Limits...
Comparison of navigation techniques for large digital images.

Hemminger BM, Bauers A, Yang J - J Digit Imaging (2008)

Bottom Line: There were statistically significant performance differences between several groupings of the techniques.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.

View Article: PubMed Central - PubMed

Affiliation: School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3360, USA. bmh@ils.unc.edu

ABSTRACT
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.

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MagLens magnification area vs area covered by the lens. ZLB is ZL3 and ZLC is ZL4 for the MagLens interaction method.
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Fig2: MagLens magnification area vs area covered by the lens. ZLB is ZL3 and ZLC is ZL4 for the MagLens interaction method.

Mentions: MagLens The slow version of the MagLens technique performed fairly well; it was faster on average than the Pointer and ArrowKey slow techniques. However, the fast MagLens was the worst performing technique in the test set. While the MagLens technique can be particularly useful for spot checking for targets, its lack of support for systematic searching may have placed it at the bottom of the list of target-finding techniques.Participants using both versions of the MagLens used similar strategies to search for targets. They would examine the full image to identify locations where the target was likely to be located. They would then zoom in one or two times in the likely locations and pan around those areas looking for the target. This selective magnification technique was fairly successful for most participants. The participants with faster average times per image, using both versions of the technique, were very adept at picking out targets using this method.If selective magnification was not successful, participants would move to a full scan of the image. Full scanning involved moving the magnification lens, at either ZL3 or ZL4, over the entire image in a lawnmower motion. Five of the participants avoided scanning with ZL4 if possible, only moving to that zoom level after a full scan with ZL3 did not produce a result. As one participant explained, “If you use the highest level of zoom [ZL4], it is easier to see objects but harder to scan, because you lose the context of where you are looking.”In comparison to participants using other techniques, MagLens participants spent a lot of time examining the full image. This is likely related to the fact that they had access to the full image even when they were utilizing the two zoom levels. Unlike users of the Sectional technique, participants seemed to struggle with the two levels of zoom. Although no participants explicitly requested an extra level of zoom, one participant explained, “Though two levels of zoom were necessary for locating the targets, scanning on the highest level [ZL4] was nearly impossible, but it was difficult to recognize the objects on the other level [ZL3].”Participants using both versions of the MagLens struggled with knowing exactly where they had already scanned. This problem is exacerbated (in both versions of the technique) by the fact that the area that is magnified in the lens is much smaller than the area that is covered by the lens; in other words, when a small area is being magnified, a large area around it is neither visible under the lens or visible in the full-image view. See Fig. 2 for an illustration of this loss of context.Fig. 2


Comparison of navigation techniques for large digital images.

Hemminger BM, Bauers A, Yang J - J Digit Imaging (2008)

MagLens magnification area vs area covered by the lens. ZLB is ZL3 and ZLC is ZL4 for the MagLens interaction method.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3043868&req=5

Fig2: MagLens magnification area vs area covered by the lens. ZLB is ZL3 and ZLC is ZL4 for the MagLens interaction method.
Mentions: MagLens The slow version of the MagLens technique performed fairly well; it was faster on average than the Pointer and ArrowKey slow techniques. However, the fast MagLens was the worst performing technique in the test set. While the MagLens technique can be particularly useful for spot checking for targets, its lack of support for systematic searching may have placed it at the bottom of the list of target-finding techniques.Participants using both versions of the MagLens used similar strategies to search for targets. They would examine the full image to identify locations where the target was likely to be located. They would then zoom in one or two times in the likely locations and pan around those areas looking for the target. This selective magnification technique was fairly successful for most participants. The participants with faster average times per image, using both versions of the technique, were very adept at picking out targets using this method.If selective magnification was not successful, participants would move to a full scan of the image. Full scanning involved moving the magnification lens, at either ZL3 or ZL4, over the entire image in a lawnmower motion. Five of the participants avoided scanning with ZL4 if possible, only moving to that zoom level after a full scan with ZL3 did not produce a result. As one participant explained, “If you use the highest level of zoom [ZL4], it is easier to see objects but harder to scan, because you lose the context of where you are looking.”In comparison to participants using other techniques, MagLens participants spent a lot of time examining the full image. This is likely related to the fact that they had access to the full image even when they were utilizing the two zoom levels. Unlike users of the Sectional technique, participants seemed to struggle with the two levels of zoom. Although no participants explicitly requested an extra level of zoom, one participant explained, “Though two levels of zoom were necessary for locating the targets, scanning on the highest level [ZL4] was nearly impossible, but it was difficult to recognize the objects on the other level [ZL3].”Participants using both versions of the MagLens struggled with knowing exactly where they had already scanned. This problem is exacerbated (in both versions of the technique) by the fact that the area that is magnified in the lens is much smaller than the area that is covered by the lens; in other words, when a small area is being magnified, a large area around it is neither visible under the lens or visible in the full-image view. See Fig. 2 for an illustration of this loss of context.Fig. 2

Bottom Line: There were statistically significant performance differences between several groupings of the techniques.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.

View Article: PubMed Central - PubMed

Affiliation: School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3360, USA. bmh@ils.unc.edu

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus