Phase Based Volume Registration Using CUDA
2010 (English)In: Acoustics Speech and Signal Processing (ICASSP), 2010, IEEE , 2010, 658-661 p.Conference paper (Refereed)
We present a method for fast phase based registration of volume data for medical applications. As the number of different modalities within medical imaging increases, it becomes more and more important with registration that works for a mixture of modalities. For these applications the phase based registration approach has proven to be superior. Today there seem to be two kinds of groups that work with medical image registration, one that works with refining of the registration algorithms and one that works with implementation of more simple algorithms on graphic cards for speeding up the algorithms. We put the work from these groups together and get the best from both worlds. We achieve a speedup of 10-30 compared to our CPU implementation, which makes fast phase based registration possible for large medical volumes.
Place, publisher, year, edition, pages
IEEE , 2010. 658-661 p.
, IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings, ISSN 1520-6149 ; 2010
Image registration, local phase, CUDA, GPU
National CategoryEngineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-54035DOI: 10.1109/ICASSP.2010.5495134ISI: 000287096000159ISBN: 978-1-4244-4295-9OAI: oai:DiVA.org:liu-54035DiVA: diva2:297927
The 35th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), March 14–19, Dallas, Texas, USA
©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Anders Eklund, Mats Andersson and Hans Knutsson, Phase Based Volume Registration Using CUDA, 2010, Proceedings of the 35th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), 658-661. http://dx.doi.org/10.1109/ICASSP.2010.54951342010-02-192010-02-192013-08-28Bibliographically approved