In addition to the inherent qualities of a digital image, the qualities of the monitor and graphics control card as well as the viewing conditions will affect the perceived quality of an image that is displayed on a soft copy display (SD) system. With the implementation of picture archiving and communication systems (PACS), many diagnoses are being made based on images displayed on SD devices, and consequently SD quality may affect the accuracy of diagnosis. Unlike the traditional film-on-lightbox display, optimal SD system parameters are not well defined, and many issues remain unsettled. In this article, the human observer performance, as measured by contrast sensitivity, for several SD devices including an active matrix liquid crystal flat panel monitor is reported. Contrast sensitivities were measured with various display system configurations. Experimental results showed that contrast sensitivity depends on many factors such as the type of monitor, the monitor brightness, and the gamma settings of the graphics card in a complex manner. However, there is a clear correlation between the measured contrast thresholds and the gradient of the display device's luminance response curve. Based on this correlation, it is proposed to use the gradient of luminance response curve as a quality-index or metric for SD devices.KEY WORDS: Soft copy display, contrast sensitivity, gradient of luminance response curve, display quality index, human observer performance A DISPLAY SYSTEM is the final link between the acquired image data and the eye-brain system of the human observer. Obviously the quality of a soft copy display (SD) system has a direct impact on the perceived image quality, and various components of an SD system can affect the performance of the human observer. 1-15 An SD system typically includes a monitor (either CRT or LCD flatpanel) and a graphics control card. An SD system is more complex than a conventional film/lightbox (the hard copy) display system, and it has many varieties. In radiology, the increasing number of picture archiving and communication system (PACS) implementations worldwide has led to an increasing number of diagnostic decisions being made based on images that are displayed on computer monitors. However, the quality of SD systems varies and there is no common, easy-to-use quality index to determine and to compare the quality of a display or to predict a user's performance. Furthermore, image processing and manipulation may partially compensate for an SD system's contrast and spatial resolution deficiency. 7,16,17 For instance, zooming in on an image on an SD work station can compensate for the spatial resolution limitations of the monitor. Also, it is possible to adjust image contrast by ''windowing and leveling'' of an image. However, these adjustments decrease a user's performance efficiency. Thus, it is important to ensure the optimization of the entire SD system so that unnecessary adjustments are minimized.