Landmark Matching via Large Deformation Diffeomorphisms on the Sphere
Journal of Mathematical Imaging and Vision
Automatic Landmark Tracking and its Application to the Optimization of Brain Conformal Mapping
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Optimization of brain conformal mapping with landmarks
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
3D Surface Matching and Registration through Shape Images
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Technical Section: Fourier method for large-scale surface modeling and registration
Computers and Graphics
3D shape context surface registration for cortical mapping
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Comparative analysis of quasi-conformal deformations in shape space
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Intra-patient supine-prone colon registration in CT colonography using shape spectrum
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Rigid and non-rigid shape matching for mechanical components retrieval
CISIM'12 Proceedings of the 11th IFIP TC 8 international conference on Computer Information Systems and Industrial Management
Robust shape correspondence via spherical patch matching for atlases of partial skull models
MeshMed'12 Proceedings of the 2012 international conference on Mesh Processing in Medical Image Analysis
Pose analysis using spectral geometry
The Visual Computer: International Journal of Computer Graphics
Group-wise cortical correspondence via sulcal curve-constrained entropy minimization
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
Equiareal parameterizations of NURBS surfaces
Graphical Models
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Accurate registration of cortical structures plays a fundamental role in statistical analysis of brain images across population. This paper presents a novel framework for the non-rigid intersubject brain surface registration, using conformal structure and spherical thin-plate splines. By resorting to the conformal structure, complete characteristics regarding the intrinsic cortical geometry can be retained as a mean curvature function and a conformal factor function defined on a canonical, spherical domain. In this transformed space, spherical thin-plate splines are firstly used to explicitly match a few prominent homologous landmarks, and in the meanwhile, interpolate a global deformation field. A post-optimization procedure is then employed to further refine the alignment of minor cortical features based on the geometric parameters preserved on the domain. Our experiments demonstrate that the proposed framework is highly competitive with others for brain surface registration and population-based statistical analysis. We have applied our method in the identification of cortical abnormalities in PET imaging of patients with neurological disorders and accurate results are obtained.