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Joint Multimodal Segmentation of Clinical CT and MR from Hip Arthroplasty Patients

Ranzini, MBM; Ebner, M; Cardoso, MJ; Fotiadou, A; Vercauteren, T; Henckel, J; Hart, A; ... Modat, M; + view all (2018) Joint Multimodal Segmentation of Clinical CT and MR from Hip Arthroplasty Patients. In: Glocker, B and Yao, J and Vrtovec, T and Frangi, A and Zheng, G, (eds.) Computational Methods and Clinical Applications in Musculoskeletal Imaging: 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers. Springer: Cham, Switzerland. Green open access

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Abstract

Magnetic resonance imaging (MRI) is routinely employed to assess muscular response and presence of inflammatory reactions in patients treated with metal-on-metal hip arthroplasty, driving the decision for revision surgery. However, MRI is lacking contrast for bony structures and as a result orthopaedic surgical planning is mostly performed on computed tomography images. In this paper, we combine the complementary information of both modalities into a novel framework for the joint segmentation of healthy and pathological musculoskeletal structures as well as implants on all images. Our processing pipeline is fully automated and was designed to handle the highly anisotropic resolution of clinical MR images by means of super resolution reconstruction. The accuracy of the intra-subject multimodal registration was improved by employing a non-linear registration algorithm with hard constraints on the deformation of bony structures, while a multi-atlas segmentation propagation approach provided robustness to the large shape variability in the population. The suggested framework was evaluated in a leave-one-out cross-validation study on 20 hip sides. The proposed pipeline has potential for the extraction of clinically relevant imaging biomarkers for implant failure detection.

Type: Proceedings paper
Title: Joint Multimodal Segmentation of Clinical CT and MR from Hip Arthroplasty Patients
Event: MSKI: 5th International Workshop and Challenge on Computational Methods and Clinical Applications in Musculoskeletal Imaging
Location: Quebec City
Dates: 10 September 2017 - 10 September 2017
ISBN-13: 9783319741130
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-74113-0_7
Publisher version: https://doi.org/10.1007/978-3-319-74113-0_7
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.
Keywords: Muscoloskeletal imaging, Multimodal segmentation, Multimodal registration, CT, MR, Arthroplasty
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 Ortho and MSK Science
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 Chemical Engineering
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/10033909
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