Active shape models—their training and application
Computer Vision and Image Understanding
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
2D+T Acoustic Boundary Detection in Echocardiography
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
Tracking of LV endocardial surface on real-time three-dimensional ultrasound with optical flow
FIMH'05 Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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Deformable models have been widely used in image segmentation since the introduction of the snakes. Later the introduction of level set frameworks to solve the energy minimization problem associated with the deformable model overcame some limitations of the parametric active contours with respect to topological changes by embedding surface representations into higher dimensional functions. However, this may also bring in more computational load so that recent advances in spatio-temporal resolutions of 3D/4D imaging raised some challenges for real-time segmentation, especially for interventional imaging. In this context, a novel segmentation framework, Surface Function Actives (SFA), is proposed for real-time segmentation purpose. SFA has great advantages in terms of potential efficiency, based on its dimensionality reduction for the surface representation. Utilizing implicit representations with variational framework also provides flexibility and benefits currently shared by level set frameworks. An application for minimally-invasive intervention is shown to illustrate the potential applications of this framework.