Research on Graphical Interfaces to Perform Anatomical Queries on Large Collections of Gene Expression Images

Yan Cai

Supervisor(s): Katja B├╝hler

VRVis Research Center

Abstract: How to find the most interesting image when tens of thousands are involved? How to present relevant information to help users gain a deeper understanding of this data? As image information is increasing sharply, searching and presenting of images in large databases became more and more important in image management. In this paper, we focus on large neuro-anatomical image collections of Drosophila (fruit fly) brains. Our goal is to propose a design for optimizing a graphical query interface for anatomical search to present more valuable information behind the images and also improve the usability. In order to achieve this, we first investigated different relevant websites such as "Fly Circuit'', "Fly Light'' and "Allen Mouse Brain Atlas'' and also image management programs such as PivotViewer and Zegami, analyze and compare these websites and programs with different perspectives, and try to defines guidelines for best practices out of them. Based on our findings we propose several mockups for neuro-anatomical query interfaces.
Keywords: Design, Human-Computer Interaction
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Year: 2017