Classification applied to brain haemorrhage detection: Initial phantom studies using electrical impedance measurements

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Date
2018-06-11Author
McDermott, Barry
O'Halloran, Martin
Santorelli, Adam
McGinley, Brian
Porter, Emily
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McDermott, Barry, O'Halloran, Martin, Santorelli, Adam, McGinley, Brian, & Porter, Emily. (2018). Classification applied to brain haemorrhage detection: Initial phantom studies using electrical impedance measurements. Paper presented at the 19th International Conference on Biomedical Applications of Electrical Impedance Tomography, Edinburgh, Scotland, 11-13 June.
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Abstract
Machine learning and classification algorithms are applied to data collected from an EIT system. The system is used with an anatomically accurate head phantom setup in a variety of situations modelling normal and haemorrhagic brain. This initial study demonstrates the promise of classification, but also indicates challenges.