IEEE Transactions on Pattern Analysis and Machine Intelligence
Scattered Data Interpolation with Multilevel B-Splines
IEEE Transactions on Visualization and Computer Graphics
Non-parametric diffeomorphic image registration with the demons algorithm
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Fast free-form deformation using graphics processing units
Computer Methods and Programs in Biomedicine
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We propose a meta-algorithm for registration improvement by combining deformable image registrations (MetaReg). It is inspired by a well-established method from machine learning, the combination of classifiers. MetaReg consists of two main components: (1) A strategy for composing an improved registration by combining deformation fields from different registration algorithms. (2) A method for regularization of deformation fields post registration (UnfoldReg). In order to compare and combine different registrations, MetaReg utilizes a landmark-based classifier for assessment of local registration quality. We present preliminary results of MetaReg, evaluated on five CT pulmonary breathhold inspiration and expiration scan pairs, employing a set of three registration algorithms (NiftyReg, Demons, Elastix). MetaReg generated for each scan pair a registration that is better than any registration obtained by each registration algorithm separately. On average, 10% improvement is achieved, with a reduction of 30% of regions with misalignments larger than 5mm, compared to the best single registration algorithm.