3D Knowledge-based Segmentation Using Sparse Hierarchical Models : contribution and Applications in Medical Imaging
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Summary
The methodological focus of the thesis is to devise methods for the consistent localization of positions in the anatomy and the navigation within the muscle data across patients, and to extend the shape representation of 3D structures using diffusion wavelets.
- Type
- dissertation
- Published
- 2010-05-12
- Cited by
- 0
- References
- 164
- Access
- Open access
- OpenAlex
- https://openalex.org/W103338145
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:62381502
Keywords
Segmentation, Computer science, Artificial intelligence, Pattern recognition (psychology), Representation (politics)
References
- A simplified method to measure the diffusion tensor from seven MR images
- Diffusion kernels on graphs and other discrete structures
- Snakes, shapes, and gradient vector flow
- Procrustes methods in the statistical analysis of shape
- Learning Shape: Optimal Models for Analysing Natural Variability
- Special Invited Paper-Additive logistic regression: A statistical view of boosting
- Decision Forests with Long-Range Spatial Context for Organ Localization in CT Volumes
- Skeletal Muscle Plasticity in Health and Disease
- Improving Appearance Model Matching Using Local Image Structure
- Local Appearance Knowledge and Shape Variation Models for Muscle Segmentation
- Localized Shape Variations for Classifying Wall Motion in Echocardiograms
- Efficient Kernel Density Estimation of Shape and Intensity Priors for Level Set Segmentation
- Clustering of the Human Skeletal Muscle Fibers Using Linear Programming and Angular Hilbertian Metrics
- 3D Knowledge-Based Segmentation Using Pose-Invariant Higher-Order Graphs
- Anatomical Modelling of the Musculoskeletal System from MRI
- Deformable M-Reps for 3D Medical Image Segmentation
- Liver Segmentation Using Sparse 3D Prior Models with Optimal Data Support
- Morphometric tools for landmark data: Contents
- Robust Active Shape Models: A Robust, Generic and Simple Automatic Segmentation Tool
- Spectral Graph Theory
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