TY - GEN
T1 - Unifying vascular information in intensity-based nonrigid lung CT registration
AU - Cao, Kunlin
AU - Ding, Kai
AU - Christensen, Gary E.
AU - Raghavan, Madhavan L.
AU - Amelon, Ryan E.
AU - Reinhardt, Joseph M.
PY - 2010/8/12
Y1 - 2010/8/12
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-642-14366-3_1
DO - 10.1007/978-3-642-14366-3_1
M3 - Conference contribution
AN - SCOPUS:77955327085
SN - 3642143652
SN - 9783642143656
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1
EP - 12
BT - Biomedical Image Registration - 4th International Workshop, WBIR 2010, Proceedings
T2 - 4th International Workshop on Biomedical Image Registration, WBIR 2010
Y2 - 11 July 2010 through 13 July 2010
ER -