%0 Conference Paper %1 6556539 %A Ruhaak, J. %A Konig, L. %A Hallmann, M. %A Papenberg, N. %A Heldmann, S. %A Schumacher, H. %A Fischer, B. %B Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on %D 2013 %K evolutionary gradient masterbib multimodal niching %P 572-575 %R 10.1109/ISBI.2013.6556539 %T A fully parallel algorithm for multimodal image registration using normalized gradient fields %U http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6556539&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6556539 %X We present a super fast variational algorithm for the challenging problem of multimodal image registration. It is capable of registering full-body CT and PET images in about a second on a standard CPU with virtually no memory requirements. The algorithm is founded on a Gauss-Newton optimization scheme with specifically tailored, mathematically optimized computations for objective function and derivatives. It is fully parallelized and perfectly scalable, thus directly suitable for usage in many-core environments. The accuracy of our method was tested on 21 PET-CT scan pairs from clinical routine. The method was able to correct random distortions in the range from -10 cm to 10 cm translation and from -15° to 15° degree rotation to subvoxel accuracy. In addition, it exhibits excellent robustness to noise.

@inproceedings{6556539, abstract = {We present a super fast variational algorithm for the challenging problem of multimodal image registration. It is capable of registering full-body CT and PET images in about a second on a standard CPU with virtually no memory requirements. The algorithm is founded on a Gauss-Newton optimization scheme with specifically tailored, mathematically optimized computations for objective function and derivatives. It is fully parallelized and perfectly scalable, thus directly suitable for usage in many-core environments. The accuracy of our method was tested on 21 PET-CT scan pairs from clinical routine. The method was able to correct random distortions in the range from -10 cm to 10 cm translation and from -15° to 15° degree rotation to subvoxel accuracy. In addition, it exhibits excellent robustness to noise.}, added-at = {2014-06-23T20:17:09.000+0200}, author = {Ruhaak, J. and Konig, L. and Hallmann, M. and Papenberg, N. and Heldmann, S. and Schumacher, H. and Fischer, B.}, biburl = {https://www.bibsonomy.org/bibtex/2f2deec627d62546f575ca7432f893f67/marcioweck}, booktitle = {Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on}, doi = {10.1109/ISBI.2013.6556539}, interhash = {412893da9c4dd1b94d991e6c31afe850}, intrahash = {f2deec627d62546f575ca7432f893f67}, issn = {1945-7928}, keywords = {evolutionary gradient masterbib multimodal niching}, month = {April}, pages = {572-575}, timestamp = {2014-06-23T20:17:09.000+0200}, title = {A fully parallel algorithm for multimodal image registration using normalized gradient fields}, url = {http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6556539&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6556539}, year = 2013 }