In this paper, we address the problem of constrained segmentation of natural images, in which a human user places one seed point inside each object of interest in the image and th...
In this paper, we describe a method for segmenting fiber bundles from diffusion-weighted magnetic resonance images using a locally-constrained region based approach. From a pre-co...
John Melonakos, Marc Niethammer, Vandana Mohan, Ma...
Configurations of dense locally parallel 3D curves occur in medical imaging, computer vision and graphics. Examples include white matter fibre tracts, textures, fur and hair. We d...
This paper proposes a method to match diffusion tensor magnetic resonance images (DT-MRI) through the large deformation diffeomorphic metric mapping of vector fields, focusing on ...
Yan Cao, Michael I. Miller, Raimond L. Winslow, La...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...