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» An Adaptive Level Set Method for Medical Image Segmentation
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MICCAI
2005
Springer
15 years 10 months 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
15 years 11 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»
15 years 11 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 7 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
14 years 10 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