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Abstract #0264

A ranking of pipelines for optimal co-registration of anatomical and diffusion weighted images of the cervical spinal cord

Stephanie Alley1, Francesco Grussu1, Marios C. Yiannakas1, Hugh Kearney1, Olga Ciccarelli1, Ferran Prados1,2, S├ębastien Ourselin2, and Claudia AM Gandini Wheeler-Kingshott1,3,4

1UCL Institute of Neurology, Queen Square MS Centre, University College London, London, United Kingdom, 2Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 3Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy, 4Brain MRI 3T Mondino Research Center, C. Mondino National Neurological Institute, Pavia, Italy

We conduct the first systematic evaluation of the performance of three widely used registration software toolkits (FLIRT from FSL, NiftyReg and ANTs employing Spinal Cord Toolbox) in an effort to outline a method for reliable co-registration between anatomical and quantitative (EPI-based) spinal cord MRI. We generate a diverse set of registration pipelines and rank them according to quality of co-registration metrics. We find that ANTs and NiftyReg outperform FLIRT, and we report heterogeneity of specifications for optimal co-registration among software toolkits.

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