Deep-learning-assisted visualization for live-cell images | IEEE Conference Publication | IEEE Xplore

Deep-learning-assisted visualization for live-cell images


Abstract:

Analyzing live-cell images is particularly challenging because cells simultaneously move and undergo systematic changes. Visually inspecting live-cell images therefore in...Show More

Abstract:

Analyzing live-cell images is particularly challenging because cells simultaneously move and undergo systematic changes. Visually inspecting live-cell images therefore involves simultaneously tracking individual cells and detecting relevant spatio-temporal changes. The high cognitive burden of such a complex task makes this kind of analysis inefficient and error prone. In this paper, we describe a deep-learning-assisted visualization based on automatically derived high-level features to identify target cell changes in live-cell images. Applying a novel user-mediated color assignment scheme that maps abstract features into corresponding colors, we create color-based visual annotations that facilitate visual reasoning and analysis of complex time-varying live-cell image datasets.
Date of Conference: 17-20 September 2017
Date Added to IEEE Xplore: 22 February 2018
ISBN Information:
Electronic ISSN: 2381-8549
Conference Location: Beijing, China

References

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