D Reconstruction of Transfemoral Residual Limb from MRI Images
FACOETTI, Giancarlo;RIZZI, Caterina;VITALI, Andrea;
2013-01-01
Abstract
This work is part a new design platform for lower limb prosthesis centered on the patient’s digital model and based on the integrated use of virtual prototyping tools. In particular, 3D detailed model of residual limb, that includes not only the external skin but also bones and soft tissues, is needed for socket design and finite element analysis to study the socket-residual limb interaction. In this paper, we present a procedure for 3D automatic reconstruction of the residual starting from MRI images. The output is a 3D geometric model, in a neutral format (IGES), which permits CAD information exchange among the modules composing the design platform. The reconstruction procedure consists of three different phases: image pre-processing, voxel segmentation, 3D models generation. Results have been considered promising and future activities to enhance the algorithm performance have been planned.Pubblicazioni consigliate
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