Multisubject non-rigid registration of Brain MRI using intensity and geometric features

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2208, Issue , 2001, Pages 734-742

  Cachier, Pascal ^a   Mangin, Jean François ^b   Pennec, Xavier ^a   Rivière, Denis ^b   Papadopoulos Orfanos, Dimitri ^b   Régis, Jean ^c   Ayache, Nicholas ^a  

^a INRIA   (France)

^b DIF   (France)

^c TIMONE HOSPITAL   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; IMAGE MATCHING; MAGNETIC RESONANCE IMAGING; MEDICAL COMPUTING; RADIAL BASIS FUNCTION NETWORKS;

FEATURE POINT MATCHING; GEOMETRIC FEATURE; INTENSITY-BASED REGISTRATION; LINEAR COMBINATIONS; NONPARAMETRIC APPROACHES; NONRIGID REGISTRATION; RADIAL BASIS FUNCTIONS; REGISTRATION PROCESS;

MEDICAL IMAGING;

EID: 84948753649     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45468-3_88     Document Type: Conference Paper

References (15)

1. P. Cachier and N. Ayache. Regularization in Image Non-Rigid Registration: I. Trade-Off between Smoothness and Similarity. Technical report, INRIA, 2001.
2. H. Chui, J. Rambo, J. Duncan, R. Schultz, and A. Rangarajan. Registration of Cortical Anatomical Structures via Robust 3D Point Matching. In Proc. of IPMI’99, number 1613 in LNCS, pages 168–181, Visegrád, Hungary, June 1999.
3. D. L. Collins, G. Le Goualher, and A. C. Evans. Non-Linear Cerebral Registration with Sulcal Constraints. In Proc. of MICCAI’98, volume 1496 of LNCS, pages 974–984, Cambridge, USA, October 1998. Springer.
4. P. Hellier and C. Barillot. Coupling Dense and Landmark-Based approaches for Non Rigid Registration. Technical Report 1368, IRISA, November 2000.
5. G. Lohmann and D. Y. von Cramon. Automatic Labelling of the Human Cortical Surface using Sulcal Basins. Medical Image Analysis, 4(3):179–188, 2000.
6. G. Malandain, G. Bertrand, and N. Ayache. Topological Segmentation of Discrete Surfaces. Int. J. of Comp. Vision, 10(2):158–183, 1993.
7. J.-F. Mangin. Entropymi nimization for automatic correction of intensityno nuniformity. In Proc. of MMBIA’00, pages 162–169, 2000.
8. J.-F. Mangin, V. Frouin, I. Bloch, J. Regis, and J. López-Krahe. From 3D MR images to structural representations of the cortex topographyu sing topology preserving deformations. J. of Math. Imaging and Vision, 5(4):297–318, 1995.
9. J. Régis, J.-F. Mangin, V. Frouin, F. Sastre, J. C. Peragut, and Y. Samson. Generic Model for the Localization of the Cerebral Cortex and Preoperative Multimodal Integration in Epilepsy Surgery. Stereotactic Functional Neurosurgery, 65:72–80, 1995.
10. D. Rivière, J.-F. Mangin, D. Papadopoulos, J.-M. Martinez, V. Frouin, and J. Régis. Automatic Recognition of Cortical Sulci using a Congregation of Neural Networks. In Proc. of MICCAI’00, volume 1935 of LNCS, pages 40–49, Pittsburgh, USA, October 2000. Springer.
11. A. Roche, G. Malandain, and N. Ayache. Unifying Maximum Likelihood Approaches in Medical Image Registration. Int. J. of Imaging Systems and Technology, 11:71–80, 2000.
12. P. Thompson and A. W. Toga. A Surface-Based Technique for Warping 3-Dimensional Images of the Brain. IEEE Trans. on Medical Imaging, 15(4):402–417, 1996.
13. M. Vaillant and C. Davatzikos. Hierarchical Matching of Cortical Features for Deformable Brain Image Registration. In Proc. of IPMI’99, volume 1613 of LNCS, pages 182–195, Visegrád, Hungary, June/July 1999. Springer.
14. J. D. G. Watson, R. Myers, and R. Frackowiak et al. Area (V5) of the human cortex: evidence from a combined studyu sing positron emission tomographyan d magnetic resonnance imaging. Cerebral Cortex, 3:79–94, 1993.
15. W. Welker. Whyd oes the cerebral cortex fissure and fold. Cerebral Cortex, 8B:3–135, 1989.