Active shape models—their training and application
Computer Vision and Image Understanding
An Adaptive-Focus Deformable Model Using Statistical and Geometric Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 4th international conference on Computer graphics and interactive techniques in Australasia and Southeast Asia
Diffeomorphic statistical shape models
Image and Vision Computing
Repairing and meshing imperfect shapes with Delaunay refinement
2009 SIAM/ACM Joint Conference on Geometric and Physical Modeling
Quality meshing of implicit solvation models of biomolecular structures
Computer Aided Geometric Design - Special issue: Applications of geometric modeling in the life sciences
Spatiotemporal Atlas Estimation for Developmental Delay Detection in Longitudinal Datasets
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
On the Manifold Structure of the Space of Brain Images
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Computer Methods and Programs in Biomedicine
Construction of neuroanatomical shape complex atlas from 3D brain MRI
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
4D cardiac reconstruction using high resolution CT images
FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
Learning an atlas of a cognitive process in its functional geometry
IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
3D anatomical shape atlas construction using mesh quality preserved deformable models
Computer Vision and Image Understanding
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The construction of 3D anatomical shape atlas has been extensively studied in medical image analysis research for a variety of applications. Among the multiple steps of shape atlas construction, establishing anatomical correspondences across subjects is probably the most critical and challenging one. The adaptive focus deformable model (AFDM) [16] was proposed to tackle this problem by exploiting cross-scale geometry characteristics of 3D anatomy surfaces. Although the effectiveness of AFDM has been proved in various studies, its performance is highly dependent on the quality of 3D surface meshes. In this paper, we propose a new framework for 3D anatomical shape atlas construction. Our method aims to robustly establish correspondences across different subjects and simultaneously generate high-quality surface meshes without removing shape detail. Mathematically, a new energy term is embedded into the original energy function of AFDM to preserve surface mesh qualities during the deformable surface matching. Shape details and smoothness constraints are encoded into the new energy term using the Laplacian representation An expectation-maximization style algorithm is designed to optimize multiple energy terms alternatively until convergence. We demonstrate the performance of our method via two diverse applications: 3D high resolution CT cardiac images and rat brain MRIs with multiple structures.