Unifying vascular information in intensity-based nonrigid lung CT registration
WBIR'10 Proceedings of the 4th international conference on Biomedical image registration
Early detection of emphysema progression
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Probabilistic elastography: estimating lung elasticity
IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
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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We present a new image registration based method for monitoring regional disease progression in longitudinal image studies of lung disease. A free-form image registration technique is used to match a baseline 3D CT lung scan onto a following scan. Areas with lower intensity in the following scan compared with intensities in the deformed baseline image indicate local loss of lung tissue that is associated with progression of emphysema. To account for differences in lung intensity owing to differences in the inspiration level in the two scans rather than disease progression, we propose to adjust the density of lung tissue with respect to local expansion or compression such that the total weight of the lungs is preserved during deformation. Our method provides a good estimation of regional destruction of lung tissue for subjects with a significant difference in inspiration level between CT scans and may result in a more sensitive measure of disease progression than standard quantitative CT measures.