Optical flow based deformable volume registration using a novel second-order regularization prior. Grbić, S., Urschler, M., Pock, T., & Bischof, H. In Dawant, B., M. & Haynor, D., R., editors, Medical Imaging 2010: Image Processing, volume 7623, pages 76232R, 3, 2010. SPIE. ![Optical flow based deformable volume registration using a novel second-order regularization prior [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex Nonlinear image registration is an initial step for a large number of medical image analysis applications. Optical flow based intensity registration is often used for dealing with intra-modality applications involving motion differences. In this work we present an energy functional which uses a novel, second-order regularization prior of the displacement field. Compared to other methods our scheme is robust to non-Gaussian noise and does not penalize locally affine deformation fields in homogeneous areas. We propose an efficient and stable numerical scheme to find the minimizer of the presented energy. We implemented our algorithm using modern consumer graphics processing units and thereby increased the execution performance dramatically. We further show experimental evaluations on clinical CT thorax data sets at different breathing states and on dynamic 4D CT cardiac data sets. © 2010 Copyright SPIE - The International Society for Optical Engineering.
@inproceedings{
title = {Optical flow based deformable volume registration using a novel second-order regularization prior},
type = {inproceedings},
year = {2010},
pages = {76232R},
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abstract = {Nonlinear image registration is an initial step for a large number of medical image analysis applications. Optical flow based intensity registration is often used for dealing with intra-modality applications involving motion differences. In this work we present an energy functional which uses a novel, second-order regularization prior of the displacement field. Compared to other methods our scheme is robust to non-Gaussian noise and does not penalize locally affine deformation fields in homogeneous areas. We propose an efficient and stable numerical scheme to find the minimizer of the presented energy. We implemented our algorithm using modern consumer graphics processing units and thereby increased the execution performance dramatically. We further show experimental evaluations on clinical CT thorax data sets at different breathing states and on dynamic 4D CT cardiac data sets. © 2010 Copyright SPIE - The International Society for Optical Engineering.},
bibtype = {inproceedings},
author = {Grbić, Saša and Urschler, Martin and Pock, Thomas and Bischof, Horst},
editor = {Dawant, Benoit M. and Haynor, David R.},
doi = {10.1117/12.844549},
booktitle = {Medical Imaging 2010: Image Processing}
}
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