For biomechanical simulations, the segmentation of multiple adjacent anatomical structures from medical image data is often required. If adjacent structures are hardly distinguishable in image data, automatic segmentation methods for single structures in general do not yield sufficiently accurate results. To improve segmentation accuracy in these cases, knowledge about adjacent structures must be exploited. Optimal graph searching based on deformable surface models allows for a simultaneous segmentation of multiple adjacent objects. However, this method requires a correspondence relation between vertices of adjacent surface meshes. Line segments, each containing two corresponding vertices, may then serve as shared displacement directions in...
M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geom...
Image segmentation of 3D medical images is a challenging problem with several still not totally solv...
This PhD dissertation is focused on the development of algorithms for the automatic segmentation of ...
Statistical Shape Models have been proven to be valuable tools for segmenting anatomical structures ...
Statistical Shape Models have been proven to be valuable tools for segmenting anatomical structures ...
Medical images are challenging for segmentation. Deformable models proved to be one of the most effe...
The similarity of pixel intensities, presence of noise, existence of partial volume effect and so on...
Deformable models are widely used for image segmentation, most commonly to find single objects withi...
Abstract. A novel method for the segmentation of multiple objects from 3D medical images using inter...
UnrestrictedPeople have been studying shapes since the ancient times, using geometry to model those ...
This paper presents a new method for segmenting medical images by modeling interaction between neigh...
Deformable surface models are often represented as triangular meshes in image segmentation applicati...
Abstract During the past few years we have witnessed the development of many methodologies for buil...
Identifying multiple deformable parts on meshes and establishing dense correspondences between them ...
This thesis presents research work on deformable surface model for 3D object segmentation. Over the ...
M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geom...
Image segmentation of 3D medical images is a challenging problem with several still not totally solv...
This PhD dissertation is focused on the development of algorithms for the automatic segmentation of ...
Statistical Shape Models have been proven to be valuable tools for segmenting anatomical structures ...
Statistical Shape Models have been proven to be valuable tools for segmenting anatomical structures ...
Medical images are challenging for segmentation. Deformable models proved to be one of the most effe...
The similarity of pixel intensities, presence of noise, existence of partial volume effect and so on...
Deformable models are widely used for image segmentation, most commonly to find single objects withi...
Abstract. A novel method for the segmentation of multiple objects from 3D medical images using inter...
UnrestrictedPeople have been studying shapes since the ancient times, using geometry to model those ...
This paper presents a new method for segmenting medical images by modeling interaction between neigh...
Deformable surface models are often represented as triangular meshes in image segmentation applicati...
Abstract During the past few years we have witnessed the development of many methodologies for buil...
Identifying multiple deformable parts on meshes and establishing dense correspondences between them ...
This thesis presents research work on deformable surface model for 3D object segmentation. Over the ...
M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geom...
Image segmentation of 3D medical images is a challenging problem with several still not totally solv...
This PhD dissertation is focused on the development of algorithms for the automatic segmentation of ...