General Object Reconstruction Based on Simplex Meshes
International Journal of Computer Vision
Subdivision Methods for Geometric Design: A Constructive Approach
Subdivision Methods for Geometric Design: A Constructive Approach
A geometric database for gene expression data
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Deformable M-Reps for 3D Medical Image Segmentation
International Journal of Computer Vision - Special Issue on Research at the University of North Carolina Medical Image Display Analysis Group (MIDAG)
Neuroinformatics for Genome-Wide 3-D Gene Expression Mapping in the Mouse Brain
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
DRAMMS: Deformable Registration via Attribute Matching and Mutual-Saliency Weighting
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Simultaneous geometric - iconic registration
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Landmark/image-based deformable registration of gene expression data
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Markov Random Field-based fitting of a subdivision-based geometric atlas
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Automated segmentation of multi-part anatomical objects in images is a challenging task. In this paper, we propose a similarity-based appearance-prior to fit a compartmental geometric atlas of the mouse brain in gene expression images. A subdivision mesh which is used to model the geometry is deformed using a Markov Random Field (MRF) framework. The proposed appearance-prior is computed as a function of the similarity between local patches at corresponding atlas locations from two images. In addition, we introduce a similarity-saliency score to select the mesh points that are relevant for the computation of the proposed prior. Our method significantly improves the accuracy of the atlas fitting, especially in the regions that are influenced by the selected similarity-salient points, and outperforms the previous subdivision mesh fitting methods for gene expression images.