Shape Analysis of Brain Ventricles Using SPHARM
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Tightening: curvature-limiting morphological simplification
Proceedings of the 2005 ACM symposium on Solid and physical modeling
Shape modeling and analysis with entropy-based particle systems
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Image registration driven by combined probabilistic and geometric descriptors
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Estimation of smooth growth trajectories with controlled acceleration from time series shape data
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Efficient probabilistic and geometric anatomical mapping using particle mesh approximation on GPUs
Journal of Biomedical Imaging - Special issue on Parallel Computation in Medical Imaging Applications
Mixed-Effects shape models for estimating longitudinal changes in anatomy
STIA'12 Proceedings of the Second international conference on Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data
Geodesic shape regression in the framework of currents
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
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Shape regression promises to be an important tool to study the relationship between anatomy and underlying clinical or biological parameters, such as age. In this paper we propose a new method to building shape models that incorporates regression analysis in the process of optimizing correspondences on a set of open surfaces. The statistical significance of the dependence is evaluated using permutation tests designed to estimate the likelihood of achieving the observed statistics under numerous rearrangements of the shape parameters with respect to the explanatory variable. We demonstrate the method on synthetic data and provide a new results on clinical MRI data related to early development of the human head.