BALUWALA ET AL.: NON-RIGID CHEST IMAGE REGISTRATION
Annals of the BMVA Vol. 2011, No. 4, pp 1−15 (2011)
© 2011. The copyright of this document resides with its authors.
It may be distributed unchanged freely in print or electronic forms.
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Abstract
Non-rigid image registration of chest CT images acquired at different breathing
stages is often necessary in today’s medical practice. Current algorithms take little
consideration of physical characteristics of the different tissues during the
registration process. In earlier work, we have presented a registration framework
based on the elastic transformation model that incorporated additional constraints
to preserve topology and rigid structures. In this paper, we extend our previous
registration framework to a viscous fluid model using the same constraints. A
comparison between the fluid and elastic registrations, with and without the
additional constraints, has been performed on 3D chest phantom data. The results
show that the fluid registration model using additional constraints is even more
successful in keeping the ribs and other bony structures rigid while reducing the
amount of folding in the deformation field, thus leading to better preservation of
topology.
1 Introduction
Medical image registration is defined as the process of determining the spatial
correspondence between two images. Non-rigid image registration plays an important
role in clinical applications ranging from early stage diagnosis of disease to therapy
planning and monitoring of treatment response or disease progression. Non-rigid
registration techniques use transformation models based on different principles such as
optical flow [Horn et al. (1981)], free form deformations [Rueckert et al. (1999)], radial
basis functions [Bookstein (1989)] or physical continuum models [Christensen et al. (1994),
Bajcsy et al. (1989)]. Image registration forms an important component of pulmonary