
doi: 10.1145/2834117
This article describes the design and evaluation of two generations of an interface for navigating datasets of gigapixel images that pathologists use to diagnose cancer. The interface design is innovative because users panned with an overview:detail view scale difference that was up to 57 times larger than established guidelines, and 1 million pixel “thumbnail” overviews that leveraged the real estate of high-resolution workstation displays. The research involved experts performing real work (pathologists diagnosing cancer), using datasets that were up to 3,150 times larger than those used in previous studies that involved navigating images. The evaluation provides evidence about the effectiveness of the interfaces and characterizes how experts navigate gigapixel images when performing real work. Similar interfaces could be adopted in applications that use other types of high-resolution images (e.g., remote sensing or high-throughput microscopy).
Human-centered computing - Empirical studies in HCI, Gigapixel images, Humancentered computing - Interaction design theory, Human-centered computing - Visualization systems and tools, pathology, zoomable user interface, concepts and paradigms, navigation, overview+detail
Human-centered computing - Empirical studies in HCI, Gigapixel images, Humancentered computing - Interaction design theory, Human-centered computing - Visualization systems and tools, pathology, zoomable user interface, concepts and paradigms, navigation, overview+detail
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