Image analysis tools are used for the extraction of clinical data from Doppler Echocardiography images. Currently, manual methods are subject to large inter- and intra-observer variability. The proposed automated methodology may provide a more robust method and a powerful tool for noninvasive evaluation of cardiac haemodynamics, especially for patients with Atrial Fibrillation (ATF). ATF patients suffer from a non-homogenous heart rate, and the shape of the Doppler signal obtained from them differs from beat to beat. This variability requires the averaging of several measures in order to produce acceptable clinical data. The presented methodology works on signals from the Mitral Valve (MV) and the Tricuspid Valve (TV), and detects the envelope of the velocity vs. time function, the Maximal Velocity Envelope (MVE). From the MVE, clinical data is extracted, such as the peak velocity and the area beneath the curve. Parameters taken from several beats in a single image are averaged in order to provide more representative and robust results. Experimental results show a strong correlation between the automatically extracted parameters and parameters acquired manually by an Echo technician.