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Abstract #3340

Non-rigid “image” registration in k-space

Thomas Küstner1,2,3, Christopher Gilliam4, Thierry Blu5, Martin Schwartz3,6, Gastao Cruz1, Jiazhen Pan3, Christian Würslin2, Nina F Schwenzer7, Holger Schmidt7, Bin Yang3, Konstantin Nikolaou8, René M Botnar1, Claudia Prieto1, and Sergios Gatidis2,8
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2Medical Image and Data Analysis (MIDAS), University Hospital Tübingen, Tübingen, Germany, 3Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany, 4RMIT University, Melbourne, Australia, 5Chinese University Hong Kong, Hong Kong, Hong Kong, 6Section on Experimental Radiology, University Hospital Tübingen, Tübingen, Germany, 7University of Tübingen, Tübingen, Germany, 8Department of Radiology, University Hospital Tübingen, Tübingen, Germany

Non-rigid motion estimation is an important task in correction of respiratory and cardiac motion. Usually this problem is formulated in image space via diffusion, parametric-spline or optical flow methods. For these applications non-rigid motion commonly needs to be estimated from cardiac or respiratory states which are highly subsampled in k-space. Image-based registration can be impaired by aliasing artefacts or by estimation from low-resolution images. In this work, we propose a novel non-rigid registration technique directly in k-space based on optical flow. The proposed method is compared against image-based registrations and tested on fully-sampled and highly-accelerated 3D motion-resolved MR imaging.

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