Comparison of navigation techniques for large digital images

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.