Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI. Zach Eaton-Rosen, Andrew Melbourne, Eliza Orasanu, M. Jorge Cardoso, Marc Modat, Alan Bainbridge, Giles S. Kendall, Nicola J. Robertson, Neil Marlow, Sebastien Ourselin. NeuroImage 2015 doi:10.1016/j.neuroimage.2015.02.010
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The first of hopefully many papers on our GENFI cohort.
Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the Genetic Frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis, Rohrer et al. Lancet Neurology
Dowload the paper here. For the full reference, click read more.
Imaging endpoints for clinical trials in Alzheimer's disease, Cash DM, Rohrer JD, Ryan NS, Ourselin S, Fox NC, Alzheimer's Research and Therapy, 2014 Dec 20;6(9):87. doi: 10.1186/s13195-014-0087-9
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Describes the algorithmical underpinnings of NiftySim's general purpose contact modelling pipeline. Stian F. Johnsen, Zeike A. Taylor, Lianghao Han, Yipeng Hu, Matthew J. Clarkson, David J. Hawkes, and Sebastien Ourselin. International Journal of Computer Assisted Radiology and Surgery. 2015. The article can be downloaded here.
Description of the NiftySim FEM software package, its architecture and use cases. Stian F. Johnsen, Zeike A. Taylor, Matthew J. Clarkson, John Hipwell, Marc Modat, Bjoern Eiben, Lianghao Han, Yipeng Hu, Thomy Mertzanidou, David J. Hawkes, and Sebastien Ourselin. International Journal of Computer Assisted Radiology and Surgery. 2014. The article is available from here.
The NifTK software platform for image-guided interventions: platform overview and NiftyLink messaging, Matthew J. Clarkson, Gergely Zombori, Steve Thompson, Johannes Totz, Yi Song, Miklos Espak, Stian Johnsen, David Hawkes, Sebastien Ourselin, Int J Comput Assist Radiol Surg. 2014 Nov 20. PMID:25408304
The paper can be downloaded here.
In collaboration with the Institute of Nuclear Medicine (UCLH) and the Dementia Research Centre, TIG presented 5 papers at the IEEE NSS-MIC 2014 conference in Seattle. Among them, two were short-listed to participate in the student paper competitions.
The proceedings will soon be available on the IEEE Xplore website.
The purpose of this translational project is to demonstrate the feasibility, robustness, and clinical value of automated image analysis approaches on a large database of routine clinical brain imaging. This position specifically aims at developing a fully automated anomaly detection and triage system for clinical magnetic resonance brain imaging. The successful applicant will also bridge the gap between algorithm developers and end users, enhancing the translation to clinical practice. Additional duties will involve the integration of the developed system into the in-house NifTK software platform and the deployment of a scalable image analysis platform aiming at facilitating ‘big data’ approaches to major neurological disorders.