Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Bernhard Kainz, Amir Alansary, Christina Malamateniou, Kevin Keraudren, Mary Rutherford, J. V. Hajnal, Daniel Rueckert
Original language | English |
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Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Publisher | Springer-Verlag Berlin Heidelberg |
Pages | 555-562 |
Number of pages | 8 |
Volume | 9350 |
ISBN (Print) | 9783319245706, 9783319245706, 9783319245706 |
DOIs | |
Published | 20 Nov 2015 |
Additional links | |
Event | 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany Duration: 5 Oct 2015 → 9 Oct 2015 |
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9350 |
ISSN (Print) | 03029743 |
ISSN (Electronic) | 16113349 |
Conference | 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 |
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Country/Territory | Germany |
City | Munich |
Period | 5/10/2015 → 9/10/2015 |
Kainz_MICCAI2015a.pdf, 3.6 MB, application/pdf
Uploaded date:24 Feb 2016
Version:Accepted author manuscript
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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