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Abstract #4330

Automatic sodium maps reconstruction using PatchMatch algorithm for phantom detection

Ferran Prados1,2, Bhavana S Solanky2, Patricia Alves Da Mota2, Manuel Jorge Cardoso1, Wallace J Brownlee2, Niamh Cawley2, David H Miller2, Xavier Golay3, Sebastien Ourselin1, and Claudia Angela Michela Gandini Wheeler-Kingshott2,4

1Translational Imaging Group, Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 2NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom, 3Brain Repair & Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom, 4Brain Connectivity Center, C. Mondino National Neurological Institute, Pavia, Italy

Quantitative sodium magnetic resonance imaging (23Na-MRI) enables the non-invasive measurement of in vivo total 23Na concentration (TSC) in the human brain. This involves a complex process of reconstructing datasets acquired to calculate a TSC map. Quantitative TSC map calibration relies on external reference phantoms with known concentration for linear calibration. This commonly involves manually segmenting the phantoms by trained raters, hindering automatic image analysis, and presenting a bottleneck in the TSC computation. We propose to substitute the manual segmentation by OPAL, a novel, fast, robust and reliable technique for segmenting sodium phantoms that allows fully-automatic reconstruction of TSC maps.

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