Multi-modal and Multi-temporal Image Registration in the Presence of Gross Outliers Using Feature Voxel-Weighted Normalized Mutual Information

@article{Gu2006MultimodalAM,
  title={Multi-modal and Multi-temporal Image Registration in the Presence of Gross Outliers Using Feature Voxel-Weighted Normalized Mutual Information},
  author={ZhiJun Gu and Binjie Qin},
  journal={2006 IEEE Nuclear Science Symposium Conference Record},
  year={2006},
  volume={6},
  pages={3209-3212}
}
A novel automatic registration algorithm based on new similarity measure called Feature Voxel-Weighted Normalized Mutual Information (FVW-NMI) is presented for accurate and robust multi-modal and multi-temporal image registration in the presence of gross outliers. Based on assumption of corresponding voxels having some common similar spatial information between multi-modal and multi-temporal images, feature measure maps for both floating and reference images are computed to estimate a… CONTINUE READING