M Pietsch1, A Schlaefke, T J Vogl, B Bergh. 1. Department of Information Technology and Biomedical Engineering, Universitätsklinikum Heidelberg, Tiergartenstrasse 15, 69121, Heidelberg, Germany.
Abstract
OBJECTIVES: The aim of this study was to develop and verify different methods of measuring time-to-display (TTD) for radiological images with image web systems (IWS). The process should be automatable in order to repeatedly perform a large number of measurements without human interaction. MATERIALS AND METHODS: Three methods were defined and compared with respect to usability, stability, and quality of results. Method 1 was based on Windows 2000 Performance Monitor, whereas method 2 employed phototransistors taped to the screen and connected to a separate PC. A software tool developed for method 3, which used Windows application programming interface (API) function, calls to read the color code assigned to specific pixels on the screen. RESULTS: Method 3 proved to be the most reliable and easy to automate. The accuracy is practically equivalent to method 2, but it proved to be far more automatable. Method 1 produced the largest mean error, was easily disturbed, but was also easy to set up and provided additional insights into the system's architecture especially if combined with method 3. CONCLUSIONS: To measure the performance of image distribution systems, any of these methods can be used, but method 3 proved to be superior.
OBJECTIVES: The aim of this study was to develop and verify different methods of measuring time-to-display (TTD) for radiological images with image web systems (IWS). The process should be automatable in order to repeatedly perform a large number of measurements without human interaction. MATERIALS AND METHODS: Three methods were defined and compared with respect to usability, stability, and quality of results. Method 1 was based on Windows 2000 Performance Monitor, whereas method 2 employed phototransistors taped to the screen and connected to a separate PC. A software tool developed for method 3, which used Windows application programming interface (API) function, calls to read the color code assigned to specific pixels on the screen. RESULTS: Method 3 proved to be the most reliable and easy to automate. The accuracy is practically equivalent to method 2, but it proved to be far more automatable. Method 1 produced the largest mean error, was easily disturbed, but was also easy to set up and provided additional insights into the system's architecture especially if combined with method 3. CONCLUSIONS: To measure the performance of image distribution systems, any of these methods can be used, but method 3 proved to be superior.
Authors: Kenneth W Clark; David L Melson; Stephen M Moore; G James James Blaine; Ralph A Moulton; William K Clayton; Colin S Peterson; Bruce A Vendt Journal: J Digit Imaging Date: 2003-12-15 Impact factor: 4.056
Authors: E Bellon; J Wauters; J Fernàndez-Bayó; M Feron; K Verstreken; J Van Cleynenbreugel; B Van den Bosch; M Desmaret; G Marchal; P Suetens Journal: Med Inform (Lond) Date: 1997 Oct-Dec