International Journal of Computer Vision
2D+T Acoustic Boundary Detection in Echocardiography
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Segmentation of Echocardiographic Image Sequences Using Spatio-temporal Information
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
On the Incorporation of shape priors into geometric active contours
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
IEEE Transactions on Image Processing
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In the automatic segmentation of echocardiographic images, a priori shape knowledge is used to compensate poor features in ultrasound images. The shape knowledge is often learned via off-line training process, which requires tedious human effort and is unavoidably expertise-dependent. More importantly, a learned shape template can only be used to segment a specific class of images with similar boundary shapes.In this paper, we present a multi-scale level set framework for echo image segmentation. We extract echo image boundaries automatically at a very coarse scale. These boundaries are then not only used as boundary initials at finer scales, but also as an external constraint to guide contour evolutions. This constraint functions similar to a traditional shape prior. Experimental results validate this combinative framework.