Probabilistic models are extensively used in medical image segmentation. Most of them employ parametric representations of densities and make idealizing assumptions, e.g. normal di...
In this note, we propose a method to perform segmentation on the tensor manifold, that is, the space of positive definite matrices of given dimension. In this work, we explicitly ...
Yogesh Rathi, Allen Tannenbaum, Oleg V. Michailovi...
We cast the problem of multiframe stereo reconstruction of a smooth shape as the global region segmentation of a collection of images of the scene. Dually, the problem of segmenti...
In this paper, we present a novel information theoretic approach to image segmentation. We cast the segmentation problem as the maximization of the mutual information between the ...
Alan S. Willsky, Anthony J. Yezzi Jr., John W. Fis...
In this paper, we propose a data-driven approach that extracts prior information for segmentation of the left ventricle in cardiac MR images of transplanted rat hearts. In our app...
Xiao Jia, Chao Li, Ying Sun, Ashraf A. Kassim, Yij...