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Beyond the resolution limit: Diffusion parameter estimation in partial volume

Eaton-Rosen, Z; Melbourne, A; Jorge Cardoso, M; Marlow, N; Ourselin, S; (2016) Beyond the resolution limit: Diffusion parameter estimation in partial volume. In: Ourselin, S and Joskowicz, J and Sabuncu, MR and Unal, G and Wells, W, (eds.) Medical Image Computing and Computer-Assisted Intervention MICCAI 2016. (pp. pp. 605-612). Springer International Publishing AG Green open access

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Abstract

Diffusion MRI is a frequently-used imaging modality that can infer microstructural properties of tissue,down to the scale of microns. For single-compartment models,such as the diffusion tensor (DT),the model interpretation depends on voxels having homogeneous composition. This limitation makes it difficult to measure diffusion parameters for small structures such as the fornix in the brain,because of partial volume. In this work,we use a segmentation from a structural scan to calculate the tissue composition for each diffusion voxel. We model the measured diffusion signal as a linear combination of signals from each of the tissues present in the voxel,and fit parameters on a per-region basis by optimising over all diffusion data simultaneously. We test the proposed method by using diffusion data from the Human Connectome Project (HCP). We down sample the HCP data,and show that our method returns parameter estimates that are closer to the higher solution ground truths than for classical methods. We show that our method allows accurate estimation of diffusion parameters for regions with partial volume. Finally,we apply the method to compare diffusion in the fornix for adults born extremely preterm and matched controls.

Type: Proceedings paper
Title: Beyond the resolution limit: Diffusion parameter estimation in partial volume
Event: MICCAI 2016 - 19th International Conference on Medical Image Computing and Computer Assisted Intervention
Location: Athens, Greece
Dates: 17 October 2016 - 21 October 2016
ISBN-13: 9783319467252
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-46726-9_70
Publisher version: http://doi.org/10.1007/978-3-319-46726-9_70
Language: English
Additional information: Copyright © Springer International Publishing AG 2016. The final publication is available at Springer via http://doi.org/10.1007/978-3-319-46726-9_70.
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 Population Health Sciences > UCL EGA Institute for Womens Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health > Neonatology
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/1531903
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