Weight preserving image registration for monitoring disease progression in lung CT.
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.
Gorbunova
Vladlena
V
Department of Computer Science, University of Copenhagen, Denmark.
Lol
Pechin
P
Ashraf
Haseem
H
Dirksen
Asger
A
Nielsen
Mads
M
de Bruijne
Marleen
M
D000465:Algorithms; D001185:Artificial Intelligence; D018450:Disease Progression; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D029424:Pulmonary Disease, Chronic Obstructive / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*