23 research outputs found
Optimization of a contrast-detail-based method for electronic image display quality evaluation
Performance and function of a high-speed multiple star topology image management system at Mayo Clinic Scottsdale
Proposal of a Quality-Index or Metric for Soft Copy Display Systems: Contrast Sensitivity Study
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
Digitizing radiographic films: a simple way to evaluate indirect digital images
OBJECTIVES: This study applied a simple method to evaluate the performance of three digital devices (two scanners and one digital camera) using the reproducibility of pixel values attributed to the same radiographic image. METHODS: Using the same capture parameters, a radiographic image was repeatedly digitized in order to determine the variability of pixel values given to the image throughout the digitization process. One coefficient value was obtained and was called pixel value reproducibility. RESULTS: A significant difference in pixel values was observed among the three devices for the digitized images (ANOVA, p<0.00001). There was significant pixel value variability at the same digitization conditions for one scanner and the digital camera. CONCLUSIONS: Digital devices may assign pixel values differently in consecutive digitization depending on the optical density of the radiographic image and the equipment. The pixel value reproducibility was not satisfactory as tested for two devices. It is maybe advisable knowing the digitization variations regarding pixel values whenever using digital radiography images in longitudinal clinical examinations