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Registration of Untracked 2D Laparoscopic Ultrasound to CT Images of the Liver using Multi-Labelled Content-Based Image Retrieval

Ramalhinho, J; Tregidgo, HFJ; Gurusamy, K; Hawkes, DJ; Davidson, B; Clarkson, MJ; (2020) Registration of Untracked 2D Laparoscopic Ultrasound to CT Images of the Liver using Multi-Labelled Content-Based Image Retrieval. IEEE Transactions on Medical Imaging 10.1109/TMI.2020.3045348. (In press). Green open access

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Abstract

Laparoscopic Ultrasound (LUS) is recommended as a standard-of-care when performing laparoscopic liver resections as it images sub-surface structures such as tumours and major vessels. Given that LUS probes are difficult to handle and some tumours are iso-echoic, registration of LUS images to a pre-operative CT has been proposed as an image-guidance method. This registration problem is particularly challenging due to the small field of view of LUS, and usually depends on both a manual initialisation and tracking to compose a volume, hindering clinical translation. In this paper, we extend a proposed registration approach using Content-Based Image Retrieval (CBIR), removing the requirement for tracking or manual initialisation. Pre-operatively, a set of possible LUS planes is simulated from CT and a descriptor generated for each image. Then, a Bayesian framework is employed to estimate the most likely sequence of CT simulations that matches a series of LUS images. We extend our CBIR formulation to use multiple labelled objects and constrain the registration by separating liver vessels into portal vein and hepatic vein branches. The value of this new labeled approach is demonstrated in retrospective data from 5 patients. Results show that, by including a series of 5 untracked images in time, a single LUS image can be registered with accuracies ranging from 5.7 to 16.4 mm with a success rate of 78%. Initialisation of the LUS to CT registration with the proposed framework could potentially enable the clinical translation of these image fusion techniques.

Type: Article
Title: Registration of Untracked 2D Laparoscopic Ultrasound to CT Images of the Liver using Multi-Labelled Content-Based Image Retrieval
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TMI.2020.3045348
Publisher version: https://doi.org/10.1109/TMI.2020.3045348
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 > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Surgical Biotechnology
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 Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10118248
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