A composite registration framework for respiratory motion modelling from 4D MRI

4D MRI is current gaining attention as an imaging modality which is able to capture inter-cycle variability of respiratory motion. Such information is beneficial for example in radiotherapy planning and delivery. However the motion extracted from 4D MRI is dependant on the method of processing the images. Typically a deformable registration algorithm is used so that the 3D motion of every point in the image can be found. We have used several popular registration algorithms which have been recently published with publicly available data. Our findings suggest that due to the low contrast of 4D MRI, the registration is only accurate near clear boundaries, and less accurate elsewhere, to different degrees depending on the algorithm used. We thus suggest modelling organ deformation as an affine transformation, which is then embedded into the deformation field for more accurate modelling of respiratory motion.