Evaluation of Active Contour-based Techniques toward Bone Segmentation from CT Images

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.

[1]  Anthony J. Yezzi,et al.  A geometric snake model for segmentation of medical imagery , 1997, IEEE Transactions on Medical Imaging.

[2]  Purang Abolmaesumi,et al.  An estimation/correction algorithm for detecting bone edges in CT images , 2005, IEEE Transactions on Medical Imaging.

[3]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[4]  V. Caselles,et al.  A geometric model for active contours in image processing , 1993 .

[5]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[6]  J. Sethian,et al.  Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .

[7]  S. Osher,et al.  Algorithms Based on Hamilton-Jacobi Formulations , 1988 .

[8]  Tony F. Chan,et al.  A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model , 2002, International Journal of Computer Vision.

[9]  Junaed Sattar.  Snakes , Shapes and Gradient Vector Flow , 2022 .

[10]  Randy E. Ellis,et al.  Validation of bone segmentation and improved 3-D registration using contour coherency in CT data , 2006, IEEE Transactions on Medical Imaging.

[11]  Baba C. Vemuri,et al.  Shape Modeling with Front Propagation: A Level Set Approach , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Guillermo Sapiro,et al.  Affine invariant scale-space , 1993, International Journal of Computer Vision.

[13]  Nikos Paragios,et al.  Gradient vector flow fast geometric active contours , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .