In this paper, a novel deformable model is proposed for robust segmentation in the presence of weak/misleading appearance cues. Owing to the less trustable ...
We use deformable models and shape prior. Shape representation is based on landmarks. Chest X-ray. Lung CAD. Liver in low-dose whole- ...
This scheme facilitates a more compact shape prior modeling and hence a more robust and efficient segmentation. Our deformable model is applied on two very.
SSC is robust to non-Gaussian errors and still preserves individual shape characteristics even when such characteristics is not statistically significant.
In this paper, we design two strategies to decrease the computational complexity of SSC, making a robust, accurate and efficient deformable segmentation system.
In this paper, a novel deformable model is proposed for robust segmentation in the presence of weak/misleading appearance cues. Owing to the less trustable ...
This paper proposes to transfer shape modeling learned from an existing but different dataset to assist cell segmentation in a new target dataset without ...
Aug 23, 2012 · In both scenar- ios, Sparse Shape Composition needs to solve a large scale sparse optimization problem, which has high computational complexity.
Organ shape plays an important role in various clinical practices such as segmentation. Effective modeling of shape priors is challenging because: (1) shape ...
This scheme facilitates a more compact shape prior modeling and hence a more robust and efficient segmentation. Our deformable model is applied on two very.