Neuroimaging Analysis in R By Elizabeth Sweeney Abstract: Brain structural magnetic resonance imaging (sMRI) is a tool that uses a magnetic field to produce detailed images of the brain. Brain sMRI are most commonly used to diagnose disease and monitor disease progression and are critically important for disease research. I will introduce the basics of working with brain sMRI data in R. The R packages for these processing steps are housed on neuroconductor (https://neuroconductor.org). Neuroconductor is an open-source platform for rapid testing and dissemination of reproducible computational imaging software. To conclude I will introduce two packages that I authored that are also housed on neuroconductor, sublime and oasis. These packages are both used on brain sMRI in patients with multiple sclerosis. These packages identify or ‘segment’ areas of the brain that contain white matter lesions. Bio: Dr. Elizabeth Sweeney will be starting as an assistant professor in the Division of Biostatistics and Epidemiology at Weill Cornell this May. Previously, she was a senior data scientists at Covera health and before that Flatiron health. At both Covera and Flatiron she worked on research with electronic medical records (EMR) data. Elizabeth completed her PhD in Biostatistics at the Johns Hopkins Bloomberg School of Public health in 2016. Her dissertation research made contributions to the improved analysis of structural magnetic resonance imaging (MRI) in patients with multiple sclerosis. Her interest in this area began with a traineeship at the Nation Institute of Neurological Disease and Stroke, where she did research in an image analysis lab focused on multiple sclerosis. Elizabeth has co-taught a number of tutorials and courses on neuroimage data analysis, including a Coursera course. When not analyzing structural MRI or EMR data, Elizabeth enjoys hiking and biking and is currently working towards her Catskills 3500 Club hiking badge. Twitter: @emsweene57 Presented at the 2019 New York R Conference (May 11th, 2019)