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Active contours is a popular technique for image segmentation. However, active contour tend to converge to the closest local minimum of its energy function and often requires a close boundary initialization. We introduce a new approach that overcomes the close boundary initialization problem by reformulating the external energy term. We treat the active contour as a mean curve of the probability density...
Accurate definition of similarity measure is a key component in image registration. Most commonly used intensity-based similarity measures rely on the assumptions of independence and stationarity of the intensities from pixel to pixel. Such measures cannot capture the complex interactions among the pixel intensities, and often result in less satisfactory registration performances, especially in the...
The criterion for the correct spatial alignment is a key component in image registration. We formulate the registration problem as one that finds the spatial and intensity mappings of minimal complexity that make images exactly equal. We do not assume any parametric forms of these functions, and estimate them within variational calculus. We analytically solve for non-stationary intensity mapping,...
Tracking of speckles in echocardiography enables the study of myocardium deformation, and thus can provide insights about heart structure and function. Most of the current methods are based on 2D speckle tracking, which suffers from errors due to through-plane decorrelation. Speckle tracking in 3D overcomes such limitation. However, 3D speckle tracking is a challenging problem due to relatively low...
We introduce a novel probabilistic approach for non-parametric nonrigid image registration using generalized elastic nets, a model previously used for topographic maps. The idea of the algorithm is to adapt an elastic net (a constrained Gaussian mixture) in the spatial-intensity space of one image to fit the second image. The resulting net directly represents the correspondence between image pixels...
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