There is an urgent need for a measurement protocol and software analysis for objective testing of the imaging performance of medical ultrasound equipment from a user's point of view. Methods for testing of imaging performance were developed. Simple test objects were used, which have a long life expectancy. First, the elevational focus (slice thickness) of the transducer was estimated and the in-plane transmit focus was positioned at the same depth. Next, the postprocessing look-up-table (LUT) was measured and linearized. The tests performed were echo level dynamic range (dB), contrast resolution (i.e., gamma of display, number of gray levels/dB) and sensitivity, overall system sensitivity, lateral sensitivity profile, dead zone, spatial resolution and geometric conformity of display. The concept of a computational observer was used to define the lesion signal-to-noise ratio, SNR(L) (or Mahalanobis distance), as a measure for contrast sensitivity. All the measurements were made using digitized images and quantified by objective means, i.e., by image analysis. The whole performance measurement protocol, as well as the quantitative measurements, have been implemented in software. An extensive data-base browser was implemented from which analysis of the images can be started and reports generated. These reports contain all the information about the measurements, such as graphs, images and numbers. The approach of calibrating the gamma by using a linearized LUT was validated by processing simultaneously acquired rf data. The contrast resolution and echo level of the rf data had to be compressed by a factor of two and amplified by a gain factor corresponding to 12 dB. This resulted in contrast curves that were practically identical to those obtained from DICOM image data. The effects of changing the transducer center frequency on the spatial resolution and contrast sensitivity were estimated to illustrate the practical usefulness of the developed approach of quality assurance by measuring objective performance characteristics. The developed methods might be considered as a minimum set of objective quality assurance measures. This set might be used to predict clinical performance of medical ultrasound equipment, taking into account the performance at a unique point in space i.e., the coinciding depths of the elevation and in-plane (azimuth) foci. Furthermore, it should be investigated whether the approach might be used to compare objectively various brands of equipment and to evaluate the performance specifications given by the manufacturer. Last but not least, the developed approach can be used to monitor, in a hospital environment, the medical ultrasound equipment during its life cycle. The software package may be viewed and downloaded at the website http://www.qa4us.eu.