Non-alcoholic fatty liver disease (NAFLD) has become the most common liver disease with an estimated global prevalence of 25%. Its link to metabolic, cardiovascular, and more severe forms of liver disease presents a major challenge for future healthcare. MRI allows accurate quantification of liver fat concentration. Since manual delineation of the liver is time-consuming, measurements are typically performed in small subjectively selected regions of interest which limits accuracy and precision. This work presents an automated method for liver fat assessment using multi-atlas segmentation. Evaluation with measurements using manual liver segmentation (n=306) demonstrates excellent agreement (R=1.000, difference -0.03%, p=0.001).