Sciweavers

101
Voted
VISSYM
2007
15 years 2 months ago
Flexible And Topologically Localized Segmentation
One of the most common visualization tasks is the extraction of significant boundaries, often performed with isosurfaces or level set segmentation. Isosurface extraction is simple...
Gunnar Johansson, Ken Museth, Hamish Carr
99
Voted
ISBI
2006
IEEE
16 years 29 days ago
Homogeneity measures for multiphase level set segmentation of brain MRI
Elsa D. Angelini, Ting Song, Andrew Laine
112
Voted
IPMI
1999
Springer
16 years 1 months ago
Co-dimension 2 Geodesic Active Contours for MRA Segmentation
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...
96
Voted
MICCAI
2003
Springer
16 years 1 months ago
VETOT, Volume Estimation and Tracking Over Time: Framework and Validation
We have implemented an effective and publicly available tool, VETOT, to track and quantify the evolution of tumors and organs over time. VETOT includes a framework both for registr...
Jean-Philippe Guyon, Mark Foskey, Jisung Kim, Zeyn...
133
Voted
ECCV
2004
Springer
16 years 2 months ago
Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation
Abstract. We propose a variational framework for the integration multiple competing shape priors into level set based segmentation schemes. By optimizing an appropriate cost functi...
Daniel Cremers, Nir A. Sochen, Christoph Schnö...
113
Voted
CVPR
2006
IEEE
16 years 2 months ago
On Manifold Structure of Cardiac MRI Data: Application to Segmentation
We develop theory and algorithms to incorporate image manifold constraints in a level set segmentation algorithm. This provides a framework to simultaneously segment every image o...
Qilong Zhang, Richard Souvenir, Robert Pless
106
Voted
ICCV
2009
IEEE
16 years 5 months ago
Level Set Segmentation with Both Shape and Intensity Priors
We present a new variational level-set-based segmentation formulation that uses both shape and intensity prior information learned from a training set. By applying Bayes’ rule...
Siqi Chen and Richard J. Radke