3D video-fluoroscopy can accurately estimate in-vivo kinematics of joint prosthesis. To this aim, for each of the hundreds of frames of an acquisition, a 3D surface model of the prosthesis is registered to the relevant contours on the 2D X-ray projections. Commercial software only provide simple edge detector followed by a time consuming manual procedure to delete the undesired contours. A fast and robust semi-automated prosthesis segmentation method, combining region growing and level set methods, is proposed to speed up the analysis and to reduce the human interaction.

Tersi L., Tarroni G., Corsi C., Stagni R. (2010). Automatic prosthesis segmentation in 3D fluoroscopy. SCICLI (RG) : s.n.

Automatic prosthesis segmentation in 3D fluoroscopy

TERSI, LUCA;TARRONI, GIACOMO;CORSI, CRISTIANA;STAGNI, RITA
2010

Abstract

3D video-fluoroscopy can accurately estimate in-vivo kinematics of joint prosthesis. To this aim, for each of the hundreds of frames of an acquisition, a 3D surface model of the prosthesis is registered to the relevant contours on the 2D X-ray projections. Commercial software only provide simple edge detector followed by a time consuming manual procedure to delete the undesired contours. A fast and robust semi-automated prosthesis segmentation method, combining region growing and level set methods, is proposed to speed up the analysis and to reduce the human interaction.
2010
Proceedings ICVSS 2010
1
1
Tersi L., Tarroni G., Corsi C., Stagni R. (2010). Automatic prosthesis segmentation in 3D fluoroscopy. SCICLI (RG) : s.n.
Tersi L.; Tarroni G.; Corsi C.; Stagni R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/114090
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