Abstract
Automatic bone segmentation of Computed Tomography (CT) images is an important step in imageguided surgery where segmentation errors could be critical. Previous attempts include intensity-, edge-, region-, and deformable curve-based approaches [1], but none claims fully satisfactory performance. In this study, we have tested most widely used active contour (AC) -based approaches to segment knee bones from CT imagery, namely the Gradient Vector Flow (GVF) AC, the original geometric AC, the geodesic AC, the GVF fast geometric AC, and the Chan-Vese multiphase AC without edges. Among the techniques, only the Chan-Vese multiphase AC demonstrated satisfactory performance, proving its suitability for bone segmentation from CT images.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
