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Smith, G., Stoyanov, Z., Vukadinovic Greetham, D., Grindrod, P. and Saddy, D. 
ORCID: https://orcid.org/0000-0001-8501-6076
(2014)
Towards the computer-aided diagnosis of dementia based on the geometric and network connectivity of structural MRI data.
In: CADDementia workshop, Medical Image Computing and Computer Assisted Intervention (MICCAI) 2014 conference, 14-18 Sep 2014, Boston.
Abstract/Summary
We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.
| Item Type | Conference or Workshop Item (Paper) |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/37130 |
| Item Type | Conference or Workshop Item |
| Refereed | Yes |
| Divisions | Interdisciplinary Research Centres (IDRCs) > Centre for Integrative Neuroscience and Neurodynamics (CINN) Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Centre for the Mathematics of Human Behaviour (CMOHB) |
| Uncontrolled Keywords | MRI, dementia, mild cognitive impairment, voxel, auto- matic, diagnosis, graph Laplacian, Network Theory |
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