Fully-Deformable 3D Image Registration in Two Seconds

Daniel Budelmann, Lars König, Nils Papenberg, Jan Lellmann


We present a highly parallel method for accurate and efficient variational deformable 3D image registration on a consumer-grade graphics processing unit (GPU). We build on recent matrix-free variational approaches and specialize the concepts to the massively-parallel manycore architecture provided by the GPU. Compared to a parallel and optimized CPU implementation, this allows us to achieve an average speedup of 32.53 on 986 real-world CT thorax-abdomen follow-up scans. At a resolution of approximately 256 3 voxels, the average runtime is 1.99 seconds for the full registration. On the publicly available DIR-lab benchmark, our method ranks third with respect to average landmark error at an average runtime of 0.32 seconds.

Original languageEnglish
Title of host publicationBildverarbeitung für die Medizin 2019
Number of pages6
PublisherSpringer Berlin Heidelberg
Publication date07.02.2019
ISBN (Print)978-3-658-25325-7
ISBN (Electronic)978-3-658-25326-4
Publication statusPublished - 07.02.2019
EventWorkshop on Bildverarbeitung fur die Medizin 2019 - Lübeck, Germany
Duration: 17.03.201919.03.2019
Conference number: 224899


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