by Hemminger, Bradley M.; Bauers, Anne; Yang, Jian

Medical images are examined on computer screens in a variety of contexts. Frequently, these images are larger than computer screens, and computer applications support different paradigms for user navigation of large images. The paper reports on a systematic investigation of what interaction techniques are the most effective for navigating images larger than the screen size for the purpose of detecting small image features. An experiment compares five different types of geometrically zoomable interaction techniques, each at two speeds (fast and slow update rates) for the task of finding a known feature in the image. There were statistically significant performance differences between several groupings of the techniques. The fast versions of the ArrowKey, Pointer, and ScrollBar performed the best. In general, techniques that enable both intuitive and systematic searching performed the best at the fast speed, while techniques that minimize the number of interactions with the image were more effective at the slow speed. Additionally, based on a postexperiment questionnaire and qualitative comparison, users expressed a clear preference for the Pointer technique, which allowed them to more freely and naturally interact with the image.

DOI: 10.1007/s10278-008-9133-0
Online Date: 6/27/2008
Print publication date: 10/1/2008
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by Langer, Steve

Picture-archiving and communication systems are complex entities, but at core they consist of compute processors that are networked together to store and retrieve objects. Therein lay fundamental aspects of both performance benchmarking and predicting future costs, provided one can accurately predict trends in both exam volumes and sizes. Hence, determining the correct amount of capital to reserve annually for the information technology infrastructure can be a difficult process for the administrator of a medical center. Both exam volumes and sizes tend to increase over time. In addition, users demand more compute-intensive applications and expect exam delivery to the desktop to be ever timelier despite the increase in size. Against this, storage, compute, and networking costs tend to decrease over time for the same performance level. At the end of the day, the question of whether to budget more or less capital for next year’s infrastructure is not trivial. This paper develops a methodology that uses current baseline data to predict the “ampleness” of a budget to meet future needs.

DOI: 10.1007/s10278-008-9126-z
Online Date: 6/3/2008
Print publication date: 8/1/2009
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