Legouhy, A;
Commowick, O;
Rousseau, F;
Barillot, C;
(2019)
Online atlasing using an iterative centroid.
In:
MICCAI: International Conference on Medical Image Computing and Computer-Assisted Intervention.
(pp. pp. 366-374).
Springer: Cham, Switzerland.
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Abstract
Online atlasing, i.e. incrementing an atlas with new images as they are acquired, is key when performing studies on databases very large or still being gathered. We propose to this end a new diffeomorphic online atlasing method without having to perform again the atlasing process from scratch. New subjects are integrated following an iterative procedure gradually shifting the centroid of the images to its final position, making it computationally cheap to update regularly an atlas as new images are acquired (only needing a number of registrations equal to the number of new subjects). We evaluate this iterative centroid approach through the analysis of the sharpness and variance of the resulting atlases, and the transformations of images, comparing their deviations from a conventional method. We demonstrate that the transformations divergence between the two approaches is small and stable and that both atlases reach equivalent levels of image quality.
Type: | Proceedings paper |
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Title: | Online atlasing using an iterative centroid |
Event: | MICCAI 2019: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 |
ISBN-13: | 978-3-030-32247-2 |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | https://doi.org/10.1007/978-3-030-32248-9_41 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10124112 |
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