In cardiovascular diagnostics, the knowledge of blood pressure is essential for the physician. Nowadays, blood pressures
are usually obtained by catheter measurements or sphygmomanometric methods. These techniques suffer from different
drawbacks in terms of invasiveness, observable vessels and the resolution of the pressure values, respectively. Magnetic
resonance imaging (MRI) offers a promising approach to establish a method for blood pressure measurements that is
able to overcome these difficulties. Phase-contrast MRI is used to acquire velocity-encoded data. Fluid pressure
gradients can be derived from the measured velocities using the Navier-Stokes equations. Unfortunately, this technique
is known to suffer from a strong sensitivity to imaging quality. Especially the low signal-to-noise ratios (SNR) of phase
contrast MRI data combined with the limited spatial and temporal resolution could severely reduce the reliability of
computations. In this paper, we analyze computations of blood pressure gradients based on phase contrast MRI
measurements of steady and pulsatile flow in a phantom. The influence of image quality of the velocity-encoded data as
well as of different segmentation techniques is evaluated. In case of steady flow, the pressure gradient values computed
via Navier-Stokes equations show good agreement with theoretical values if physical a-priori knowledge is incorporated.
If a pulsatile aortic flow profile is applied, the computed pressure gradients generally match catheter measurements well.
Nevertheless, an underestimation of pressure gradient peaks is observed. Different segmentation techniques influence the
size of root mean squared errors between computation and measurement as well as their reduction by the use of higher