Bicuspid aortic valve (BAV) is the most common congenital heart defect and can lead to severe complications. Many studies have been conducted to evaluate the potential of geometric and hemodynamic biomarkers to predict BAV-related aortopathy. This work proposes a novel semi-automatic protocol to characterize geometry and hemodynamics of aorta and aortic valve based on 2D cine and 4D flow MRI data. The protocol was applied to 12 BAV and 12 control subjects. Statistical differences between the groups were identified and linear regression models were investigated to elucidate the potential of this protocol to investigate the risk of disease progression. Statistical differences between the groups were found for orifice eccentricity, aorta diameter, velocity, jet angle and flow displacement. Key findings of the regression analysis include the association in the proximal ascending aorta between aorta diameter and mean velocity (negative), jet angle (positive) and flow displacement (positive), in the combined cohort. Positive association between flow displacement in the proximal aorta and orifice jet angle in TAV subjects was found. This study represents a pilot application of a protocol for standardized assessment of aortic geometry and hemodynamics associated with BAV disease. Its limited need for user input is advantageous for large cohort studies.