Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
A Theoretical and Computational Framework for Isometry Invariant Recognition of Point Cloud Data
Foundations of Computational Mathematics
Particle-Based Shape Analysis of Multi-object Complexes
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Group-Wise Point-Set Registration Using a Novel CDF-Based Havrda-Charvát Divergence
International Journal of Computer Vision
Asymmetric Image-Template Registration
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Global medical shape analysis using the Laplace-Beltrami spectrum
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
International Journal of Computer Vision
IEEE Transactions on Image Processing
Synthesis of realistic subcortical anatomy with known surface deformations
MeshMed'12 Proceedings of the 2012 international conference on Mesh Processing in Medical Image Analysis
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We present a method that allows the detection, localization and quantification of statistically significant morphological differences in complex brain structures between populations. This is accomplished by a novel level-set framework for shape morphing and a multi-shape dissimilarity-measure derived by a modified version of the Hausdorff distance. The proposed method does not require explicit one-to-one point correspondences and is fast, robust and easy to implement regardless of the topological complexity of the anatomical surface under study. The proposed model has been applied to different populations using a variety of brain structures including left and right striatum, caudate, amygdala-hippocampal complex and superior- temporal gyrus (STG) in normal controls and patients. The synthetic databases allow quantitative evaluations of the proposed algorithm while the results obtained for the real clinical data are in line with published findings on gray matter reduction in the tested cortical and sub-cortical structures in schizophrenia patients.