Tella Amo, M;
Daga, P;
Chadebecq, F;
Thompson, S;
Shakir, D;
Dwyer, G;
Wimalasundera, R;
... Ourselin, S; + view all
(2016)
A Combined EM and Visual Tracking Probabilistic Model for Robust Mosaicking: Application to Fetoscopy.
In:
Proceedings of the 7th International Workshop on Biomedical Image Registration.
(pp. pp. 524-532).
IEEE: Las Vegas, NV, USA.
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Abstract
Twin-to-Twin Transfusion Syndrome (TTTS) is a progressive pregnancy complication in which inter-twin vascular connections in the shared placenta result in a blood flow imbalance between the twins. The most effective therapy is to sever these connections by laser photo-coagulation. However, the limited field of view of the fetoscope hinders their identification. A potential solution is to augment the surgeon’s view by creating a mosaic image of the placenta. State-of-the-art mosaicking methods use feature-based ap- proaches, which have three main limitations: (i) they are not robust against corrupt data e.g. blurred frames, (ii) tem- poral information is not used, (iii) the resulting mosaic suf- fers from drift. We introduce a probabilistic temporal model that incorporates electromagnetic and visual tracking data to achieve a robust mosaic with reduced drift. By assuming planarity of the imaged object, the nRT decomposition can be used to parametrize the state vector. Finally, we tackle the non-linear nature of the problem in a numerically stable manner by using the Square Root Unscented Kalman Filter. We show an improvement in performance in terms of robustness as well as a reduction of the drift in comparison to state-of-the-art methods in synthetic, phantom and ex vivo datasets.
| Type: | Proceedings paper |
|---|---|
| Title: | A Combined EM and Visual Tracking Probabilistic Model for Robust Mosaicking: Application to Fetoscopy |
| Event: | WBIR 2016 |
| Location: | Las Vegas, Nevada, USA |
| Dates: | 26 June 2016 - 01 July 2016 |
| ISBN: | 9781509014378 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/CVPRW.2016.72 |
| Publisher version: | http://wbir2016.doc.ic.ac.uk/program/ |
| Language: | English |
| Additional information: | Copyright © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Keywords: | Mosaicing, kalman filter, unscented transform, square root unscented kalman filter, TTTS |
| 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 UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1495954 |
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