Tregidgo, Henry;
Soskic, Sonja;
Ochanyi, Mark D;
Althonayan, Juri;
Billot, Benjamin;
Maffei, Chiara;
Golland, Polina;
... Iglesias, Juan Eugenio; + view all
(2023)
Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023.
Springer: Cham, Switzerland.
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Abstract
The human thalamus is a subcortical brain structure that comprises dozens of nuclei with different function and connectivity, which are affected differently by disease. For this reason, there is growing interest in studying the thalamic nuclei in vivo with MRI. Tools are available to segment the thalamus from 1 mm T1 scans, but the image contrast is too faint to produce reliable segmentations. Some tools have attempted to refine these boundaries using diffusion MRI information, but do not generalise well across diffusion MRI acquisitions. Here we present the first CNN that can segment thalamic nuclei from T1 and diffusion data of any resolution without retraining or fine tuning. Our method builds on our histological atlas of the thalamic nuclei and silver standard segmentations on high-quality diffusion data obtained with our recent Bayesian adaptive segmentation tool. We combine these with an approximate degradation model for fast domain randomisation during training. Our CNN produces a segmentation at 0.7 mm isotropic resolution, irrespective of the resolution of the input. Moreover, it uses a parsimonious model of the diffusion signal (fractional anisotropy and principal eigenvector) that is compatible with virtually any set of directions and b-values, including huge amounts of legacy data. We show results of our proposed method on three heterogeneous datasets acquired on dozens of different scanners. The method is publicly available at freesurfer.net/fswiki/ThalamicNucleiDTI.
| Type: | Proceedings paper |
|---|---|
| Title: | Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI |
| Event: | MICCAI 2023 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-031-43993-3_24 |
| Publisher version: | https://doi.org/10.1007/978-3-031-43993-3_24 |
| 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 > 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-pp.ucl.ac.uk/id/eprint/10179302 |
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