© 2013 IEEE. The existing efforts in computer assisted semen analysis have been focused on high speed imaging and automated image analysis of sperm motility. This results in a large amount of data, and it is extremely challenging for both clinical scientists and researchers to interpret, compare and correlate the multidimensional and time-varying measurements captured from video data. In this work, we use glyphs to encode a collection of numerical measurements taken at a regular interval and to summarize spatio-temporal motion characteristics using static visual representations. The design of the glyphs addresses the needs for (a) encoding some 20 variables using separable visual channels, (b) supporting scientific observation of the interrelationships between different measurements and comparison between different sperm cells and their flagella, and (c) facilitating the learning of the encoding scheme by making use of appropriate visual abstractions and metaphors. As a case study, we focus this work on video visualization for computer-aided semen analysis, which has a broad impact on both biological sciences and medical healthcare. We demonstrate that glyph-based visualization can serve as a means of external memorization of video data as well as an overview of a large set of spatiotemporal measurements. It enables domain scientists to make scientific observation in a cost-effective manner by reducing the burden of viewing videos repeatedly, while providing them with a new visual representation for conveying semen statistics.
|Original language||English (US)|
|Number of pages||14|
|Journal||IEEE Transactions on Visualization and Computer Graphics|
|State||Published - Aug 2015|
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The authors wish to thank Akanksha Mishra and CelineJones from the Institute of Life Sciences Oxford for theinvaluable advice and feedback during the design process.They are also grateful to Drs. David Foo and HermesGad^elha for discussions at Centre for Human ReproductiveScience, Birmingham Women’s NHS Foundation Trust.Imaging data were captured as part of DJS’s Fellowship(Medical Research Council grant G0600178). This visualiza-tion work was supported by the King Abdullah Universityof Science and Technology, UK EPSRC, and the James Mar-tin Foundation.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.