Deformable image registration is a key part of modern medical image processing and analysis. The aim of image registration is to align one image to another image. In this paper, three deformable image registration methods (NiftyReg, MRF-based and lreg) are compared based on their estimated motion field from 4D MRI data for respiratory motion modelling. The result shows that all of these methods are able to extract respiratory motion with different degrees of certainty. In terms of overall displacement for each organ, lreg with piecewise affine transformation produces more realistic motion than NiftyReg and MRF-Based registration. Finally, we can conclude that deformable image registration can be used to extract respiratory motion for applications such as integration into external beam radiotherapy treatment planning and delivery.
['Ehsan Golkar', 'Ashrani A. Abd. Rahni', 'Riza Sulaiman']
Comparison of intensity based deformable registration methods for respiratory motion modelling from 4D MRI