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» An Adaptive Level Set Method for Medical Image Segmentation
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MICCAI
2005
Springer
16 years 23 days ago
MR Diffusion-Based Inference of a Fiber Bundle Model from a Population of Subjects
This paper proposes a method to infer a high level model of the white matter organization from a population of subjects using MR diffusion imaging. This method takes as input for e...
Vincent El Kouby, Yann Cointepas, Cyril Poupon, De...
CVPR
2008
IEEE
16 years 1 months ago
A statistical deformation prior for non-rigid image and shape registration
Non-rigid registration is central to many problems in computer vision and medical image analysis. We propose a registration algorithm which is regularized by prior knowledge in th...
Marcel Lüthi, Thomas Albrecht, Thomas Vetter
CVPR
1999
IEEE
1104views Computer Vision» more  CVPR 1999»
16 years 1 months ago
Geodesic Active Contours for Supervised Texture Segmentation
This paper presents a variational method for supervised texture segmentation, which is based on ideas coming from the curve propagation theory. We assume that a preferable texture...
Nikos Paragios, Rachid Deriche
FIMH
2009
Springer
14 years 9 months ago
Discriminative Joint Context for Automatic Landmark Set Detection from a Single Cardiac MR Long Axis Slice
Cardiac magnetic resonance (MR) imaging has advanced to become a powerful diagnostic tool in clinical practice. Automatic detection of anatomic landmarks from MR images is importan...
Xiaoguang Lu, Bogdan Georgescu, Arne Littmann, Edg...
DAGM
2010
Springer
15 years 1 months ago
Local Regression Based Statistical Model Fitting
Fitting statistical models is a widely employed technique for the segmentation of medical images. While this approach gives impressive results for simple structures, shape models a...
Matthias Amberg, Marcel Lüthi, Thomas Vetter