The study aims to perform a simple but effective integration of geometric information of segmented 3D bones' surface and density information provided by volume MRI (Magnetic Resonance Imaging). Such a representation method could support diagnosis process, biomedical simulation, computed assisted surgery and prosthesis fitting. The input consists of a volume MRI of a carpal district and the corresponding 3D surface model. The algorithm superimposes image and surface, and, once found the image voxel correspondent to each surface point, maps the grey level of the voxels identified on the segmented surface. The output is a surface mesh on which the texture, induced by the MRI, has been mapped. The approach is effective, general and applicable to different anatomical districts. Further elaboration of the results can be used to perform landmark identification or segmentation correction.

Mapping grey-levels on 3D segmented anatomical districts

Paccini M.;Spagnuolo M.
2019-01-01

Abstract

The study aims to perform a simple but effective integration of geometric information of segmented 3D bones' surface and density information provided by volume MRI (Magnetic Resonance Imaging). Such a representation method could support diagnosis process, biomedical simulation, computed assisted surgery and prosthesis fitting. The input consists of a volume MRI of a carpal district and the corresponding 3D surface model. The algorithm superimposes image and surface, and, once found the image voxel correspondent to each surface point, maps the grey level of the voxels identified on the segmented surface. The output is a surface mesh on which the texture, induced by the MRI, has been mapped. The approach is effective, general and applicable to different anatomical districts. Further elaboration of the results can be used to perform landmark identification or segmentation correction.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1030837
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