Anatomy-Driven Brain Connectivity Mapping
Lead Research Organisation:
UNIVERSITY COLLEGE LONDON
Department Name: Computer Science
Abstract
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Organisations
Publications
Graham M
(2016)
Realistic simulation of artefacts in diffusion MRI for validating post-processing correction techniques
in NeuroImage
Batalle D
(2017)
Early development of structural networks and the impact of prematurity on brain connectivity
in NeuroImage
Alexander DC
(2017)
Image quality transfer and applications in diffusion MRI.
in NeuroImage
Bastiani M
(2017)
Improved tractography using asymmetric fibre orientation distributions
in NeuroImage
Slattery C
(2017)
ApoE influences regional white-matter axonal density loss in Alzheimer's disease
in Neurobiology of Aging
Ferizi U
(2017)
Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi-group comparison.
in NMR in biomedicine
Grussu F
(2017)
Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?
in Annals of Clinical and Translational Neurology
| Description | Two key findings so far: - Using non-symmetric fibre orientation patterns improves brain connectivity mapping via tractography. Within the grant we have developed a method for estimating non-symmetric fibre configurations from MRI data using neighbourhood information and shown that embedding these new objects within existing tractography algorithms resolves long-standing ambiguities in brain connectivity mapping. - Dispersion is often mistaken for crossing in diffusion MRI. Various studies suggest that fibre crossing configurations arise in a large proportion of MRI voxels in white matter of the brain. Within this grant we have challenges that view noting that more continuous patterns of fibre dispersion can appear as crossing although in fact should be considered separately. Experimental work reveals that many of the voxels previously identified as containing crossings in fact are more likely to contain dispersed fibre configurations. This influences the design of future tractography algorithms for brain connectivity mapping. |
| Exploitation Route | These findings prompt further development of tractography algorithms and the underlying models they use, both of which are evolving fast. |
| Sectors | Healthcare Pharmaceuticals and Medical Biotechnology |
| Description | EPSRC Centre for Doctoral Training in Intelligent, Integrated Imaging In Healthcare (i4health) |
| Amount | £6,034,274 (GBP) |
| Funding ID | EP/S021930/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2019 |
| End | 03/2028 |
| Description | Enabling clinical decisions from low-power MRI in developing nations through image quality transfer |
| Amount | £1,020,000 (GBP) |
| Funding ID | EP/R014019/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2018 |
| End | 01/2021 |
| Description | Image Quality Transfer |
| Amount | £60,000 (GBP) |
| Organisation | Microsoft Research |
| Sector | Private |
| Country | Global |
| Start | 09/2015 |
| End | 09/2018 |
| Description | Learning MRI and histology image mappings for cancer diagnosis and prognosis |
| Amount | £774,000 (GBP) |
| Funding ID | EP/R006032/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 12/2017 |
| End | 01/2020 |