Bayesian modeling of uncertainty in low-level vision
International Journal of Computer Vision
Closed-Form Solutions for Physically Based Shape Modeling and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active shape models—their training and application
Computer Vision and Image Understanding
Modal Matching for Correspondence and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Matching of Cortical Features for Deformable Brain Image Registration
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
Statistical Study on Cortical Sulci of Human Brains
IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
Labeling the Brain Surface Using a Deformable Multiresolution Mesh
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Extending Active Shape Models to Incorporate a-priori Knowledge about Structural Variability
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Spatial Priors for Part-Based Recognition Using Statistical Models
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Recovering Human Body Configurations Using Pairwise Constraints between Parts
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Statistical Multi-Object Shape Models
International Journal of Computer Vision
The Representation and Matching of Pictorial Structures
IEEE Transactions on Computers
Learning Local Objective Functions for Robust Face Model Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic feature localisation with constrained local models
Pattern Recognition
Multiple Tree Models for Occlusion and Spatial Constraints in Human Pose Estimation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Hierarchical Vibrations: A Structural Decomposition Approach for Image Analysis
EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Parcellation of the Auditory Cortex into Landmark---Related Regions of Interest
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
Surface/Volume-Based Articulated 3D Spine Inference through Markov Random Fields
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Constructing a Dictionary of Human Brain Folding Patterns
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Segmentation of Lumbar Vertebrae Using Part-Based Graphs and Active Appearance Models
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Brain image registration using cortically constrained harmonic mappings
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Geometry driven volumetric registration
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Flexible spatial models for grouping local image features
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
IEEE Transactions on Image Processing
Fast free-vibration modal analysis of 2-D physics-based deformable objects
IEEE Transactions on Image Processing
Hi-index | 0.01 |
We recently presented a method for the delineation of cortical regions of interest that relies on the finite element decomposition of shape [21]. Our current work strengthens and extends the proposed technique with the following contributions: First, we provide a detailed discussion of the computational challenges related to applying the hierarchical shape modelling and energy minimisation approach to the representation and segmentation of specific areas in cortical surfaces. Second, we analyse the underlying heuristics in order to elucidate the representational power and accuracy of the a priori constrained, partial model of the auditory cortex anatomy, and improve the cortical landmark localisation. We show experimentally that a valid parametric prior can be built from expert prior knowledge in a straightforward manner. By employing the advantages of the hierarchical shape decomposition, the model can be substantially improved on the basis of training sets, which are much smaller compared with state-of-the-art methods.