Journal of Mathematical Imaging and Vision - Special issue on mathematical imaging
Graphical Models and Image Processing
International Journal of Computer Vision
IRMA: An Image Registration Meta-algorithm
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
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
Automated sulci identification via intrinsic modeling of cortical anatomy
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
A topology preserving level set method for geometric deformable models
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Real-Time Algorithm for the Approximation of Level-Set-Based Curve Evolution
IEEE Transactions on Image Processing
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Teichmüller Shape Descriptor and Its Application to Alzheimer's Disease Study
International Journal of Computer Vision
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In this paper we propose a novel system for the accurate reconstruction of cortical surfaces from magnetic resonance images. At the core of our system is a novel framework for outlier detection and pruning by integrating intrinsic Reeb analysis of Laplace-Beltrami eigenfunctions with topology-preserving evolution for localized filtering of outliers, which avoids unnecessary smoothing and shrinkage of cortical regions with high curvature. In our experiments, we compare our method with FreeSurfer and illustrate that our results can better capture cortical geometry in deep sulcal regions. To demonstrate the robustness of our method, we apply it to over 1300 scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI).We show that cross-sectional group differences and longitudinal changes can be detected successfully with our method.