An interactive visual analysis tool for cellular behavior studies using large collections of microscopy videos

Chuan Wang, Jia Kai Chou, Kwan-Liu Ma, Arpad Karsai, Ying X. Liu, Evgeny Ogorodnik, Victoria Tran, Gang-yu Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an interactive visual analysis tool created for studying collections of video data. Our driving application is cellular behavior studies that use microscopy imaging methods. The studies routinely generate large amounts of videos with various experimental conditions. It is very time-consuming for the scientists to watch each video and manually extract features-of-interest for further comparative and quantitative studies. We show that with our visualization tool, scientists are now able to conveniently observe, select and isolate, and compare and analyze the cellular behaviors from different perspectives within one framework. The tremendous time and effort saved allow scientist to focus on deriving the actual meaning behind certain observed behaviors.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 2nd International Conference on Multimedia Big Data, BigMM 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781509021789
DOIs
StatePublished - Aug 16 2016
Event2nd IEEE International Conference on Multimedia Big Data, BigMM 2016 - Taipei, Taiwan, Province of China
Duration: Apr 20 2016Apr 22 2016

Other

Other2nd IEEE International Conference on Multimedia Big Data, BigMM 2016
CountryTaiwan, Province of China
CityTaipei
Period4/20/164/22/16

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Media Technology

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    Wang, C., Chou, J. K., Ma, K-L., Karsai, A., Liu, Y. X., Ogorodnik, E., Tran, V., & Liu, G. (2016). An interactive visual analysis tool for cellular behavior studies using large collections of microscopy videos. In Proceedings - 2016 IEEE 2nd International Conference on Multimedia Big Data, BigMM 2016 (pp. 1-8). [7544989] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigMM.2016.67