A limited memory algorithm for bound constrained optimization
SIAM Journal on Scientific Computing
Injectivity conditions of 2D and 3D uniform cubic B-spline functions
Graphical Models - Pacific Graphics '99 in Graphical Models
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Weight Preserving Image Registration for Monitoring Disease Progression in Lung CT
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Semi-automatic Reference Standard Construction for Quantitative Evaluation of Lung CT Registration
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Evaluation of 4D-CT Lung Registration
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Tracking regional tissue volume and function change in lung using image registration
Journal of Biomedical Imaging - Special issue on Lung Imaging Data Analysis
Improving intensity-based lung CT registration accuracy utilizing vascular information
Journal of Biomedical Imaging - Special issue on Lung Imaging Data Analysis
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Image registration plays an important role within pulmonary image analysis. Accurate registration is critical to post-analysis of lung mechanical properties. To improve registration accuracy, we utilize the rich information of vessel locations and shapes, and introduce a new similarity criterion, sum of squared vesselness measure difference (SSVMD). This metric is added to three existing intensity-based similarity criteria for nonrigid lung CT image registration to show its ability in improving matching accuracy. The registration accuracy is assessed by landmark error calculation and distance map visualization on vascular tree. The average landmark errors are reduced by over 20% and are within 0.7 mm after adding SSVMD constraint to three existing intensity-based similarity metrics. Visual inspection shows matching accuracy improvements in the lung regions near the thoracic cage and near the diaphragm. Experiments also show this vesselness constraint makes the Jacobian map of transformations physiologically more plausible and reliable.