UCL  IRIS
Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at http://www.ucl.ac.uk/finance/research/post_award/post_award_contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
A Combined EM and Visual Tracking Probabilistic Model for Robust Mosaicking: Application to Fetoscopy.
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.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers Show More
Author
Dept of Med Phys & Biomedical Eng
Author
Dept of Med Phys & Biomedical Eng
Author
Dept of Med Phys & Biomedical Eng
Author
Dept of Computer Science
Author
Dept of Med Phys & Biomedical Eng
Author
Dept of Med Phys & Biomedical Eng
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by