Flexible reconstruction and correction of unpredictable motion from stacks of 2D images

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Abstract

We present a method to correct motion in fetal in-utero scan sequences. The proposed approach avoids previously necessary manual segmentation of a region of interest. We solve the problem of non-rigid motion by splitting motion corrupted slices into overlapping patches of finite size. In these patches the assumption of rigid motion approximately holds and they can thus be used to perform a slice-to-volumebased (SVR) reconstruction during which their consistency with the other patches is learned. The learned information is used to reject patches that are not conform with the motion corrected reconstruction in their local areas. We evaluate rectangular and evenly distributed patches for the reconstruction as well as patches that have been derived from superpixels. Both approaches achieve on 29 subjects aged between 22–37 weeks a sufficient reconstruction quality and facilitate following 3D segmentation of fetal organs and the placenta.

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Kainz, B., Alansary, A., Malamateniou, C., Keraudren, K., Rutherford, M., Hajnal, J. V., & Rueckert, D. (2015). Flexible reconstruction and correction of unpredictable motion from stacks of 2D images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9350, pp. 555–562). Springer Verlag. https://doi.org/10.1007/978-3-319-24571-3_66

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