This study investigates automatic assessment of the left ventricular (LV) diastolic function using cine cardiac magnetic resonance (MR) imaging. Most of the existing LV assessment algorithms addressed the systolic function, which essentially pertains to the analysis of regional wall motion abnormalities or the estimation of the ejection fraction. However, several recent clinical studies suggested that evaluating the diastolic function is essential. The diastolic function plays an important role in assessing cardiovascular abnormalities, particularly in the case of heart failure with preserved ejection fraction. The assessments of LV relaxation and stiffness abnormalities can be achieved with cardiac MR imaging. Unlike with transthoracic echocardiography, MR is not limited by an acoustic window, and allows exhaustive myocardial imaging with excellent spatial resolution. We propose an algorithm that evaluates the LV relaxation from short-axis cine MR images. The method is based on three main steps: (1) non-rigid registration, which yields a sequence of points over time, given a user-provided contour on the first frame; (2) computations of the LV filling rate and volume over the cardiac cycle; and (3) automatic detection of the maxima of the E and A waves. We report comprehensive experimental evaluations over MR data sets acquired from 53 subjects, including comparisons with independent reports for the same subjects from echocar-diography. The proposed algorithm yielded a Kappa measure of 0.66, a substantial agreement with the echocardiography results.