Synthetic Brainbows

Y. Wan, H. Otsuna, C. Hansen

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Brainbow is a genetic engineering technique that randomly colorizes cells. Biological samples processed with this technique and imaged with confocal microscopy have distinctive colors for individual cells. Complex cellular structures can then be easily visualized. However, the complexity of the Brainbow technique limits its applications. In practice, most confocal microscopy scans use different florescence staining with typically at most three distinct cellular structures. These structures are often packed and obscure each other in rendered images making analysis difficult. In this paper, we leverage a process known as GPU framebuffer feedback loops to synthesize Brainbow-like images. In addition, we incorporate ID shuffing and Monte-Carlo sampling into our technique, so that it can be applied to single-channel confocal microscopy data. The synthesized Brainbow images are presented to domain experts with positive feedback. A user survey demonstrates that our synthetic Brainbow technique improves visualizations of volume data with complex structures for biologists.
Original languageEnglish (US)
Pages (from-to)471-480
Number of pages10
JournalComputer Graphics Forum
Issue number3pt4
StatePublished - Jul 1 2013
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: This research was sponsored by NIH-1R01GM098151-01, the DOE NNSA Award DE-NA0000740, KUS-C1-016-04 made by King Abdullah University of Science and Technology (KAUST), DOE SciDAC Institute of Scalable Data Management Analysis and Visualization DOE DE-SC0007446, NSF OCI-0906379, NSF IIS-1162013. We would like to thank A. Kelsey Lewis and her colleagues of the Department of Human Genetics at the University of Utah for a good explanation of the Brainbow technique. We also want to thank all the biologists participated in the survey. The reviewers' comments are very encouraging and helpful to us.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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