Segmentation of medical images is challenging due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Consequently, this task involves ...
Since the work by Osher and Sethian on level-sets algorithms for numerical shape evolutions, this technique has been used for a large number of applications in numerous fields. In...
Abstract. Automatic and semi-automatic magnetic resonance angiography (MRA) segmentation techniques can potentially save radiologists large amounts of time required for manual segm...
Liana M. Lorigo, Olivier D. Faugeras, W. Eric L. G...
The class of geometric deformable models, also known as level sets, has brought tremendous impact to medical imagery due to its capability of topology preservation and fast shape r...
Jasjit S. Suri, Kecheng Liu, Sameer Singh, Swamy L...
We propose a novel approach for improving level set seg-
mentation methods by embedding the potential functions
from a discriminatively trained conditional random field
(CRF) in...
Dana Cobzas (University of Alberta), Mark Schmidt ...