Abstract
This study investigates a new parameterization of deformation fields for image registration. Instead of standard displacements, this parameterization describes a deformation field with its transformation Jacobian and curl of end velocity field. It has two important features which make it appealing to image registration: 1) it relaxes the need of an explicit regularization term and the corresponding ad hoc weight in the cost functional; 2) explicit constraints on transformation Jacobian such as topology preserving and incompressibility constraints are straightforward to impose in a unified framework. In addition, this parameterization naturally describes a deformation field in terms of radial and rotational components, making it especially suited for processing cardiac data. We formulate diffeomorphic image registration as a constrained optimization problem which we solve with a step-then-correct strategy. The effectiveness of the algorithm is demonstrated with several examples and a comprehensive evaluation of myocardial delineation over 120 short-axis cardiac cine MRIs acquired from 20 subjects. It shows competitive performance in comparison to two recent segmentation based approaches. © 2010 Springer-Verlag.
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CITATION STYLE
Chen, H. M., Goela, A., Garvin, G. J., & Li, S. (2010). A parameterization of deformation fields for diffeomorphic image registration and its application to myocardial delineation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6361 LNCS, pp. 340–348). https://doi.org/10.1007/978-3-642-15705-9_42
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