Topological segmentation of discrete surfaces
International Journal of Computer Vision
Journal of Mathematical Imaging and Vision - Special issue on mathematical imaging
Hierarchical Matching of Cortical Features for Deformable Brain Image Registration
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
Registration of Cortical Anatomical Structures via Robust 3D Point Matching
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
Automatic Recognition of Cortical Sulci Using a Congregation of Neural Networks
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Non-linear Cerebral Registration with Sulcal Constraints
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Entropy Minimization for Automatic Correction of Intensity Nonuniformity
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
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
Using Points and Surfaces to Improve Voxel-Based Non-rigid Registration
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Iconic feature based nonrigid registration: the PASHA algorithm
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Isotropic Energies, Filters and Splines for Vector Field Regularization
Journal of Mathematical Imaging and Vision
Joint Bayesian Cortical Sulci Recognition and Spatial Normalization
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Automatically learning cortical folding patterns
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Brain image registration using cortically constrained harmonic mappings
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Proceedings of the 29th DAGM conference on Pattern recognition
A robust hybrid method for nonrigid image registration
Pattern Recognition
Simultaneous geometric - iconic registration
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Incorporating rigid structures in non-rigid registration using triangular b-splines
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
Coordinate-based versus structural approaches to brain image analysis
Artificial Intelligence in Medicine
Balanced feature matching in probabilistic framework and its application on object localisation
International Journal of Computer Applications in Technology
International Journal of Computer Vision
Hi-index | 0.00 |
In this article we merge point feature and intensity-based registration in a single algorithm to tackle the problem of multiple brain registration. Because of the high variability of the shape of the cortex across individuals, there exist geometrical ambiguities in the registration process that an intensity measure alone is unable to solve. This problem can be tackled using anatomical knowledge. First, we automatically segment and label the whole set of the cortical sulci, with a non-parametric approach that enables the capture of their highly variable shape and topology. Then, we develop a registration energy that merges intensity and feature point matching. Its minimization leads to a linear combination of a dense smooth vector field and radial basis functions. We use and process differently the bottom line of the sulci from its upper border, whose localization is even more variable across individuals. We show that the additional sulcal energy improves the registration of the cortical sulci, while still keeping the transformation smooth and one-to-one.