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Accelerating the Registration of Image Sequences by Spatio-Temporal Multilevel Strategies

 
: Aggrawal, H.O.; Modersitzki, J.

:

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society:
IEEE 17th International Symposium on Biomedical Imaging, ISBI 2020. Symposium Proceedings : 3-7 April 2020, Iowa City, Iowa, USA
Piscataway, NJ: IEEE, 2020
ISBN: 978-1-5386-9330-8
ISBN: 978-1-5386-9331-5
S.683-686
International Symposium on Biomedical Imaging (ISBI) <17, 2020, Iowa City/Iowa>
Englisch
Konferenzbeitrag
Fraunhofer MEVIS ()

Abstract
Multilevel strategies are an integral part of many image registration algorithms. These strategies are very well-known for avoiding undesirable local minima, providing an outstanding initial guess, and reducing overall computation time. State-of-the-art multilevel strategies build a hierarchy of discretization in the spatial dimensions. In this paper, we present a spatio-temporal strategy, where we introduce a hierarchical discretization in the temporal dimension at each spatial level. This strategy is suitable for a motion estimation problem where the motion is assumed smooth over time. Our strategy exploits the temporal smoothness among image frames by following a predictor-corrector approach. The strategy predicts the motion by a novel interpolation method and later corrects it by registration. The prediction step provides a good initial guess for the correction step, hence reduces the overall computational time for registration. The acceleration is achieved by a factor of 2.5 on average, over the state-of-the-art multilevel methods on three examined optical coherence tomography datasets.

: http://publica.fraunhofer.de/dokumente/N-595986.html