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Child brain tumours can be classified by advanced imaging and AI

  • Brain tumours are the most common solid tumours in childhood and the largest cause of death from cancer in this age group
  • Being able to classify a brain tumour’s type, without the use of biopsy, is hard to do; however diffusion weighted imaging, an advanced imaging technique, when combined with machine learning, can help a UK-based multi-centre study, including WMG, University of Warwick has found.
  • Being able to characterise the tumour(s) faster and more accurately means they can be treated more efficiently

Diffusion weighted imaging and machine learning can successfully classify the diagnosis and characteristics of common types of paediatric brain tumours a UK-based multi-centre study, including WMG at the University of Warwick has found. This means that the tumour can be characterised and treated more efficiently.

New IDH paper on modelling human heart mechanics

Profs Mark Williams’ and Theo Arvanitis’ research groups publish a new paper, proposing for the first time a numerical approach to investigate the effect of fibre-angle distribution in the dysfunction of myocardial fibre structure of left-ventricle of the human heart, The work was done in collaboration with colleagues at University Hospitals Coventry and Warwickshire. Find more at

Fri 20 Feb 2015, 11:33 | Tags: Publications

Two new publications for Prof Thomas Nichols

IDH Professor Thomas Nichols has co-authored two new papers on Human Brain Structures and neuroimaging data

Fri 20 Feb 2015, 10:30 | Tags: Publications, Research, fMRI, Tom Nichols

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